Category

General

Dec 20
0

Sell Side Are From Mars, Buy Side Are From Venus

By | General | No Comments

 

Sell Side Are From Mars, Buy Side Are From Venus

by Mark Artherton – Senior Content Strategist, Smartkarma

Posted on Smartkarma on 15th December 2017
Read more of Mark’s work by clicking here!

I really enjoyed reading Douglas Kim’s Confessions of an Independent Research Analyst – though in the UK ‘Confessions…’ are more linked to a series of smutty 1970s films – cultural factors play such an important part in headlines!  Thankfully we have moved on a lot from the casual misogynism of the 1970s (though maybe not far enough).  While Douglas Kim paints a strong and compelling picture from one side of the research divide, the demand side is a curious beast.  Prior to starting LR Research, I worked for 17 years on the buy side in institutional long-only firms and hedge funds, reaching a level where I was running GBP7bn across Emerging Markets and Asia as the head of a team of 14 portfolio managers and analysts.  Through my career, I have seen a number of buy-side ‘organisational models’ first hand.  Fundamental, active portfolio management is not a homogenous entity, there are almost as many processes as there are investment teams.  The sell side has developed best to support the largest clients with the biggest voices (and wallets), but the wants and desires of the buy side are still poorly served in my opinion.

I am a great believer in the power of path dependence in life and markets.  Investment research has its own path dependence and therefore it is important to consider the history of investment research.  This path dependency has brought the investment industry to a situation where neither side feels fulfilled, but there is a general reluctance to break away from historical mechanisms of research production and consumption.

The development of the buy side/sell side relationship

The way the traditional investment research model developed came from a very narrow set of circumstances existing mainly in the US and to a lesser extent the UK as the capital markets developed through the 19th and 20th centuries.

In the late 19th century and early 20th century, capital markets in the UK and US were well established and Investment Trusts had expanded the pool of investors to include those with lower means.  Institutional investors saw strong growth of their assets during the early decades of the 20th century.

A sample of 33,078 shareholders in 261 company share registers relating to 47 UK-registered companies, spread across all sectors for the period 1870 to 1935, reveals that only 505 of the shareholders were institutional investors. They held 4.2% of the value of these securities in the decade of the 1900s, 7.7% in the 1910s, 6.0% in the 1920s, and 23.8% by the 1930s. The remaining securities were held by individual investors either directly or through personal trusts (Rutterford, Green, Maltby, and Owens 2010).

Undoubtedly there was investment research provided by third parties in the first 50 years of the 20th century and this would have been ‘independent’, but personal connections played a much larger part in the ‘research’ process.  Stockbrokers would advise high net worth individual investors based upon their contacts in the corporate, political and financial sphere.

Moreover, they said that investment decisions in UK investment trusts relied on ‘the personal judgements of the managers and directors, who … depend to a considerable extent on personal contacts and the advice of brokers … The operation of the law of averages is relied on to minimize the effect of mistaken judgments. (Chamberlain and Hay, 1931)’

In the UK (where the ‘old school tie’ network dominated), the asset management industry had a reputation for long lunches and being populated by the underachieving younger son of a well to do family – there was a need for well-informed research to address this base of customers.  That is not to say that there were not talented individuals managing funds in the UK, but in general, the level of professionalism was lower than it is today.

In the US, the Investment Trust industry was purported to be more professional with in-house research departments being well stocked in the early 20th century, but the bull market of the 1920s led to the rapid abandonment of research in favour of blind buying.

Most paradoxical was the early abandonment of research and analysis in guiding investment trust policies. Investment had now become so beautifully simple that research was unnecessary and statistical analysis a mere encumbrance. Hence the sound policy was to buy what everyone else was buying … The man in the street, having been urged to entrust his funds to the superior skill of investment experts—for substantial compensation— was soon reassuringly told that the trusts would be careful to buy nothing except what the man in the street was buying himself. (Graham and Dodd 1934, p. 311)

Prior to the bubble in stocks in the 1920s, common stocks were valued in a way more akin to bonds.  Stockbrokers would use their connections to look for the dividend potential and the stability of corporate cash flows and recommend such investments to their clients, capital appreciation was much less important.  The bubble in the 1920s changed this and dragged in more and more individual investors and the selling techniques deteriorated rapidly.  The subsequent market crash and depression in the 1930s was followed by the second world war.

After the second world war, in the US in the 50s and 60s, the investment landscape had changed again, with most asset managers coming from corporate pension funds, with little or no experience of investment.  As the 60s progressed into the 70s in the US there was more professionalism but a lot of trading was led by information that would now be considered inside information (insider trading regulations have been in place in the USA since 1904, but it was the Insider Trading Sanctions Act of 1984 and the Insider Trading and Securities Fraud Enforcement Act of 1988 that put a significant halt on the practice).

The huge growth of corporate pension fund assets in the 1960s led to the search for performance and ways to reduce the reliance on one manager.   This search was triggered by underperformance and regulatory change.  In the US, the buy side was underperforming in the 60s – a survey by AG Becker & Co. in 1968 found significant underperformance of corporate pension assets (AG Becker actually formed one of the first pension consultancies on the back of this work).  In the 1960s, ‘Performance’ funds emerged with ‘film star’ like fund managers and they gathered significant assets.  The underperformance of corporate pension funds and the star power of mutual fund ‘performance’ fund managers led to the eventual market crash that began in 1969.  These contrasting performance issues and regulatory change led to increased demand for professional research services.

The major regulatory change in the 1970s was the advent of Employment Retirement Income Security Act (ERISA) in 1974, which led to the creation and huge growth in 401K retirement plans.   The ‘Prudent Man’ rule in the 1970s led asset managers to look for professional advice, especially in equities.

The brokerage community was not slow to react to the increased demand for third-party investment research.  The brokerage community was working under fixed rate commissions in the United States prior to the regulatory change of ‘May Day’ in 1975.  In this pre-1975 environment, the only way to compete was by offering bundled services, services paid for by ‘soft dollars’.  The research departments set up by brokerages were, in effect, independent.  Brokerages did no trading or investment banking on their own book, they acted solely as a middleman with a fixed fee.

Donaldson, Lufkin & Jenrette (DLJ) were amongst the first to offer the services of an analyst/salesman (Interestingly, DLJ’s history is the basis of current wall street, they were the first NYSE member firm to IPO – changing NYSE bylaws along the way – and set up the current situation of taking on risk with other people’s capital).

DLJ and other firm’s analysts were highly regarded and built close relationships with companies and pension funds.  The long form report really took off in the late 60s, and financial analysis became easier with the appearance of the first calculator (the first portable calculator came to market in 1970).  Investor’s time horizons were longer in the 1970s (chart 1) and there was no real focus upon quarterly returns and earnings.

One could argue that the golden age of independent equity research happened between 1965 and 1975 when DLJ and others started covering mid and small cap equities in the US.  DLJ was able to pick up new clients by expanding coverage and this encouraged ‘waterfront’ coverage over time.

Chart 1 – Average equity holding periods

Investment reports now are little changed from this era, but the marketplace has changed dramatically, led by the change in regulation.  The first ‘unbundling’ event happened in May 1975.  To encourage competition in brokerage fees the SEC forced the unbundling of other services.  The industry did manage to successfully argue that investment research should not be ‘unbundled’ and this led to the ‘Safe Harbour’ Regulation, and the eventual embedding of investment research in the large investment banks.

The rapid reduction in brokerage commissions due to competition forced a wave of mergers on Wall Street.  Firms combined investment banking, brokerage, trading and research, reducing the independence of research along the way.   Research analysts had been offering corporate advice prior to this wave of mergers, but investment bankers more fully exploited the advantages of having an analyst who faced both the buy side and the corporate side.

In the late 1970s and early 1980s, equity analysts fell out of favour due to weak stock markets.  Bond analysts were much more in favour.  Mutual funds also started to build up their own ‘in-house’ research departments.  The resumption of the Bull market in equities in the early 90s, led to the rise of the ‘rock star’ analyst, especially in the tech sector.  This was the most recent peak of the sell-side analyst.  After the Nasdaq bubble and the scandals surrounding a number of the ‘rock stars’, the market settled into the fairly familiar pattern of today.  The vast bulk of research is provided to investment managers ‘for free’ as a bundled service.  This research has potential and real conflicts of interest and has not changed in format since the mid-1960s.

The history of investment research is quite US-centric, but the format and structure of the research report were set in the US market and in my experience, other markets have copied this approach for their institutional service.  The rules and regulations surrounding the production of research in each jurisdiction may differ but generally, the research has been bundled with commissions for many years.  MIFID II changes this for European markets and is forcing a much greater focus on the cost and profitability of investment research.  With pressure on active management fees, there is scope for significant disruption to occur in the provision of third-party investment research.

The 20th century shifted through phases with the high point of investment research occurring in the late 60s and early 70s.  This model of Research that developed was then co-opted by the large investment banks as a way to drive their agenda.  There was little need to change the model as research was not the driving force behind client relationships.  Clients had little incentive to press for change as they were, in effect, receiving a free service and the tail began wagging the dog.

Where are we now?

For the past 50 years, the buy and sell side have been growing further apart.  Rather like a couple who are forced to consider their relationship and suddenly find that they have little in common.  The wealthier couples have found a way to make it work, but the rest are searching for a way to move things forward.

The old standard of ‘give me a well-researched recommendation and if I trust you I will trade with you’ has disappeared in a fog of mistrust and oversupply.  There is no way back to those simpler days, things have changed too much and regulators would not allow it.  There is still a demand for external investment research.  What is important now, is how that research is delivered and how it is monetised.  The traditional sell-side is moving with the times, but they have significant baggage.  As I have argued previously MIFID II will give investment banks the incentive to invest and innovate in their research product.  Independent Investment Research has been around for decades but is yet to provide innovation that disrupts existing solutions in a meaningful way.  There are many talented individuals in the Independent Investment Research space but it has proven difficult to move beyond the traditional ‘consultancy’ style model.

The likes of BCA and Ned Davies Research have been around for years, grew in size and been purchased by a larger entity (EuroMoney).   Both firms are characterised as being based on standardised templates, charts and quantitative factors as well as the quality of their analysts.  Bloomberg has also tried to move in this direction with standardised charting supporting their industry analysis, for example.  The large data houses will become more incentivised to sell analysis along with their data and charting capabilities.  As publishing converges with data provision in the marketplace this will put more pressure on investment bank research provision and the traditional independent research approach.

The current marketplace for independent research is characterised by:

  • the need for best execution and MIFID II delinking trading from investment research;
  • chronic over-supply of research in some areas and under-supply in others;
  • an explosion in different forms of asset management;
  • and a lack of innovation in the production and delivery of investment research due to cost pressures;
  • the difficulty of scaling a niche offering.

Is Independent Research any different to Investment Bank research when a fund manager ignores the recommendation?

I am going to stick my head above the parapet and argue that no research analyst can make a correct call all of the time.  Back in the 60s, equities were so mispriced that a positive initiation report almost always guaranteed a bump in the stock price.  In the 90s ‘rock star’ analysts could move prices on their own but it turns out that the cheerleading nature of that time caught up with the analysts.  A smart individual, with a reputation built through their time on the sell side, can build a loyal client following.  Certain individuals can build rather lucrative careers, but there are limits.  These limits can be self-imposed – the value of insight can be perceived to decline the more it is shared – therefore some providers limit the number of clients.  Other limits can come from the nature of the insight provided – there may only be a limited demand for certain kinds of research.

What do fund managers want?

At the risk of sounding pithy, the answer to that question depends on the individual portfolio manager.  There are two major reasons why the vast bulk of research reports go unread.  The first is that the demand for a particular report is esoteric and fleeting in nature.  The second is the oversupply of reports in the marketplace.   The much-maligned quarterly earnings report may be read by some fund managers, those who have been away or are trying to come up to speed on a new stock.  But once a fund manager has read one or two (and the company’s earnings release) there is limited added utility in reading a third or fourth.  What the fund manager may miss is that the 15th one does carry a really useful insight, but it is lost in the noise.

Maybe there are fund managers and in-house analysts who have faith that an individual external analyst makes good recommendations on a consistent basis.  That analyst’s work and views will be in demand from that subset of readers.  Measuring analyst success is a huge business.   Alpha Capture systems, such as Marshall Wace’s TOPS system deliver strong returns, but the system is less about the success of an individual and more about the aggregate screening of the mass of data they obtain.  The system will not blindly follow individual recommendations but will work with the data identifying trends and factors.  Those buy side houses with access to data capture systems will use the data in a way that fits with their process.

Alpha capture can work really well for quantitative processes and has potential uses for fundamental processes looking at the timing of entry to a position.   But simply relying upon the past accuracy of stock recommendations of a single analyst to drive trading is not a solution that will be followed on the buy side.  A good level measurable alpha will be used as one indicator to identify quality in a crowded marketplace.  Alpha measures are limited, though and can emphasise analysts on a lucky run and work against analysts with high-quality work but bad luck or the inability to turn good analysis into a good recommendation.

I believe that the buy side is responsible for investment decisions and portfolio construction, and should be able to operate without a recommendation from an analyst.  If the research fits with the process of the individual portfolio manager, if the independent analyst acts as the eyes and ears of the decision maker then the recommendation becomes moot.  Recommendations are measurable, that is why the market is hooked on them.  It is much more difficult to measure the quality of input to a process.

The reality is that you can put a hundred fund managers or buy-side analysts in a line and it will be highly unlikely that any two would agree on the use of external research and recommendations.  Everyone has there own way of using external research.

This difference in opinion arises because funds have many degrees of freedom to meet their objective.  The fund process is the starting point, which may or may not include some initial quantitative screening.  There will be a buy decision, a portfolio construction decision, a risk process and a sell discipline – each of which can vary by fund.  Within the fund management structure, there may be in-house specialist analysts, there will be portfolio managers who may be portfolio manager/analysts or pure portfolio constructors.  There will be a variance in the amount of top down and bottom up work carried out.  There will be varying degrees of importance placed upon macroeconomic variables.  In each team, the way an individual works within the process structure will differ – in some cases it can differ greatly if a team values a differentiated approach.  Funds will hold a varying number of stocks, they will have red lines that they will not cross (no investment in Russia, etc.).  It is very clear that each individual buy-side PM or analyst will have a varying requirement from external research, that varies by topic, and approach an through time.

This variety has traditionally been met with ‘waterfront’ coverage by the sell side.  There is no way of predicting what a client base wants at any particular point in time, so the sell side provided an ‘all you can eat buffet’ of research.  This is grossly inefficient but was self-supporting given the bundling with trading commissions and support from the Capital Markets function.

In the eyes of the buyside, information loses its value the more it is shared.  It becomes difficult to grow a business if adding more subscribers dilutes the value of the information and analysis supplied.  This is different to a media model, where the utility is not diminished by more subscribers, in fact, network effects work to enhance the value if more people subscribe.  This scarcity value works for a small number of independent providers, but it is a difficult model for most to replicate.

An active fundamental portfolio manager shows his/her value by outperforming and attracting inflows.  This value is rewarded highly.  An independent research analyst shows his/her value by the client base they can attract and the amount they can charge that client base.

Conclusion

There are three main ways to grow a business in independent research.  The first is to come to the party with an existing following of clients.  The real added value in this business is from personal contact with the analyst.  The restriction of time then limits the ability to grow such a business.  Adding further analysts within an existing framework can grow the top line, but the cost base in most cases seems to grow equally as fast unless other services are offered (such as agency execution).   The Consulting Model.

The second way is to develop a retail following and then charge low value subscriptions to a lot of people.  To achieve this, the writings must be in an area with exceptional retail investor interest.  This model relies on the quality of the writing and the subject matter rather than access to the individual.  Bill Bishop and his Sinocism blog may be the closest example here, but others do exist.  The ‘tip sheet’ model.

The third way is to develop a data and chart heavy model run as a high-end publication.  Ned Davies and BCA are proponents of this.  The clear framework of using charts and data to drive the product supported by analysis.  The publishing model.

With the exception of the publishing model, I believe that these models are not currently well served.  Both the consulting model and the ‘tip sheet’ model offer significant room for future development in independent investment research.

This does mean that the number of highly paid individuals in the research industry will shrink.  The buy side is seeing fee pressure and the traditional fundamental equities business continues to struggle.  MIFID II should cut the implicit subsidy offered to investment bank research departments.  This is a huge reduction in the actual top line and the potential top line for the investment research industry.  If everyone engaged in this industry stays in this industry then the average remuneration must decline.  Now, more than ever, the independent research industry needs to provide a truly differentiated service just to survive.  Relying solely on the production of great investment ideas will not be enough to ensure survival.

The CFO in asset managers will now be the final arbiter of the monetary value of external investment research.  This value will naturally be compared to the cost of an internal analyst, as it is the most easily available comparator.  An in-house analyst will be looking for ideas that support the investment process and should sit more comfortably with the existing portfolio construction.  This is not necessarily the case within buy-side firms.  An analyst may support portfolio managers with very different processes.  There can be a lot of tension between portfolio managers and analysts within a firm.  It is much easier to veto expenditure on an external supplier than to remove an internal one, however.  It is also easier to present a convincing argument that hiring an internal analyst makes sense.

The buy side is slowly moving from ‘an all you can eat buffet’ (paid for by someone else) approach to external investment research, to an a la carte (own account) approach.  In this environment spending will decline, consumption will decline but quality will rise.  This shift will require fund managers to examine their own needs and desires in much greater detail or live with regret.  It will also require the providers of research to adjust their menus significantly and innovate.

There is a fourth way!  The use of technology to effect new solutions for the investment research industry.  The individual analyst will (mainly) be capped in the revenue they can generate by themselves.  The traditional growth approach of bolting on more cost is capped by its own weight and rarely leads to profitable margins.  The slew of online libraries or research supermarkets cannot encourage the collaboration that is required to grow.  A platform like Smartkarma offers the ability to move in a fresh and new direction.    It is early days, but true fintech is the future of investment research in my opinion.

 

Terminating Analysts: The Rise of the Machines

by Mark Artherton – Founder & CEO of LR Investment Services

Posted on Smartkarma as an independent insight on 3rd November 2017
Read more of Mark’s work by clicking here!

 

Nov 22
0

Confessions of a Shipping Analyst: Voyage of the Damned, Asian Equity Research Version

By | General | No Comments

 

Confessions of a Shipping Analyst: Voyage of the Damned, Asian Equity Research Version

by Daniel Hellberg

Independent insight posted to Smartkarma 22nd November 2017
Read more of Daniel’s work by clicking here!

 

At the risk of making Smartkarma (SMARTKARMA SP) seem like a New Orleans confessional the day after Mardi Gras, here’s another analyst ‘confession’ readers can file alongside Douglas Kim‘s excellent Confessions of an Independent Research Analyst (and interesting pieces in a similar, reflective vein from Hemindra Hazari and Nandini Vijayaraghavan, CFA, which you can find here and here).

Some (Fairly Ancient) History …

By way of introduction, I have now been posting here at Smartkarma for almost exactly 18 months, mostly writing about transportation, logistics, and tourism in Greater China and elsewhere in the region.

But I got my start in Asian equity research almost a quarter of a century ago in Taiwan. I had been working as an analyst at a corporate — a US-based container shipping company that was later acquired by Neptune Orient Lines Ltd (NOL SP) — but I had grown impatient with the slow pace of change at the company, and decided to head to Hong Kong (where a college roommate had offered a place to stay) to begin looking for…something.

About a month later I landed a job as the shipping analyst at a large brokerage firm in Taipei that was half-owned by the now-infamous Peregrine Securities (raise your hand if you remember Peregrine!). I admit I knew nothing about equity research at the time, but I did know something about how container shipping worked, and that was enough to endear me to a very small group of investors who actually cared about the sector.

When a similar position opened up at SG Warburg (another name from ancient history) a few blocks away, I quickly and happily moved on from my brief stint at Peregrine. I had grown tired of witnessing colleagues break down in tears on a weekly basis — not an exaggeration! — often due to the Managing Director’s, shall we say ‘volatile’ personality and management style. Even my inexperienced eyes could see that SG Warburg’s Taipei office ran like a fine Swiss watch by comparison — and this was before the actual arrival of SwissBank and, later, UBS Group AG (UBSG VX) on the scene.

At SG Warburg (later SBC Warburg, then SBC Warburg Dillon Read, then UBS Warburg Dillon Read, and finally just…UBS) I was asked to cover Taiwan’s listed shipping and airline companies — I believe there were eight at the time. But as an added bonus I was also asked to cover other local cyclical sectors, including steel, paper, and the local auto assembly companies. In other words, I was given the “opportunity” to cover the deeply un-sexy names none of the more senior analysts at the firm wanted to bother with!

After about four years in that position I transferred to the US with UBS to cover freight transportation on their US equity research team in New York. This mostly consisted of following larger names like Fedex Corp (FDX US), United Parcel Service Cl B (UPS US), and the US railroads. And then a few years after that, I went to work on the buy-side as a generalist industrials analyst for a series of US-based but Asia-focused Long / Short hedge funds.

And that pretty much brings us to 2015, when I began writing independent research on Asian equities, and trying (without much success) to market it to institutional investors in the US.

Regrets? I’ve Had a Few: Working as a Sell-Side Shipping Analyst

For the most part, I have very fond memories of my time as a sell-side analyst, particularly the years I spent in Taiwan with SG Warburg / UBS. Still, it wasn’t all fun and games, and certainly I share many of the complaints most sell-side analysts have: subtle pressure from Corporate Finance to maintain positive views on their clients’ shares; a cumbersome and time-consuming editing and publishing process; a rigid requirement that the analyst publish an exhaustive initiation note followed by regularly quarterly updates (usually to the detriment of more interesting idea-oriented pieces).

But in addition to these common complaints, there were other challenges I view as specific to covering cyclicals like shipping:

  1. For long stretches of time, many of the traditional cyclical stocks I covered would report depressed earnings or losses, and their market capitalization would in response often shrink to levels that pushed them off the radar screens of long-only institutional investors. In other words, although the stocks in these sectors certainly deserved at least a baseline level of attention from the analyst throughout the cycle, there were long periods where they really did not bear full-time coverage.
  2. Many of the companies within these traditional cyclical sectors — shipping and steel stand out — are truly global industries. But too often we as analysts covered them as ‘local companies’, and as such we were not encouraged to work with colleagues in other geographic markets who covered similar companies.
  3. Many of the traditional cyclicals I used to cover have been around for a century or more and the pace of change within these industries is often glacial. I remember taking up coverage of the four large US railroads in 1999 and thinking to myself, ‘is there anything new or interesting to say about these companies, some of which have been around since the US Civil War’?
  4. On joint marketing trips with colleagues who covered larger, more popular sectors (tech, financials) I usually ended up with the role of bag-carrier or hailer-of-taxicabs, sometimes given just a few seconds to present my ‘best ideas’ within my coverage. Not that I hold a grudge!

How Smartkarma Has Changed the Game for This Analyst

On the recommendation of an old SG Warburg friend who worked on the buy-side in Singapore, I got in touch with the folks at Smartkarma in Spring 2016 and I’ve been publishing my work there ever since.

Posting my work at Smartkarma addresses some of the mainstream complaints many former sell-side analysts have: there is no pressure from Corporate Finance to temper one’s views on a stock; the editing and publishing process is intuitive and streamlined; and analysts aren’t required to first publish a 60-page initiation note (and then regularly quarterly updates) before they express their views on a sector or an individual name.

But Smartkarma also addresses some of the frustrations specific to this analyst who was once ‘stuck’ covering traditional cyclical names like shipping and steel:

  • Analysts at Smartkarma can devote their time and resources to covering sectors, companies, and themes that are dynamic and topical and thus likely to generate investable ideas for readers, even if these are only tangentially related to their backgrounds. Analysts need not wait for the cyclical names under their coverage to turn (for better or worse) before publishing; they can instead focus on ideas outside their core coverage that are actionable, and thus worth analyzing, now.
  • Unbound by geographic restrictions on coverage, analysts here at Smartkarma can take the appropriate Global or Regional view of a sector.
  • Analysts from different geographical markets or different sectoral backgrounds can also freely collaborate to generate ideas here on Smartkarma, as noted by Douglas Kim in his piece.
  • In short, analysts (‘Insight Providers’ in Smartkarma parlance) who post their ideas here are free to break out of geographic or sectoral ‘silos’ and direct their time and energy to areas they feel are mostly likely to generate winning ideas. Ultimately, resources are directed to areas where they are mostly likely to generate optimal returns (both for Smartkarma’s Insight Providers and for subscribers). For those of us who used to focus on traditional cyclicals, this flexibility is extremely valuable. For those who cover growth sectors like technology, which is subject to constant change, this freedom may be less noticeable.

 

Confessions of a Shipping Analyst: Voyage of the Damned, Asian Equity Research Version

by Daniel Hellberg

Independent insight posted to Smartkarma 22nd November 2017
Read more of Daniel’s work by clicking here!

 

Nov 21
0

Institutionalised Quirks for Analysts to Ponder

By | General | No Comments

 

Institutionalised Quirks for Analysts to Ponder

by Nandini Vijayaraghavan, CFA – Finsights Research

Independent insight posted on Smartkarma 21st November 2017
Read more of Nandini’s work by clicking here!

 

Blessed are those who can laugh at themselves, for they shall never cease to be amused.

As an analyst, five analytical practices that are common place but need to be changed, in my view are:

  • Focussing on accounting profits as opposed to cash flows
  • Inconsistent treatment of on-balance sheet and off-balance sheet debt
  • Deducting readily marketable inventory from debt, thereby under-stating financial leverage
  • Focussing on share of net income rather than dividends from associates and
  • Companies maintaining investment portfolios that are opaque and which often generate lower returns than that of the core business and weighted average cost of capital

Read the unabridged insight for an analysis of and real-life examples of the above-mentioned issues.

Detail

The objective of a Smartkarma insight is usually to help investors make optimal decisions. But I thought I’ll use this platform to solicit responses from fellow analysts and astute investors to five issues that I have not been able to get my head around through my analytical career.

Issue #1: The Income Statement Fixation

One of the parameters of a company’s performance analysts are expected to opine about is a company’s profitability. Financial statements across the globe consist of the income statement, balance sheet and cash flow statement. The funny thing about income statement is that revenues represent sales income that is contractually due to a company but not necessarily collected as cash during the period of reporting, expenses that a company has contractually incurred to generate the revenues it has reported but has not necessarily paid, interest expenses payable on account of the existing businesses and not on account of the capital projects underway…The list goes on.

The income statement does have its utility in terms of “smoothing” a company’s performance, enabling a company to set aside funds for the replacement of plant and machinery that is subject to wear and tear due to the normal course of business aka depreciation, determining tax liability etc.

But what the income statement does not tell you is how much cash the business is generating. A much ignored gem and a more useful tool for analysts (in my view) is the cash flow statement. The list of companies that generate accounting profits (usually EBITDA and net income) but marginal to negative cash flow from operations (CFO) is endless. The financials of Singapore-based Olam International Ltd (OLAM SP) and Hong Kong-based Noble Group Ltd (NOBL SP) illustrate the disconnect between accounting profits and cash flows.

Figure 1

Issue #2: On and Off Balance Sheet Debt

Some companies opt to fund purchases of plant and machinery through debt, cash or a combination of the two. Other companies lease their assets. Several companies operate using a combination of owned and leased assets. The lease rentals are recorded as an expense. Why is there a tendency to estimate financial leverage using on balance sheet debt and ignore the off balance sheet debt i.e. the debt equivalent of leases. There is a wide spread misconception of Singapore Airlines being in a net cash position, as is evident in this article and this one.

As demonstrated in my insight “Singapore Airlines FY17 Results: The Myth of Net Cash”, Singapore Airlines Ltd (SIA SP) has been a moderately leveraged entity if the off balance sheet debt is included while computing financial leverage.

Issue #3: Readily Marketable Inventory

The businesses of companies whose business models integrate upstream and downstream operations and commodity traders tend to be working capital intensive. These companies may also hold high levels of readily marketable inventories (RMI). The companies in question and certain analysts argue that RMI, on account of its liquid nature, ought to be deducted from consolidated debt and hence, net financial leverage is lower.

This argument puzzles me. Are we evaluating companies as going concerns or in a liquidation scenario? As long as company is treated as a going concern,

  • The company requires those inventories to render its services,
  • Avails of inventory financing through banks, and
  • Pays interest on the consolidated debt, and not on consolidated debt less RMI.

Hence, is the high ratio of RMI to inventory a source of financial strength?

The spike in Noble Group’s CFO margin to 22% in Q3 2017 (Figure 1) from negative territory during six of the seven preceding quarters was driven by asset disposals including Noble Americas Corp that resulted in:

  • A working capital release of USD508.29 million driven by
  • An 86% decline in Q3 2017 revenues to USD1.47 billion over Q2 2017, and
  • Consolidated debt as of September 30, 2017 declining to USD3.59 billion, around USD1 billion lower than USD4.56 billion as of June 30, 2017

Asian commodity traders like Olam International and Noble Group and agri-business companies like Golden Agri Resources, Wilmar International and IOI Corporation seem to have a higher risk appetite than the global majors like Archer Daniels Midland Co (ADM US) and Bunge Ltd (BG US), who manage their working capital cycles efficiently. Hence, Archer Daniels Midland Co and Bunge Ltd  maintain moderate financial leverage, i.e. the ratio of lease adjusted debt to EBITDAR (the sum of EBITDA and operating lease rentals) despite earning wafer thin EBITDA margins.

The following insights demonstrate how leverage may be understated by deducting RMI from consolidated debt.

Issue # 4: The Emperor’s New Clothes aka Acquisitions

Expensive, debt-funded, and unremunerative acquisitions have contributed to the weakening, if not downfall, of several well-regarded corporates. If companies treated such acquisitions (which companies have an amazing knack of making, at the peak of the price / business cycle)  as associates, then the share of net income is reported in the income statement (once again…) and the dividends from associates in the cash flow statement.

While we analysts comment about the trend in the share of net income from associates and its impact on accounting profits, we seldom document the dividends these expensive acquisitions generate.

Issue #5: Opaque Investment Portfolios

Blue chip corporates and conglomerates including Genting Bhd (GENT MK) and Tata Group (1396Z IN)grow their financial investment portfolios over time. While the accounting policies of these companies comply with the requisite accounting standards, the disclosure regarding the composition and returns from these investment portfolios is inadequate. My guestimates indicate that the return from these investment portfolios may at times be lower than the CFO margin and weighted average cost of capital.

“Genting Berhad: GITP & Las Vegas Projects Offer Upside Potential To This Stable Stock” highlights this gaming focussed conglomerate’s loss making investment portfolio.

We analysts could sharpen our analysis in several other areas. Do highlight such issues by commenting on this insight. I’ll be happy to write a sequel to this insight analysing these topics.

 

Institutionalised Quirks for Analysts to Ponder

by Nandini Vijayaraghavan, CFA – Finsights Research

Independent insight posted on Smartkarma 21st November 2017
Read more of Nandini’s work by clicking here!

 

Nov 17
0

The Profits (And Perils) Of Independent Large Cap Research

By | General | No Comments

 

The Profits (And Perils) Of Independent Large Cap Research

by Hemindra Hazari

Independent insight published on Smartkarma 17th November 2017
Read more of Hemindra’s work by clicking here!

 

True, the field is crowded, and fresh insights are hard to come by. Still, contrary to Douglas Kim’s argument, it’s not mid-caps, but large-caps, that offer profitable subject matter for research. The advantage for the truly independent researcher is that, while the usual corporate doors are quickly shut, there are plenty of other doors no one thinks of opening.

For independent research to be recognized as a credible alternative to sell-side research, it has to play in the same field where the big girls and boys play, and in equities, it is large cap research. There is ample space for unusual perspectives and more importantly critical commentary for enterprising analysts to standout in the faceless herd and do the profession proud.

The proliferation of independent research analysts in the capital market as a result of cost pressures in the industry and introduction of Mifid II in Europe post January 1, 2018 has provided greater flexibility for analysts as well as more variety for institutional clients. As price discovery for independent research remains a work-in-progress, analysts are examining the most cost-effective, value-added service to provide to institutional clients.

In this respect, Douglas Kim has written an in-depth, insightful and well received article, ““Confessions of an Independent Analyst” on Smartkarma, documenting his experience as an independent research analyst and possible strategies analysts can adopt to prosper from 2018 onwards. One aspect of his comprehensive article is to suggest emphasizing mid and small size company research with a focus on generating “great investment ideas,” instead of venturing into the crowded large cap research, which is dominated by the bulge bracket firms. He does acknowledge the trade-off in research to write on “higher market cap stocks which may generate more interest vs. differentiated research in writing about “undiscovered” investment plays.”

Midcap research has a charm of its own. The competition amongst analysts is less, and the thrill of uncovering hidden gems is alluring. However, just as sectors have their day in the sun and can languish in the dark and go into hibernation, the volatility in midcaps can be far more severe and the winters long and hard. Typically, midcaps are a product of a bull market, rising rapidly with generous doses of liquidity. But come a bear phase, and liquidity in stocks dries up as institutional interest wanes.Exiting stocks may not be possible on account of high impact cost. In such a phase, dedicated midcap analysts are left high and dry, while large cap sector analysts can still survive on maintenance research.

Generating great investment ideas is the Holy Grail for analysts, but consistently recommending great investment ideas is extremely difficult for a single analyst, unless the market is bullish and all stocks are on fire. In the rare instance of an independent analyst consistently picking winners, he/she might well decide that, rather labouring and framing a logical argument to convince others, investing in those ideas makes better sense. Midcaps are also high risk, and their revenue can be volatile as they typically lack broad-based stability. Midcap analysts can earn a name recommending winners but lose credibility in any downturn.

No doubt, recommending winners is the ultimate objective for analysts. However, in the real world, to be recognized and appreciated as an analyst, it is more practical to consistently produce interesting, original insights on stocks, industries and the economy, defying the consensus when necessary. Framing a logical, well-researched angle is within the expertise of the analyst, but to achieve consistency in predicting winners and losers and the future direction of stock prices, which are influenced by a host of factors, is beyond the analyst’s control. Equity research analysts typically have their share of multi-baggers and stocks where their calls go horribly wrong, and that is par for the course. And while honest analysts make a genuine attempt to get their calls right, it is difficult to be consistent in getting calls right.

It is this writer’s contention that independent analysts, in recommending large cap stocks, should focus on providing unusual insights on the company, industry and the economy. Although large cap research is a highly competitive space, there is adequate room for providing critical research, an area which is largely and deliberately ignored by most analysts. Bloomberg’s Gadfly estimates that between “50 and 70% of a senior analyst’s time is spent on corporate access.” Unsurprisingly, then, not only does critical corporate analysis become a no-go area for most large cap analysts in bulge bracket firms, but also less time is devoted for thorough analysis. As a result, most large cap research has become an extension of corporate public relations in enhancing the image of the corporate. As Howard J Klein rightly points out in his erudite insight in the casino sector, sell-side analysts avoid asking about tough issues lest they injure ongoing relationships with corporate contacts they need to do their jobs. This is entirely understandable.  But the downside is that the process tends to produce far too many softball questions in order to maintain a general air of civility and nurse relationships.

The business media are no better than most sell-side research. In India, the business media are focused on getting exclusive interviews with large cap Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs). Anchors/editors hand over “Best CEO” and “Best Corporate” awards to large companies, and organise corporate round table conferences. And, of course, their business model is dependent on corporate advertising. As a result,  in India, at least, investigative business reporting on large companies is virtually non-existent in the corporatized business media.

This is fertile, virgin territory for independent researchers to showcase their expertise in providing critical analysis: on corporate strategy, exposing senior management incompetence, accounting transparency, and the likely chinks in the layered armour of large corporates. It is highly unlikely that institutional investors will approach independent analysts to fix meetings with large corporates, and hence the corporate contact loss to an independent analyst is far less. Large corporates may, in retaliation, boycott the critical independent analyst from their regular news flow; this is inconvenient, but an experienced analyst normally should have developed multiple sources in the companies and industry that he/she covers to compensate for the loss of official contact. Moreover, the mandatory disclosures and regular corporate analysts’ presentations provide adequate information on developments for independent analysts to be kept informed without having corporate access.  ICICI Bank Ltd (ICICIBC IN), India’s second largest private sector bank by assets has refused to interact with this writer for nearly two decades post the publication of a critical research note in January 1999, and Axis Bank Ltd (AXSB IN), India’s third large private bank by assets in June 2017, declined to entertain any further queries from this writer. The management boycott has not prevented this writer from regularly publishing (here and here) critical, non-consensus research on both these banks which has been appreciated by not only institutional investors but also by insiders in these banks.

In large cap research, institutional investors are not only looking for investment ideas but are also looking for unusual insights contributing to earnings’ drivers. And since considerable sell-side coverage is flattery disguised as research, there is a huge, unsatiated appetite for well documented, critical research. Unfortunately, over time, sell-side research has got used to being spoon-fed (instead of the rigours of data analysis and reading the fine print) by investor relations (IR) executives and CFOs of the companies they cover, and loss of official corporate contact cuts off any flow of information, as analysts did not develop alternative sources of information within these companies or from the industry.  In his over 20 years of experience, this writer, as a sector analyst and head of research had noticed a reluctance by analysts to develop contacts such as labour union leaders, corporate whistle-blowers, regulators and auditors – interacting with such individuals can provide an alternative to the image projected by industry chieftains. Such management-spoon-fed individuals have no future as independent analysts, as sell-side research will provide corporate access and regurgitate management commentary to institutional clients.

Financial Times All-World Index

Source: Financial Times

Equity analysts, in general, are more comfortable presenting bullish arguments and normally ‘Buy’ recommendations outnumber ‘Sell’ calls. Even during bearish phases, the analyst community remains optimistic and expects the phase to be short-lived – near term hiccups but long term growth story intact is the common message articulated.  On account of global liquidity and some recent mild economic revival, global equity indices have been on an upswing since early 2016. It is, therefore, no surprise that even on Smartkarma, a platform dedicated for independent research analysts, bullish views are in the majority, while bearish views remain in the minority and critical commentary on large companies and their management is rare.

Bullish & Bearish Views on Smartkarma

Source: Smartkarma

 

Analysts Coverage of  Large Banks By Market Capitalisation in India

Source: Bloomberg

In India, large cap research is competitive and most of the global bulge bracket firms are present. As the financial sector has a high weightage in the market index, banks are extensively covered. HDFC Bank Limited (HDFCB IN) with a market capitalization of US$ 71.8 bn. is tracked by 54 analysts with 91% maintaining a ‘Buy’ recommendation and commentary is naturally positive. Yet Daniel Tabbush, an Insight provider at Smartkarma, is cautioning investors on HDFC Bank’s rising impairment costs.  It is possible that HDFC Bank’s share price may continue to reward shareholders as it has done in the past, but Daniel Tabbush is taking on the consensus with a contrarian view supported by data. It is such outliers who get the attention of institutional investors and most importantly they will read and evaluate the merits of his argument.

Critical, independent, analytical research is not for the meek and there are pitfalls. There is no room for errors in critical research as the concerned corporate and investors will cross verify all the data points and analysts have to cross and double check the data prior to publishing. Corporates can boycott the critical analyst and deny her/him information and corporate access. Worse, vengeful companies can tie down analysts in lengthy, expensive law suits on charges of defamation and even use their extensive political contacts to make analysts experience the hospitality of the police – as happened in the case of fellow Smartkarma Insight provider, Nitin Mangal, for his critically acclaimed research on Indiabulls when he was with the independent research firm, Veritas.

For independent research to be recognized as a credible alternative to sell-side research, it has to play in the same field where the big girls and boys play, and in equities, it is large cap research. Midcap research is exotic, and can provide fabulous returns, but it is volatile and high-risk and in economic and market downturns, companies vaporise, as does the research. Independent research can and should do midcap research, but it should not be identified with midcap companies.  Mifid II has provided a gateway for those brave, seasoned and enterprising analysts to forge a path of independence in a market heavily compromised by large corporate vested interests. It should use this opportunity to take the competition head-on, raise the bar on large corporate analysis, and in doing so, make proud the tribe of independent analysts.
 

The Profits (And Perils) Of Independent Large Cap Research

by Hemindra Hazari

Independent insight published on Smartkarma 17th November 2017
Read more of Hemindra’s work by clicking here!

 

Nov 14
0

How Independent Research Can Add Depth to Valuations in High Visibility Sectors like Casinos

By | General | No Comments

 

How Independent Research Can Add Depth to Valuations in High Visibility Sectors like Casinos

by Howard J Klein

Independent insight posted on Smartkarma 14th November 2017
Read more of Howard’s work by clicking here!

 

  • Investors in this expanding sector are deluged with me-too analytics that can often inhibit, rather than illuminate the road to smart price discovery driven by under the radar management moves.
  • Casino stocks have their temperatures taken like flu patients every time news breaks whether it is a true catalyst or simply a vapid space filler for media outlets.
  • The nature of the symbiotic relationship between standard buy and sell-side analysts and managements unavoidably is built off a process that hasn’t changed in decades but is now being challenged by sources of independent research.

 

 

Douglas Kim’s recent insight on SK Confessions of an Independent Research Analyst astutely pointed out how the role of independent research as a value added source of opinion to investors is riding on what many of us believe is a growing tide of analytics. They’re coming from new algorithms developed by quants that at times appear to be something of witches brew difficult to tease out in real-world performance. And they’re also originating from technical analysis sources that attempt to bring deeper more measurably predictive analytics to weigh in on the final investment idea. At the same time, we see investors beginning to disrupt the process by sourcing ideas and valuations from independent researchers who in a sense, have no dog in any particular fight.

Over my own career, I have been asked many times by investors what other than the standard set of data points usually applied to company performances, are the key, under the radar realities that longer term, actually drive bottom lines and by extension,  casino share prices. I have developed what I call an “alternate reality” set of proprietary metrics and valuations entirely based on a view from the inside out. It’s the intellectual property of my consulting practice, but I am happy to share some its foundational principles with Sk readers. I think investors who are clients of wealth management divisions of banks, hedge funds should nudge their advisors to enhance their research beyond the standard data points that are the holy grails of the sector, to impart a keener insight to the company or idea that would normally be the case in a buy, sell or hold call.

While the casino industry shares many elements of related businesses, like lodging, entertainment, dining, and tourism, it has by any measure in my view, totally unique performance elements that can’t readily be judged by the same data sets applied to those sectors. What’s needed is a more nuanced understanding of what makes the business unique and by knowing that, bringing a depth and perspective to an investment idea in the space.

1.The casino business is probably more heavily regulated than most any other type of enterprise at a multiplicity of levels. Where governments feverishly compete for industries like manufacturing, energy, tech and retail with all kinds of tax concessions, waivers and infrastructure emoluments, they have historically needed to be nudged, or indeed pushed, by pro-legalization advocates to open the doors to casinos. Most recently we’ve seen how Japan, despite the relentless support of Prime Minister Abe and passage of the act, has resisted the process at every stage to the evolution of that nation’s Integrated Casino Resort industry.

The old fears persist: Problem gambling,  corruption, entry for criminal elements, game integrity,  money laundering run wild. These are not official or public objections that are ever likely to greet plans to build standard hotels, entertainment arenas, auto assembly plants, technology companies. After developers finally win over officialdom and elements of the public, they find themselves subject to high, sometimes punitive taxation percentages on gaming win, constant monitoring by massive regulatory bodies that track  and let’s be frank, police, daily business on the casino floor, in its accounting departments, room towers, restaurants and dining establishments. The operating assumption to be brutally frank: We have to watch these guys. Those regulatory bureaucracies, tend to grow exponentially, every time the complications common to all cash movement businesses surface.  Beijing’s junket crackdown crashed the Macau sector in 2015. It was perfectly understandable as part of a policy to curb political corruption and money laundering. And in its aftermath, stocks in the sector took a major hit. Yet, some analysts published recommendations built on doomsday scenarios. The facts as later developed, indicated that the action was clearly a baby with the bathwater situation. Offenders were indeed rooted out–by the handfuls. But VIP players stayed away by the bushel loads due to an immediate government induced paranoia. People who had nothing to hide, hid anyway or took off for the casinos of the Philippines. So the relationship between the scope of the actual problem and reality was distorted. This has subsequently been proven by the robust recovery of VIP business in Macau.  related type industries, life is much simpler. You either make, distribute, buy or sell a product or service to an end user period. In casinos, skepticism accompanies daily business. Regulators, both in new and mature gaming markets tend to assume policies that fundamentally say: Look Mr. Casino operator, you exist at our pleasure so watch your step or we’ll pull the plug faster than you can roll a pair of dice. That is quite a difference than the attitude toward other related type businesses that are subject to a fairly normal set of regulations as to safety, sanitation, employment rules, and environmental impacts. In casinos, you have all that PLUS the mountain of regulations covering the dealing and administration of games of chance.

Beside the junket crackdown in Macau, we had moves on smoking that hit the sector stocks, ATM withdrawals, ad nauseum and bureaucrat decisions on the number of tables allowed for a given casino. These were not made by managements  making business judgments, but by officials. And if you think officialdom in the SAD were singularly overbearing—consider this. In the early days of Atlantic City New Jersey, it required an on site inspection, and a lengthy approval process to move a sign from one zone of slots to another. As a senior level executive I was required to apply for and be cleared for, an A or Key License. The application was 130 pages long on two sides. I had to list every relative I knew up to and including second cousins including their names, addresses and phone numbers. The commission had all my bank information and by the way, escorted by enforcement officials, we were all required to go to any bank in which we maintained a vault lock box, open it and go through all the contents which were duly reported. My license, when issued, was the imprimatur of a person who easily could have walked in the next day to CIA headquarters and be immediately qualified as a field officer handling top secret information. None of this accompanies your average tech startup, movie theater, pizza parlor or two hundred room motel operator. What it tells us is that this is a business that is a creature of government more so than most others and when government sneezes, the industry, and its stock, can catch pneumonia.

So the lesson here is this: Government moves, sudden or planned are not all very good reasons to sell off a stock position in an otherwise strong performing casino operator unless of course, you see options play or are a day trader looking for a quick in and out on a sudden dip. But the government isn’t the only culprit per se, in the movement of casino shares. The other is the news cycle. This is a high visibility business. People are interested in happenings in a casino venue. The media know this and when anything happens, big or small, reporters call up analysts for comment. Most recently we’ve seen how tragedies in Las Vegas, Manila have hit gaming shares in the short term when analysts weighed in on the impacts. November’s early numbers in Macau indicate a robust 28% YoY increase during the first twelve days of this month. Yet, when asked to comment, several analysts also pointed out the start of the imminent Grand Prix event that “could dampen” Novembers strong start. Why? Because historically that has been the case. Whether that happens or not, its a slender reed for sure. This is a business where played delayed is usually mortgaged to the following month: It does not disappear.

To give some color on this issue I have studied the relationship between regulatory and force maejure elements in both Macau and Las Vegas.  Early this year., associates spooked by news asked my opinion on a group of gaming stocks.  “No knee shaking or knee jerking. Just stay long,” I said. I am no oracle. I merely based these picks on a broad lens view of how the industry tends to move over time and my understanding of the management dynamics that always play into results. Here are the results of my calls to date:

Wynn Resorts Ltd Wynn Resorts Ltd (WYNN US) up 22.5% and going higher IMHO.

Las Vegas Sands Las Vegas Sands Corp (LVS US) UP 22.5%

MGM MGM Resorts International (MGM US) up 3.8%

Monarch Casino Resorts Inc. Monarch Casino & Resort Inc (MCRI US) up 47%.

Note: Monarch is a US regional casino, relatively low cap, low visibility company with properties in Reno and Colorado only. Buried just below the surface of its usually strong performances in EBITDA over time was a pattern of management skills that in my view displayed themselves in strict fiscal discipline, excellent margins and a know-how employed in creating a customer mix–most critical of all, that added a valuation far above the market price. The alpha here lay in the longtime family management linked to a pattern that suggested the company was entering the next scale-up of its base which could be added to by development or acquisition.

As the year unfolded, it would appear support for the stock began to heavy up. And the single most valuable standard metric in valuing this sector is EV/EBITDA. This is a very Capex intensive business to the debt to equity ratios will always reveal more leverage than what many standard analysts may find comfortable. But Capex is the mother’s milk of the casino business. In the right hands, it produces great returns. Secondly, investors, I believe, always need to ask themselves this key question no matter what the standard metrics like P/E, PEG, 50 day moving averages, PTs–all part of a decision to be sure. But none them alone can answer this question: Do I want to be in business with these guys? Don’t think like someone buying a blip on a trading screen, think of yourself a buying into a business–mainly a management. And the extension of that is this: What does the EV/EBITDA ratio tell me about what this business is worth if someone showed up with a fistful of money and wanted to buy in. And think of yourself as a selling shareholder.

The Symbiotic relationship between standard buy and sell side analysis and independent research.

Over a long career, I have participated both as a corporate executive answering the questions of analysts gathered for earnings calls as well as a consultant on the asking end of the conference. As a result, I came to know many from major houses and found them to provide good guidance on fundamentals based on their inquiries. But at the same time, I limned a distinct proclivity in them to keep questions in the safety zone that avoided asking about tough issues lest they injure ongoing relationships with corporate contacts they need to do their jobs. This is entirely understandable.  But the downside is that the process tends to produce far too many softball questions in order to maintain a general air of civility and nurse relationships. Enter the estimable Chinese Wall of old financial institutions who made it almost a fetish to insist that there existed an unbreachable wall between the interests of their investment banking departments and their security analysis people.

There was, to an extent, a separation that presumably was enforced but facts are facts. It has never been lost on me that institutions that raised billions over time for large and small cap casino operators, generally got rave reviews from their analyst departments. Was security analysis a tacit marketing arm of investment banking? Is it now? Let’s leap closer in time to think this out. During the 2007/8 financial crisis, many of us learned that bond rating services now and again pegged their calls on tranches of mortgage bonds on rather exotic formulations of the bundles of gold-plated obligations, so-so ones and an uncomfortable bulge of downright garbage. And at the same time, the same rating services worked with issuers for fees becoming symbiotic partners if you will, in the total transaction. There are pitfalls that are avoidable and those to be perfectly frank, that are not. And that is where in my view, the role of independent analysis comes powerfully to the front as representing a source of investing ideas and recommendations to a large extent, not in thrall to the confirmation bias,  the proclivity that Doug’s insight alluded to. Its root can be in a corporate goal that finds its way into a data set and analysis of the numbers that reinforce those goals, ending up in a less than valuable piece of research for the investor. And that is where I believe, particularly in sectors with action elements that apply to no other businesses, independent analysis will continue to grow exponentially. It is not merely the disruptive technology of the delivery system, but the extent to which the work itself is free of institution biases and favor exchanges.

Next: In our next insight this month, we will look at how to value management performance outside of standard indices and metrics to bring out insights that lead to alphas not readily apparent in the casino space.

 

How Independent Research Can Add Depth to Valuations in High Visibility Sectors like Casinos

by Howard J Klein

Independent insight posted on Smartkarma 14th November 2017
Read more of Howard’s work by clicking here!

 

Nov 10
0

Confessions of an Independent Research Analyst

By | General | No Comments

 

Confessions of an Independent Analyst

by Douglas Kim

Independent insight published on Smartkarma 10th November 2017
Read more of Douglas’ work by clicking here!

This is a follow-up to my report Independent Research in Asia 2.0. I borrowed the title from a memorable book called Confessions of an Economic Hit Man written by John Perkins. The purpose of this report is to provide a more detailed account of my personal experience as an independent research analyst in the past couple of years as well as the growth of the independent research platforms such as Smartkarma.

I hope to present an honest view of my experience and discuss both the rewards and the challenges of an independent research analyst and third-party research platforms. Many insight providers are likely to have similar struggles and may have asked the same questions that are highlighted in this report.

The global research in a post-Mifid II environment is likely to change dramatically. The clients that read this report may also get an improved understanding of how to better utilize independent research analysts and recognize their limitations as well. In particular, I discuss the following three major issues in detail:

  • The Beginning & The Network Effect
  • Warren Buffett’s “Knowing Your Circle of Competence” & Key Challenges of Coverage
  • What is Most Important?

The Beginning & The Network Effect

More than two years ago, I decided to give it a try as an independent equity research analyst. The job market was tough and with nearly two decades of experience as an equity research analyst, I thought there could be an interesting opportunity as an independent research analyst.  After Googling “Asia” and “Independent equity research analyst”, I came across a company with a catchy name called Smartkarma, which provided a third party platform for independent research analysts like myself. After a review process and a chat with Jon Foster, I was allowed to contribute on this platform. My first report on the Smartkarma was about a Korean dairy & baby formula company called Maeil Dairy Industry (005990 KS).  Biggest Beneficiary in Korea from China’s Two Children Per Family Policy? I think I spent about 3 weeks on this one report (nearly 40 pages). The initial response was disappointing, with the report getting a relatively low response from the Smartkarma community and its clients.

Nearly two years have passed since then and a few days ago, Smartkarma announced a major breakthrough investment by Sequoia Capital, which I believe is a home run for the company. What did Sequoia Capital see in Smartkarma? Sequoia has funded monster companies such as Apple, Google, Oracle, PayPal, YouTube, Instagram, Yahoo!, and WhatsApp in the past. Sequoia’s investment in Smarkarma is a HUGE thumbs up for independent research in a post-Mifid II environment. Smartkarma’s ability to capitalize on the network effect was probably one of the integral reasons as to why Sequoia Capital invested in this company.

The network effect is simply defined as a phenomenon where a good or service becomes more valuable as more people use it. 

Companies such as Google, Instagram, and WhatsApp are prime examples of this network effect. They have built enormous moats capitalizing on this network effect which is difficult to break into by its smaller competitors.

In the global independent research platforms, SeekingAlpha is probably the most well known. However, there have been a lot of questions regarding the overall quality of their contents as well as their content providers, especially from the institutional investors’ points of view. Despite these concerns, SeekingAlpha has built a strong brand name and many investors like to view this website for generating investment ideas. As Smartkarma expands in the US market as well, a key challenge will be trying to compete against established players such as SeekingAlpha.

About a decade ago, I was doing some Korean investments related consulting work for a multi-billion dollar hedge fund called Luxor Capital based in NYC. Here, I was introduced to a website called Value Investors Club, which is widely used in the hedge fund/buy-side community for generating ideas. Unlike SeekingAlpha, the contributors at Value Investors Club are anonymous, which has its pros and cons. Overall, the research generated in Value Investors Club tends to be more on an “institutional” level compared to the ones on SeekingAlpha. Established by a well-known hedge fund manager, Joel Greenblatt, the Value Investors Club’s purpose is not to make money for the website itself, but more for its users (mainly institutional buy-side firms) to generate ideas that are not normally available in regular sell-side research. The Value Investors Club is another example of a website that has benefited from the network effect. 

Right now, Smartkarma has a distinct lead in the Asian independent research platform with regards to the network effect (including the overall number of independent research providers). However, as it continues to expand in Europe and North American markets, it will face tough competitive pressures. Nonetheless, Sequoia Capital’s investment in Smartkarma provides a major vote of confidence and capital for the company to continue to successfully break into new markets globally.

Warren Buffett’s “Knowing Your Circle of Competence” & Key Challenges of Coverage

One of Warren Buffett’s favourite maxims is “knowing your circle of competence” and this has direct relevance to independent research analysts as well. Warren Buffett is famous for investing in companies that he understands. He has made investments in companies that he understands very well such as Coca-Cola and American Express. As an independent research analyst, you are “unshackled” to provide research on essentially any company in the world, unlike the traditional sell-side research analyst who typically has “core” coverage in 12-20 companies.

But who came up with the “industry rule” that the traditional sell-side research analyst needs to cover 12-20 companies and is this optimal? The equity research industry has its roots in the developed US/European markets. The need to maintain quarterly earnings updates is one of the key reasons why a typical senior equity research analyst has 12-20 companies under coverage. Think about it. Many of these companies have quarterly announcements in a similar time frame. Plus, there is a time limit as to how well an analyst can update an excel model and write about a company during the earnings seasons. The counter-party buy-side analyst (who works for a portfolio manager) typically has about 50-70 companies under “core” coverage.

Breadth vs. Focus Coverage – One of the goals of the traditional sell-side analysts is to dominate a few, core coverage stocks. For example, a few years back when I was a sell-side analyst covering renewable energy sector in Korea, one of the core stocks under my coverage was Oci Co Ltd (010060 KS), a leading producer of polysilicon. It was my job to better understand this company, write more research, and call more clients on this name than any other analyst on the Street. The salesforce always kept a record of how much trading was done on this name (and all other companies under my coverage) on a monthly basis.

This business structure is similar for the other sell-side analysts that cover stocks like Apple, Samsung Electronics, or Alibaba. Plus, there were long overseas marketing trips throughout the year. It is fair to say that about one-third of my time was spent on marketing/speaking with clients and the other two-thirds on writing research reports, updating models, and thinking about the changing industry dynamics. The amount of marketing versus writing reports may differ for each sell-side analyst but most of the sell-side analysts typically spend an awful lot of time on marketing and speaking with clients.

One of the benefits of the traditional sell-side analyst model is the fact that the biggest long-only funds sometimes have active engagement with the sell-side analysts for the stocks that they are interested in with regards to discussing key earnings estimates assumptions, for example. Analysts with solid track record of consistently forecasting earnings with logical assumptions tend to receive higher points from major long-only investors.

On the other hand, this advantage of being able to “dominate” a few stocks could work against the analyst, especially during a major downcycle in a particular industry. In addition, the extreme focus on a particular industry could also mean that this sell-side analyst maybe less aware of how the entire stock market, as well as other companies in different industries, are faring. This is where experienced strategist,  salesperson, and equity traders can really help to bring incremental value to the buy-side clients.

Given this background, one of the major dilemmas for the independent research analysts is to pick the companies and industries that they want to cover and this goes back to Warren Buffett’s emphasis on “circle of competence.” 

In the stock market, there are so many sectors to cover. But it is almost impossible to understand in depth so many different industries at the same time. Plus, many analysts may not have had previous exposure to certain industries. For example, Warren Buffett tends not to invest in biotech stocks. This does not mean there aren’t great biotech investments out there. In Korea, biotech stocks have been on a tear and they have been some of the best investments in the past several months.

With nearly two years of experience in independent research, I had to do some “soul searching” in terms of additional coverage. For example, there have been several interesting IPOs in Korea related to the biotech sector in 2017. After much thought, I decided against writing about them, despite the temptation to do so, mainly because writing research about Korean biotech stocks would mean losing some focus on my existing coverage.

In addition, the top three stocks including Samsung Electronics Co Ltd (005930 KS), SK Hynix Inc (000660 KS), and Hyundai Motor Co (005380 KS) represent nearly one-third of the entire Korean Stock Market in terms of market cap and they are well covered by existing sell-side analysts. As a result, I have concluded that it is very difficult for me to provide any differentiated view on these names and I have not written about these companies in-depth. Overall, I have tried to keep my coverage “limited” to IPOs, M&As, spin-offs, as well as on existing listed stocks related to the Korean consumer, telecom/Internet/games, industrial, rechargeable batteries, and special situations.

Challenges of Market Cap – There are many diverse investors with different needs for research on large vs. small/medium sized companies. Post-Mifid II, the low-tiered investment banks are likely to face extreme competitive pressure from the bulge bracket firms and independent research providers. As these low-tiered investment banks further downsize their research operations, their ability to cover mid-small caps will be further hampered and in this space, the independent research firms and research platforms such as Smartkarma have a chance to flourish.

In the past couple of years, I have found that clients typically show greater interests in IPOs of companies with market cap of more than US$300 to US$500 million. Personally, I have found that there are many interesting IPOs in Korea less than this market cap range but have tried to put a floor limit on trying to write research on companies with at least US$100 million in market cap.

Typically, writing about the biggest companies in the world such as Alibaba, Apple, and Tencent tend to generate more interest than companies with less than US$300 million in market cap but again there is a trade-off in being able to differentiate one’s research for companies that are not well covered. The insight providers at Smartkarma are consistently posed with this trade-off in research (higher market cap stocks which may generate more interest vs. differentiated research in writing about “undiscovered” investment plays). 

Challenges of Country vs. Sector Coverage – There are great benefits to having a sector coverage (for example in banking or telecom/Internet) for numerous companies across multiple countries in Asia. Numerous independent research providers have adopted this approach. However, one of the difficulties of taking this approach is that it may require additional capital (for example, hiring additional help for different languages).

For example, Japan and Korea are two vastly different markets and require specific language skills to cover companies adequately. For many independent research analysts in Asia, it may be easier to cover companies on a country-specific basis, given the capital constraints of many smaller independent research firms. As a result, the traditional sell-side approach to covering many companies on a sector basis may provide some competitive advantage for now.

Cooperation among insight providers – This is one area where there is potentially a super potential for independent research platforms such as Smartkarma. There are so many opportunities to interact with various insight providers and try to create innovative joint research products.

For example, one of hottest markets in the world right now is Vietnam. Plus, Korea is one of the biggest foreign direct investors in Vietnam. Given the strong investors’ interests in Vietnam coupled with the fact that Vietnam possesses many of the attributes that South Korea had about 30 years ago, I thought that a joint “Vietnam-South Korea” research report would be a good idea and contacted Vietnam & Frontier Markets specialist Dylan Waller to write joint reports involving Vietnam and South Korea, which were well-received.

I also noticed a research product produced by Angus Mackintosh called The Week That Was in Asean@Smartkarma. I thought to myself, “Why not replicate such a product for the North Asian market involving Japan and South Korea?” So I contacted Travis Lundy, Mio Kato, CFA, and Sanghyun Park to see if we could create a similar product and we all agreed that it was a good idea so we started a weekly for the North Asian market a few months back. After a while, I noticed that there was a regular weekly called The Week that Was in Greater China@Smartkarma written on a rotating basis among  Scott Laprise/ 乐天虎, Valerie Law, CFA, Ke Yan, CFA, FRM, and Daniel Hellberg.

In early 2017, I also started to read reports on the Smartkarma platform written by  Howard J Klein who is an industry veteran in the gaming industry. In writing my reports about the Korean gaming industry, Howard provided valuable inputs that helped to improve the overall quality of the reports.

In addition, I have noticed that two insight providers including Angus Mackintosh and Nicolas Van Broekhoven actually have joined forces to create a firm called CrossAsean Research a few months back, capitalizing on their experience in covering the Southeast Asian stocks.

These examples are just tip of the iceberg. As Smartkarma continues to expand globally and increases its network effect, there are likely to be many ways that the insight providers could share ideas and expertise to create joint reports that add real value to the buy-side clients.

Knowing Your Strengths and Weaknesses – At the core of Warren Buffett’s “circle of competence” also includes knowing your strengths and weaknesses in terms of skill sets. For research analysts, there are several important skill sets/experiences that are required which include 1) analyzing a given industry/company (including building models & making recommendations), 2) writing in a logical, clear manner, 3) communicating verbally/marketing, and 4) years of experience covering a specific industry/playing a key role in taking a company in overseas roadshows/company visits.

Personally, I believe I have an “above-average” skills in analyzing a company, making recommendations, and writing in a clear, logical manner. However, I am “mediocre” in verbal skills and making presentations. Being in this industry for many years, I have seen some other analysts making wonderful presentations to clients that were quite “awesome.” 

For independent research analysts with these “awesome” verbal communication and presentation skills, this actually poses a major dilemma. Working as independent research analysts may mean that they may have a lot fewer direct face-to-face meetings with buy-side clients initially as compared to when they were at traditional sell-side firms. As a result, they may be disheartened a bit since they may not be maximizing their strongest skill sets. In the long-run, as the demand for independent research increases, there will be greater opportunities for one-on-one meetings with clients. However, for now, the demand for one-on-one meetings with independent research analysts is relatively low compared to the traditional sell-side firms.

Knowing Your Client and Who Reads Your Research – For nearly two decades, I did not really know who read my research, until Smartkarma! When I was working in the sell-side, I wrote research which was distributed to the buy-side clients in a PDF format. This has been the industry standard for nearly 20 years since the adoption of the Internet and email. The sales team would occasionally tell me that a few clients liked/disagreed with my reports. There were very low visibility in terms of who actually read my reports. Having also worked in the buy-side, there is simply not enough time in a day to read all the reports. I believe I took a look at perhaps 5-10% of the reports coming in my email, and this is probably on the high side for the majority of the buy-side! According to a recent Reuters article, it notes that less than 1% of all research produced by the top 15 global investment banks are read by investors. http://www.reuters.com/article/us-markets-research/online-competitors-take-on-global-banks-in-securities-research-shake-up-idUSKBN16Z0L5

Smartkarma’s functionality of allowing the insight providers to know what clients clicked on one’s report will likely be the industry standard in the coming years. In the past couple of years, I have noticed the clients that regularly click on my notes but also the ones that no longer read my reports!

What is Most Important?

Having worked many years on the sell-side as well as an independent research analyst in the past two years, I realize that there are clear differences in the NUMBER ONE PRIORITY as a research analyst on these two different platforms. As a sell-side research analyst, the number one most important thing was quite clear – which was to get ranked by the biggest global buy-side firms including Capital, Blackrock, Allianz, JP Morgan, and Fidelity. The amount of bonus (or lack of bonus) was largely determined by whether you can get ranked by these Tier-1 firms.

However, my priority as an independent research analyst has changed. My number one priority as an independent research analyst is to generate great investment ideas. There is no longer any pressure to get ranked by these Tier-1 firms. However, there is a different kind of pressure, which is to think and write about great investment ideas. 

In addition to the rankings by the Tier-1 buy-side firms, the annual Institutional Investors (II) polls, have been highly important to the sell-side analysts. In the post-Mifid II environment, it remains to be seen how much importance II polls will continue to be. As the major investment banks adopt research platforms that are less PDF dependent but with a greater transparency of which clients are reading what reports (similar to the Smartkarma system), this should improve the ability to have a more data-based system to better understand what reports the clients are reading. As a result, the “beauty contest” based II polls are likely to be de-emphasized and data analytics based system will increasingly be preferred in determining the “value” of investment research produced by both independent and traditional sell-side research analysts in the coming years.

 

Confessions of an Independent Analyst

by Douglas Kim

Independent insight published on Smartkarma 10th November 2017
Read more of Douglas’ work by clicking here!

 

Nov 03
0

Terminating Analysts: The Rise of the Machines

By | General | No Comments

 

Terminating Analysts: The Rise of the Machines

by Mark Artherton – Founder & CEO of LR Investment Services

Posted on Smartkarma as an independent insight on 3rd November 2017
Read more of Mark’s work by clicking here!

 

Independent Research was meant to be the future, MIFID II, scaling problems and tech trends may mean that it is the past.

“I need your clothes, your boots and your calculator”

With apologies to Terminator 2, 1991

There are many, many smart people trying to forge their own path in Independent Investment Research.  For the right individual, it will always be possible to forge a lucrative career, as it is possible in journalism or book writing.  As the institutional research pie shrinks the Investment Banks (IB) will fight tooth and nail with their exceptional resources to retain market share.  If research can generate significant profits, then the IBs will be there.  How that translates into individual pay is a different matter.

Many professional service industries are seeing the impact of AI, Machine learning, big data, etc. on their entry-level positions.  The audit industry, consultants, investment banking and many others are implementing technology for ‘grunt’ level tasks.   The asset management industry and the independent investment research industry will be no different.

I will touch upon two tech trends that are disrupting investment research, the first is robot writers and the second is robot primary research.  There are many other technology disruptors in this space, but these are the most important in our opinion.

Robot Writers – they are here already

The world of journalism is already populated by Robots writing copy.  Examples are The Washington Post’s use of Heliograf, and USA Today and Associated Press’ use of Wordsmith.  Heliograf is described in a recent Wired article;

Editors create narrative templates for the stories, including key phrases that account for a variety of potential outcomes (from “Republicans retained control of the House” to “Democrats regained control of the House”), and then they hook Heliograf up to any source of structured data—in the case of the election, the data clearinghouse VoteSmart.org. The Heliograf software identifies the relevant data, matches it with the corresponding phrases in the template, merges them, and then publishes different versions across different platforms. The system can also alert reporters via Slack of any anomalies it finds in the data—for instance, wider margins than predicted—so they can investigate. “It’s just one more way to get a tip”

The purpose of Heliograf is primarily to target many different small audiences with many stories that are niche or local to grow the overall audience.   The second purpose is to improve newsroom efficiency.  Only large organisations can effectively lever technology to achieve this.  The journalism industry is full of freelance writers but their focus has shifted to counter the rise of the bots.  The Washington Post is not going to talk up the demise of traditional journalism, and the technology definitely aids those journalists with huge experience.  However, it does create a block for junior reporters, those individuals who historically did most of the grunt work in an organisation.  As the technology progresses it will impinge more and more on other journalistic activities.  Hopefully, this will lead to a come back for investigative journalism, for example, as the technology led journalism cross subsidises quality journalism.  Unfortunately, this may not be the case as the profit imperative will take the lead.

Writing a small piece on local elections or paraphrasing an earnings release is quite different to a robot writing a full in-depth report on a stock investment, but so-called ‘maintenance’ research can be automated relatively easily given the current state of technology.  Junior analysts are in the firing line.  This research is lowly valued but required.  Time-constrained portfolio managers will always need briefings, they may give limited value to them but it does work to retain an audience.  Automated report writing based upon conference calls, quarterly releases, and quarterly presentations are not that far away – a business doing this on a global level could carve an attractive niche.

Robot Researchers

The large Investment Banks are already experimenting with Robot writers to help reduce costs.  More importantly, they are investing in systems such as Kensho, which provides traders with forecasts based upon its huge database (Kensho is used extensively by Goldman Sachs, for example – see below).  As a standalone Independent Research Analyst, this should cause huge concern.  MIFID II will push the IBs to implement research technology at an even more rapid pace, and their balance sheets and resources give them a huge edge.

Kensho – A step towards the future

Kensho is disrupting the data market and appears to work in a similar fashion to Wolfram Alpha.  This is a direct attack on junior analysts and platforms such as Bloomberg, in my opinion.  In fact, it is feasible to build a Bloomberg Killer today with existing technology platforms – though Bloomberg’s existing network effects and path dependency will delay its demise.

Kensho works as follows:

Questions (asked in plain English) can be typed into a simple, Google-style text box. Stuff like: Which cement stocks go up the most when a Category 3 hurricane hits Florida? (The biggest winner? Texas Industries.) Same with which Apple supplier’s share price goes up the most when the company releases a new iPad? (OmniVision, which makes the sensors in the iPad camera.) Until now, answering these types of questions required several analysts and several days. Kensho can do it in a matter of minutes.

Kensho was dreamt up outside of the IBs but the IBs were quick to recognise its use and invest.  Initially, investing for traders, the shift into investment in research capabilities will give the IBs a tremendous edge.

Companies on the Smartkarma platform are already addressing some of these issues.  Amareos, for example, analyses a huge amount of news articles to generate sentiment and other factors giving insight into asset behaviour.  Despite some advances, I believe we are still scratching the surface in the application of technology to investment research and active investment management.  Current solutions are not holistic and many fail to account for different consumption patterns in their clients.  Retail investors may be hunting for the killer new process that they can follow blindly and make a fortune, professional investors are different, taking a much more evolutionary approach to changes in their process.  Institutional Investors have fixed processes, and inputs need to be tailored to those processes.  The technology of research delivery is lacking in this space.

The industry will continue to support human research analysts, though.  There will always be space for synthesis ( I keep coming back to this concept).  A combination of tech tools, internal workflow management and an in-depth understanding of client needs still needs synthesis.  It is synthesis that computers will find difficult to replicate.  Synthesis is the fallback position for human researchers and active investment management.

Additionally, systems may not be suited to the identifiaction of so-called ‘Black Swans’, the human mindset does throw up the occassional analyst who sheds a completely new light on a problem – Taleb, for example.  As such, the role for left field thinking is likely to be occupied by Human Researchers.

The ability to service the career buy-side analyst who is looking to refine their model of warranty expenses at Samsung Electronics (5% of admin expenses), through the thematic manager who is interested in the possible future demand for 3D NAND flash, including the corporate fixed-income manager interested in the impact of future dividend policy on debt ratings, up to the global asset allocator interested in Samsung’s impact on the MSCI index performance and many others along the way is the future of investment research.

Celebrity may also have its place, the consumers of research will always read celebrity writers, though (maybe similar to the movie industry) the draw of the star analyst may be on the wane as interconnectedness reduces the luster of celebrity.  Extending this further, while lower-end interaction can be handled by chatbots already, higher-end interaction will still require the human touch.

Conclusions

A combination of Kensho and Heliograph is a stealth killer for the bulk of the analyst community.  The much-maligned Investment Banks have a clear edge in the area of technology and already have the client relationships.  MIFID II has pushed the IBs to innovate more quickly, and I fear that Independent Research is an endangered species unless we react as a community.   We need to get ahead of this wave with more collaboration.

Don’t get me wrong, the current state of AI means that we are decades away from true AI, where a human can be replaced in all ways by a machine.  However, entry-level roles will cease to exist as technology does the ‘grunt’ work much more efficiently.  The absence of entry-level positions will create huge problems in the future, but we are yet to see a drop off in entry-level hiring in a meaningful way.  The other area that the machines will fundamentally change is the delivery and consumption of research.  A revolution is underway, if you have got experience chose your path carefully.

 

Terminating Analysts: The Rise of the Machines

by Mark Artherton – Founder & CEO of LR Investment Services

Posted on Smartkarma as an independent insight on 3rd November 2017
Read more of Mark’s work by clicking here!

 

Nov 01
0

Monetization Models for Digital Content

By | General | No Comments

 

Monetization Models for Digital Content

by Valerie Law, CFA

Independent insight posted on Smartkarma 1st November 2017
Read more of Valerie’s work by clicking here!

 

Ever since the rise of the online media industry and increasing pace of content digitization, traditional content creators, owners, and distributors have faced disruptions and declining revenues. Now, they are finding ways to monetize the content that they own or distribute. In this article, we explore seven pricing models that currently exist, but are still evolving. Some businesses could be using a combination of two or more monetization models.

1. Free with ads and/or exchange of data

Many major newspapers have adopted this model as readers moved to online reading, and get ‘accustomed’ to social media interfaces and ‘tailored-for-you’ newsfeeds. Advertisements are either embedded in the middle of the article, within a ‘pop-up box’ or ‘played’ before an article loads. Chatbots are embedded on certain Facebook pages to help with ad conversions.

For commercial websites targeting specific groups of users (eg. property portal), users get free access in exchange for their personal information. Such platforms depend on advertising from property agents/ agencies or other forms of deals with partners.

On video sharing platforms such as Youtube, famous musicians, artists, or vloggers thrive on their followership numbers so they can influence (or directly advertise to) their fans. Although content creators could earn some money by putting their creations on the platform, the big money comes in the form of corporate sponsorships or sales of other accompanying products.

To view the creators’ works, viewers may have to wait for that compulsory 10 to 30-second ads to pass, as in the case of certain free news sites. However, adblockers may be downloaded by viewers, thereby limiting advertisers’ reach (and hence monetization potential).  This may be the reason why Youtube is starting to experiment with the subscription model, which leads to our next discussion.

2. Subscription

For this model, we are referring to those businesses that focus on differentiating free-usage versus premium customers. (The multi-tiered subscription model is discussed in the next point.) Newspapers such as the Wall Street Journal and Financial Times use this model. They allow reading of the initial paragraphs by the general public, but the rest of the content is behind a paywall. SmartKarma is on this model too but could add or evolve into other models later.

For video sharing platform Youtube, it has launched YouTube Red, a premium version featuring original content from Youtube’s biggest stars with no ads at all. In the US, it costs $10 per month, but there are no updates as to when this will be available in Asia.

Music streaming services such as Spotify use this model too. The regular subscription is often free or low-priced, but it has such a huge reach. If the subscriber base is too low, operating costs have to be covered through other means. Seeking Alpha, the US-based Investment Research Platform has a wide subscription base that provides early/ exclusive access to PRO subscribers.

3. Multi-tiered Subscription or Bundles

Here, owners or platforms of digital content offer tiered access based on formats, timeliness of access, the frequency of access, or duration of access. Wiley, a well-known publisher, has an online library of articles where one can purchase instant access via a few formats: Rent, Cloud Access, or PDF.

Source: A Page from Wiley’s Online Library

An extension of this model could be the pay-per-use model coupled with a low-priced subscription. This allows the platform to have a wide user base, which the businesses then dangle premium content for additional revenues. One example is Starhub TV, which used to practice compulsory subscription to their basic-tier content before allowing viewers to access premium channels (eg. EPL). However, the rise of online content platforms and changing customer behaviours have led the telco to scrap this model recently (Source: Straits Times).

Source: Straits Times

For brokers or banks providing investment research, a multi-tier subscription is less obvious, due to the bundling of commissions and other fees. However, clients are often internally ‘tiered’ by the sales or account managers based on the clients’ trading commissions or willingness to cut out a separate budget for research. The different tiers that clients are ‘grouped’ under will determine the amount of access to corporates, analysts, or their models.

4. Pay-per-use 

This is used commonly by PayTV and the music industry. Use of music for certain events means payment of royalties to artist and recording label. Historically, this had been difficult to implement due to distribution costs or payment processing fees.

In the field of journalism, a new development is evolving to stem the decline in subscription revenues – Blendle has a good headstart which allows consumers to pay per use at around 20 cents per article. They even have a money back guarantee:

Source: Launch.blendle.com

5. Licensing for adaptation into other formats

One way to extend the monetary value of written digital work is to sell them for adaptation into other formats. One case study is China Literature Ltd (772 HK), a platform that aggregates literary works across China and collects subscriptions from readers. The real upside for writers and the platform comes from licensing popular content to film and/or game producers.  The challenge for film and game producers lies in choosing the next blockbuster to adapt.

Not every good book leads to a good film reviews, or sufficient box office sales:
Source: FiveThirtyEight, and HollywoodReporter.com

 

Some publishers may extend services such IP management contracts and/or monetize content for e-learning. The publisher O’Reilly is one such example.

6. Content whose value is tied directly to a percentage of sales (or monetization)

Platforms provide authors and creators to display their works for free. If users like what they see (usually sorted by portfolio or ratings), they can engage the creators. The platform then makes a fee or takes a cut from every transaction. Service aggregator platforms such as Fiverr and Upwork fit into this model. They sign up artists, professionals, and writers and let them display their profiles, portfolios, services, and rates. Once the creators get orders for their services (whether by the gig or by the hour), the platform charges a processing or transaction fee. Fiverr adds a processing fee for every transaction while Upwork charges a percentage of the project fee, hourly fee, or contest fee.

The author or creator can also request additional payments for every round of revision beyond the standard 1 number of revisions (within a time frame), again creating monetization opportunities for the platforms. Such platforms must utilize promotions to drive end-user demand and create supporting features to retain the professionals on their platform.

7. Content whose value is tied directly to certain desired outcomes

Specific information can be packaged to help people achieve certain desired outcomes, allowing such information to be priced higher than others. As fellow insight provider Mark Artherton explained in his piece The Future of Investment Research , mere information on its own has little value. However, the synthesis of information and distribution to the right audience can create real value.

Hence, if the information leads to an advantage or time savings in some field, the writer/creator may get a cut of the performance outcome desired by the end user. One such business close to this model is research platform Tip Ranks, which ranks analysts/writers by the overall performance of his/her calls. In this case, the desired outcome by end users is good trading/investment returns.

Another business using this model are online course providers. CFA course provider Fitch is an example. They provide free re-use of its online course materials if the students fail their exams (under certain conditions).

Conclusions

The pricing models mentioned above may not be comprehensive but serve as a discussion point for owners and/or distributors of digital content. Other monetization models also exist but are not discussed in depth. Examples include platform Eri-c which uses auctions to price research, and IBIS World (a kind of aggregator for different industry reports offering tiered subscriptions), which fellow Smartkarma insight provider Mark Artherton kindly pointed out to me.

While monetization models will evolve over time, we both agree that research providers like ourselves must think hard about how best to organize and monetize the ‘synthesis’ part of the information value chain. Below, I summarise some of the pros and cons of each model for further reflection.

 

Monetization Models for Digital Content

by Valerie Law, CFA

Independent insight posted on Smartkarma 1st November 2017
Read more of Valerie’s work by clicking here!

 

Oct 25
0

Independent Research in Asia 2.0

By | General | No Comments

 

Independent Research in Asia 2.0

by Douglas Kim

Published on Smartkarma as an independent insight on the 25th October 2017
Read more of Douglas’ work by clicking here!

 

This is a follow-up report of Mark Artherton‘s note The Future of Investment Research. The implementation of MiFID II is less than three months away and there are great changes that will occur in the investment research arena. In this note, I try to provide the major advantages and disadvantages of independent research in Asia as well as important changes that may impact this sector in the coming years. Clearly, technology will play a key role in these changes ahead and the companies that are well prepared for the technological innovations in the independent research are well positioned to benefit ahead.

It doesn’t matter if a cat is black or white, so long as it catches mice. (Source: Deng Xiaoping)

The quote above is one of Deng Xiaoping’s most memorable quotes and I believe it is very relevant to the changes ahead for both the sell-side and buy-side in terms of producing and consuming research. The buy-side wants research that will effectively enable them to make the proper investment decisions. For them, it really does not matter if the research comes from top-tier I-banks, smaller brokers, or independent research firms. As long as the research and ideas help these investment firms to make the correct buy or sell calls and help them to achieve extra alpha, that’s really what they are most interested in.

Alternative Data – Technology Driven Research

For example, there is a new field of technology-driven investment research that many asset management companies and hedge funds are increasingly relying upon, which is called “Alternative Data.” This is basically what the name suggests, which is using alternative data sources (as opposed to traditional data sources) and apply analytics to achieve extra alpha in the portfolio performance.

According to the Tabb Group, the alternative data market was about US$200 million in 2016 and is expected to become about US$400 million in 2020. According to the alternativedata.org, the number of “pure-play” alternative data providers globally rose from about 60 in 2010 to more than 130 as of September 2017.

Some of the leaders in the alternative data sector include companies such as Yipitdata, Foursquare, and 7 Park Data. Top-tier brokers such as Morgan Stanley (Alphawise) and UBS (Evidence Lab) also provide various data analytics services.

The alternative data sector is often broken down into the following main areas:

  • Web data
  • Credit card/debit card information
  • Email receipt
  • Web traffic
  • Geo-location/satellite
  • Sentiment

Main areas of alternative data: (Source: alternativedata.org)

How Does Alternative Data Work?

The following are examples of how alternative data works. These examples are taken from public sources mostly from the United States.

  • Foursquare – In 2016, Foursquare accurately predicted that Chipotle’s quarterly sales would drop about 30% versus actual sales decline of 29.7%. Foursquare is a local search and discovery service mobile app. The company uses its smartphone driven database and lots of foot traffic of its users to provide alternative data insights on retailers, real estate, and other consumer sectors.
  • Dataminr – This company uses Twitter and other social media sources to provide investors early indications on certain event outcomes. For example, tweets coming from Japan provided early clues to a recent North Korean missile launch over Japan. Dataminr also claims to have detected the vote outcome of Brexit and communicated to its clients prior to the results becoming public.
  • RS Metrics – Using satellite images, get access to the improved information about traffic flow at JCPenny malls and investors could trade on this name prior to the quarterly earnings announcement.
  • Quandl – Gather access to building permits throughout the US and the data is analyzed so that the user can view the changing levels of construction activities in different parts of the US and derive how certain construction companies are doing.
  • M Science – The company uses data mostly derived from credit card transaction data, tracking various metrics such as average transaction values, unique shoppers, and gross subscriber additions for various companies and industries.

Implications for Asian Alternative Data Providers

The examples above were mostly from the US market. However, as the market gets bigger, customers will increasingly seek alternative data in non-US markets such as Asia and Europe. On the Smartkarma platform, there are insight providers such as Ben Li (JD Finance Quantamental Research) and Ryan Shea (Amareos) that provide “alternative data” related research. My understanding of how JD Finance Quantamental Research works is that it utilizes the web data and other Big Data sources to refine and analyze information that is useful for many clients while Amareos provides extensive data analytics using various sentiment indicators. Please contact Ben Li and Ryan Shea for further details.

The growth of alternative data is likely to be explosive in Asia, mainly because this industry is starting from a low base and also there appears to be a great demand for technology-driven research that could be more effectual than the traditional way of conducting “channel checks.” 

For example, one of the traditional ways of conducting channel checks of a retail store is to check them out in person to get a “better feel” for the traffic flow and also chat with the salespeople to listen to what are some of the best selling items recently. However, if the smartphone users and their foot traffic patterns can be tracked at various retail shops and if there are enough users and data sets to reduce the potential outlier effect (such as the Foursquare’s analysis of Chipotle’s quarterly sales using the foot traffic of its users mentioned above), from a fund managers’ perspective, the latter information would be much more worthwhile having.

The competition for alternative data research in Asia will become more intense in the years to come. The natural path of competition will likely be the major players that have already established a strong presence in the US mentioned above will try to expand their services to cover more Asian companies. Plus, the large I-Banks such as Morgan Stanley and UBS as well as other large information providers such as Bloomberg and Thompson Reuters will likely bolster their alternative data analytics services. The numerous insight providers at Smartkarma that already provide alternative data services will also benefit from the greater customer demand and for those companies that do not provide alternative data services, they will likely be forced by the market to consider providing them as well.

In addition to these alternative data providers, there is a growing niche for industry expertise by sector management veterans. The most prominent firm in this sector globally is the well-known Gerson Lehrman. On the Smartkarma platform, there are industry veterans such as Howard J Klein who provide unique sector insights of the global gaming industry. Howard’s proprietary gaming metrics are different from the standard sell-side data points but are based on industry views of management evaluation, discussions with gaming industry contacts, and data points such as average bets per table over time, total ratio of gaming positions to the marketplace, etc.

Independent Research Pros and Cons

1. Non-Biased, “Out-of-the-Box” Investment Call on a Company/Sector

Without a question, technology will play a much bigger role in all areas of research in the coming years. The alternative data research that we summarized above is just a tip-of-the-iceberg. In the midst of these changes, there are some significant changes that are likely to occur as a result of the implementation of MiFID II. One of the major ones is that the buy-side will be scrutinizing carefully exactly how and what they spend on written research and interactions with analysts/companies. In a recent article on Bloomberg, it showed how the fund managers viewed one-to-one meetings and corporate access as two of the most highly valued services provided by the sell-side (see below).

Given the fact that setting up company meetings and corporate access are so critical, it is very difficult to have non-biased views of a company. For example, there are more than 20 local sell-side firms that cover widely followed stocks such as Samsung Electronics Co Ltd (005930 KS) and NCsoft Corp (036570 KS). All of the local sell-side analysts have BUY ratings on these names. If analysts put a HOLD or SELL report on these names, they could kiss goodbye any chances of a non-deal investor roadshow with these companies and they may even have difficulties setting up a company visit as well.

In the table below, we have tabulated the investment recommendations of the top 20 stocks listed on the KOSPI exchange by the local sell-side firms. Typically, there are 20+ sell-side local firms in Korea that cover these stocks. Of these 20 stocks, there are a total of 357 investment recommendations by the local sell-side firms. BUY recommendations represent an overwhelming 86% of the total, HOLD represent 13.2%, and SELL/Others are a tiny 0.8%. In fact, there is only one SELL rating out of 357 total ratings by the local brokers in Korea for the top 20 stocks on KOSPI! This is a clear-cut indication of a CLEAR BIAS towards having a BUY rating on the well-followed stocks in Korea.

When the stock market (such as KOSPI) is going up as it has been in the past year, having such a positive bias may be ok but we have seen numerous times in the past two decades how the market could turn down violently in a short period of time. From the perspective of fund managers, having such an overwhelming positive bias by the sell-side community is not really helpful. However, the incentive system (especially the significant demand to provide one-to-one company meetings and corporate access have a clear impact on the sell-side analysts’ having a positive bias in their written research of the companies under their coverage.

In the midst of this dilemma, how do sell-side analysts try to provide a “more negative, differentiated” view of a company without putting a HOLD or a SELL rating? Having worked on the sell-side for many years, there are several “arsenals” that the sell-side analysts have at their disposal where they could maintain a BUY rating but have a more negative view than the consensus which are as follows:

  • Lower earnings estimates and target prices – When a well-followed sell-side analyst slashes earnings and price targets of a large-cap company in Korea (especially when this is the FIRST earnings/price target reduction) among the sell-side community, it sometimes pays to take heed.
  • Set target prices that are at the low end of the consensus target price ranges
  • “Trading Buy” – This is a weak form of Buy (in between Buy and Hold).

All the methods mentioned above are ways that the sell-side analysts could partially differentiate their research without provoking a severe backlash from the company they cover by putting a SELL report on a company.

Clearly, the Buy-Side is not happy with existing sell-side coverage. They want change. That’s why companies such as Smartkarma have been able to develop a real business capitalizing on the existing shortfalls of the marketplace. The European regulators also understand the frustrations of the Buy-side and have taken the lead in trying to implement MiFID II. As such, we believe that one of the major advantages of independent research firms will be their ability to provide real value-added research in making “out-of-the-box,” non-consensus calls on stock investments. 

Investment Recommendations of the Top 20 Stocks on KOSPI Among Local Sell-Side Firms
Company# of Sell-Side Firms BUY*HOLDSELLOthers*
Samsung Electronics2323000
SK Hynix2319400
Hyundai Motor2320300
POSCO1816200
Samsung C&T1110100
LG Chem2119110
Naver2525000
Samsung Life Insurance1614200
KEPCO1612400
Samsung Biologics109100
KB Financial Group1111000
Shinhan Financial Group1110100
Hyundai Mobis2119101
SK Telecom1513200
SK Holdings1212000
SK Innovation2020000
LG H&H2315701
Amore Pacific2151600
LG Electronics1816200
KT&G1919000
Total3573074712
Source: Naver Finance, WiseFN
Note: Trading Buy is included in Buy; Others – Excluded from coverage


Fund managers’ changing behaviour with respect to taking meetings – We have been hearing from industry contacts that there will likely be a changing behaviour of how fund managers take meetings. For example, while fund managers are likely to continue to take meetings with top companies in Korea, they will be more hesitant on taking meetings with sell-side analysts, especially if they are relatively junior or are not one of the top-ranked analysts. In the past, the equity salespeople played a key role in“schmoozing” their clients to take meetings with junior research analysts. Now, because of the need to put a firm “dollar value” on the time spent with the analyst, the fund managers will reduce the number of meetings taken with the sell-side analysts.

How the Buy-Side Uses the Sell-Side: The Bread and Butter – With the oncoming MiFID II, there are a lot of concerns about the extent to which the overall research pie will shrink, despite the growth of independent research. One of the “bread-and-butter” ways that the buy-side uses the sell-side is as follows:

  • The buy-side fund manager is interested in a particular stock (let’s say POSCO).
  • The buy-side analyst/fund manager asks for models of POSCO from sell-side analysts. Typically, the fund manager asks models from 3-5 sell-side firms.
  • The buy-side analyst/fund manager goes through the model in detail and sees where the consensus numbers are.
  • If the buy-side analyst/fund manager has a strong conviction in POSCO and believes that the sell side is “too low” or “too high” in their estimates of sales, profits, and cash flow, then the buy-side analyst/fund manager will pull the trigger and buy or sell POSCO.

There will always be a need for sell-side equity analysts since they provide financial projections from which the buy-side could gauge the consensus and interesting ideas that the fund managers could use to make investment decisions. Despite this need, because of the shrinking research budget, the mid-to-low tiered brokers with lack of any differentiation in their research are ripe for consolidation or exit from the research business.

2. Payment for Independent Research

The payments for independent research are mainly broken down into fixed monthly fees or a certain amount per report. Companies such as Smartkarma charges a fixed monthly fees to its clients whereas other independent research outlets charge its clients on a per report basis. It would appear that the monthly fixed payment scheme is winning among the different types of independent research payments.

A major reason for this is that a big part of independent research is all about providing great ideas. And that great idea could be presented in a short one page or it may need to involve 20+ pages of explanations. Every research is different in terms of its contents and length. Plus, research analysts may provide great investment ideas one day but fail to deliver great ideas on their next reports. As such, it is very difficult to price a research on a per a research basis (exception could be customized, in-depth research for a specific client).

Sometimes, people refer to pricing research similar to how Apple makes money from users that download music on iTunes. We would argue otherwise, mainly because music is not about ideas. When you download a song on iTunes, you pretty much know what you are getting. This is not the case with research. Smartkarma has been trying to create a “ranking system” for a research (such as how many times it has been viewed by clients, how many times it has received “insight liked”, etc. We believe that this is a step in the right direction, although the overall payment system for independent research will continue to evolve with improving technology and changing customers’ demands.

In a recent Bloomberg article, it mentioned how Morgan Stanley plans to charge US$2,500 an hour for private meetings with its equity analysts for bespoke research projects. This appears to be the top-end pricing for a one-on-one meeting with a sell-side analyst. We wonder how many firms are willing to spend this amount of money for a one-hour session with the sell-side equity analyst. Fewer than 300? or 100?

One of the challenges of the payment system for independent research post-MiFID II is the difficulties in scaling up the business. Currently, the securities firms such as Goldman Sachs get paid by asset managers based on a variable rate basis, mostly determined by how much the asset managers trade with Goldman Sachs. However, some of the independent research providers charge their fees based fixed rate basis. So one of the main issues is that regardless of the size of the asset manager (whether it manages US$10 billion or US$100 million), the independent research provider whose payment system is based on fixed rate basis will typically charge the same monthly rate for both clients.

Sector/Company Coverage

One of the major issues of the independent research firms is the sector and company coverage. In the traditional sell-side coverage, the formula is pretty simple. The senior analyst at a sell-side firm typically has 12-18 companies under coverage, with focus on specific sectors such as banking, technology, or telecom/Internet. The focus on a specific sector is both positive and negative. For example, in Korea, the senior tech analysts with extensive experience in covering Samsung Electronics are the most highly sought after right now. They are typically paid more than double the average sell-side analysts.

When a certain sector is in a surging mode (such as the Korean shipbuilding sector from 2005 to 2007), there is a great demand for shipbuilding analysts. However, when the shipbuilding sector crashed from 2008 to 2010, the shipbuilding analysts also fell out of favour. Therefore, a key question that the independent research analysts and companies need to address is to have a specific plan of what sector and companies to cover and ask themselves whether the research adds additional value to the clients compared to the research that is already available in the market.

Opportunities for IPOs, M&As, and Merger Arb Related Research in Asia – In Asia, the research related to IPOs, M&As, and merger arb related opportunities have been lacking and this is one of the areas that Smartkarma has rightly identified and has been able to exploit. For example, there are numerous interesting IPOs coming out of Korea, China, and Southeast Asia. In the past, the bankers that were arranging the IPO deals were mostly responsible for the research of these IPO related companies in Asia. There was a clear need for more independent research of these Asian IPO companies and Smartkarma has been able to provide research of many of these Asian IPOs.

Opportunities for Companies Sponsored Research in Asia – Unlike in North America where companies sponsored research is well accepted, this is not the case in Asia. There are numerous independent equity research firms in North America that generate revenue from companies (typically small-mid cap) sponsored research. These companies want a greater research of their companies in order to generate higher investors interest in the stock. Typically, these companies pay US$25k to US$30k+ on 20 plus pages of initiation of company report plus quarterly updates that are distributed to major institutional investors as well as major global information platforms such as Bloomberg.

Although it would be nice to have Asian companies pay for research on initiation of company reports, this is not common practice in Asia right now. There are a lot of stumbling blocks to this in Asia. A key reason for this is because the owners and professional managers that are running the companies in North America have high incentives to raise the stock prices of their companies since many of them have stock options or equity in the company. On the other hand, the professional managers running companies in Asia typically do not have stock options or significant equity in their companies. Overall, we think that the company sponsored research will likely move at a snail-like pace in Asia in the coming years.

Conclusion:

The onset of MiFID II will bring about enormous changes to the independent research globally. There will finally be a price attached to research and that is both good and bad for the industry participants. The changes should have a positive impact on independent research providers that are able to bring real value in terms of non-consensus ideas that impact share prices and provide extra alpha to their clients. But there are credible concerns that the overall research budget will shrink.

Technological innovation will play a key role amidst all these changes in research distribution. Smartkarma has understood the importance of technology from the inception of the company and has tried to develop its business with the emphasis on using technology to develop a superior platform for independent research. Our studies of the independent research have also revealed that the technology-driven “alternative data” research & analytics are likely to be one of the fastest growing services in the years ahead.

 

Independent Research in Asia 2.0

by Douglas Kim

Published on Smartkarma as an independent insight on the 25th October 2017
Read more of Douglas’ work by clicking here!

 

Sources:

https://www.washingtonpost.com/news/innovations/wp/2016/04/28/how-foursquare-knew-before-almost-anyone-how-bad-things-were-for-chipotle/?utm_term=.0b7038afd2d6

http://www.valuewalk.com/2017/09/dataminr/

https://intelligenttradingtechnology.com/data-centres-colo/blog/quandl-offers-alternative-data-designed-improve-trading-decisions

http://www.businessinsider.com/hedge-funds-are-analysing-data-to-get-an-edge-2015-8

http://www.integrity-research.com/alternative-data-researcher-m-science-rejuvenated/

https://qz.com/1082389/quant-hedge-funds-are-gorging-on-alternative-data-in-pursuit-of-an-investing-edge/

https://www.ft.com/content/d86ad460-8802-11e7-bf50-e1c239b45787?mhq5j=e5

https://www.bloomberg.com/gadfly/articles/2017-10-22/what-s-a-star-analyst-really-worth

Oct 19
0

The Future of Research

By | General | No Comments

 

The Future of Research

by Mark Artherton – Founder & CEO of LR Investment Services

Posted on Smartkarma as an independent insight on 19th October 2017
Read more of Mark’s work by clicking here!

 

I recently attended the opening event for the Smartkarma UK office in Soho, London.  The event was well attended and there was plenty of lively debate around the impact of technology on investment research.

The first panel discussion focused on the subscription economy.  The discussion on this panel moved onto the similarities (or lack of) between investment research and other things that are now moving to be sold under a subscription model.  The moderator likened car sharing to investment research.  Ownership of cars will be a thing of the past and there will be a car waiting at the end of the road for the time you wish to use it.  The implication of such a model is that instead of a portfolio management firm ‘owning’ investment bank waterfront coverage at a very high price, that research would be better served by a more focused subscription model where the users of research only used the research that they required at the time they required it.  No need for that expensive SUV to be sat on the driveway or in the garage when the slack can be used by others whilst reducing your costs.

It was a well-received analogy, despite the differences between information and physical goods.  The analogy triggered some interesting discussion amongst the panel and I would encourage readers to view the panel discussion when it is posted on the Smartkarma website.  The downside of such a move for the producers of research is that the size of the pie is that much smaller.  Some panelists felt that the amount spent on investment research could halve.   It was stated that most the impact should be felt by the investment banks rather than independent research providers and there would be a huge market share gain from independent research.  Independent Research would be in a stronger position to utilise the rise of new models to meet the subscription requirements of the consumers of research.

I would like to move this analogy further along and to sketch out the way I believe that the investment research ecosystem should evolve.   This is an opinion piece and the existence of extreme legacy issues and path dependency make it likely that my vision of the future will not necessarily be the one that comes to pass and I will discuss those issues at the end of the piece.

How do you define investment research?

Investment Research can be broken down into three parts.  The first part is obtaining knowledge or information.  Specifically, knowledge that is available to all, not inside information.  This knowledge can be disseminated widely using new technologies and is accessible to all at all times.  This gives pure knowledge little intrinsic value beyond its initial cost of production.  This is one of reasons why Wikipedia is free.

The second part is the filtering of that knowledge.  The first stage of filtering is removing ‘fake’ knowledge.  Fake news is a hot topic at the moment and likely to continue to be so.  In an unfiltered, unedited internet base world the ability for anyone to pass anything off as knowledge increases dramatically.  Google’s search algorithms attempt to provide some comfort for the user, by (and I am massively oversimplifying here) using other sites link to a particular source as a way to measure its veracity and validity.

The second stage of filtering is reducing the knowledge down to that which is the most pertinent to an individual’s investment process and decision-making needs.   Filtering the relevant from the irrelevant in a way that fits a decision-making process.  In a world where all (non-inside) knowledge is potentially available to all this filtering system is exceptionally important.  This filtering has tremendous value.

The final part is the synthesis of this filtered and relevant knowledge.  The synthesis has two major applications for fundamental portfolio managers.  The first is its application to buying a stock in the portfolio or selling a stock from the portfolio.  The second application of the synthesis is for portfolio construction, how to arrange the individual building blocks of a given portfolio.  Synthesis, when combined with a circumstance based approach, has tremendous value.

Traditional investment researchers carry out all three of these functions in ways that vary in their effectiveness and use, but each will have their own specific method of filtering and synthesis which may or may not need an individual client’s needs.

To summarise, investment research is the following:

  • Obtaining knowledge;
  • Filtering this knowledge for quality and relevance;
  • Synthesising the filtered knowledge to impact buying and selling instruments and the portfolio construction of those instruments.

The Investment Research car

Let’s now return to the analogy of the shared car.  Investment research is so much more than sharing a ready-made car.  Ideally, investment research is having a bespoke vehicle built to your current specification at that moment in time to achieve the complete goals of a particular journey.  From choosing the type of fuel, the individual parts in the engine, the seating layout, the technology available within the vehicle, the type of terrain the vehicle will have to traverse, and the final destination.  All of this needs to be carried out in a way that understands the portfolio manager’s immediate needs without the portfolio manager necessarily having to be explicit about those needs.

Imagine a scenario where a portfolio manager has at his fingertips all of the information that is relevant and synthesised to meet her individual decision-making process allowing her to make an effective decision as to Sell something from the portfolio, buy something for the portfolio, alter the portfolio construction or just to leave everything alone at the correct point in time.  This information is supplied in a way that it can be digested rapidly.  Quantitative and algorithmic funds are already in this scenario because numbers are easy (easier) to put into such a system.  If we accept the premise that active human-led portfolio management can add value then a system as described above would add tremendous value (though some of this value is likely to be short-term and ephemeral – as you might pay hundreds of ponds to eat in a high-end restaurant).  The system as described does appear to be some form of unattainable nirvana given the path dependency built into the system.

However, it is my belief that the technology tools are there to achieve this aim.  From data collection all the way up to the basic level of Artificial Intelligence that has been achieved(human replicating AI is a lot further out than the futurologists would have us believe in my opinion).  Human input is required at all levels and it is this human technology interaction that is very important.  What is missing is the correct application of these tools – Smartkarma is a step in the right direction.

Is history holding us back?

Historical activities and path dependency often slow the evolution of systems.  The vast bulk of investment research has barely changed in it format over the past 50/60 years – since Ben Graham’s seminal book ‘Security Analysis’ and the creation of the Investment Research Report as the demand from institutional investors built in the 1950s.  There have been many tweaks and improvements in education and even quality, but the production model has not changed too much.  Delivery was impacted by email, the internet, and smartphones.  Though most delivery models are just online libraries.  Consumption itself has also altered little over time.

The historical model has not lent itself well to collaboration.  At best the lead analyst had a team of ‘grunts’ to do the legwork, but true collaboration across disciplines was very hard to find.

What is required is a 360-degree restructuring of the whole active management industry and the way research is produced, distributed and consumed.  Cherry picking models and technology from other industries is key to this.  Collaboration is also very important in this approach, getting the best to work together to give an outcome that is greater than the sum of the parts.  The success of such an approach would become clear very quickly so a shift from early adopters to the mainstream could be very rapid for the company that delivers such a system.

Creative Destruction

MIFID II has provided a catalyst for buy-side firms to think about their consumption of investment research and it has also forced all the providers of investment research to evaluate their distribution models.  The sell-side (investment banks) remain formidable opponents for independent research.  Prior to MIFID II, inbuilt biases in the system favoured investment bank (IB) research.  Some independent research providers (IRPs) were able to build businesses but true scale was rarely reached.  Some IBs may exit research but most will alter their delivery of research to benefit from the changing marketplace.  The bulge bracket investment banks have a lot of advantages on their side – deep pockets, extensive client relationships, and technology expertise to name but a few.

Does the buy-side need research that is produced outside of its own walls?  Large buy side houses may not need it at all in the future. With more effective internal communication, the larger houses will be pressured to use the resources and the knowledge within their own walls. If the payments for research out of p&l migrates globally then justifying external research becomes harder and harder, especially when process fit is considered.  The day cannot be too far away when a large buy-side house cuts off all external research. The trend of M&A to create larger and larger fund houses accelerates this possibility.  A key advantage that larger houses have is the relationships with the companies. An investor relations professional can only deal with a limited number of market touch points. Large shareholders will flex their muscles and retain access.  This approach of self-sufficiency does make seem to make some sense for the larger fund houses.   There is a global trend to bring more capabilities in house for the larger companies.  Especially for those institutions that deal in information.

There are some shortcomings to this model.  Would a large house pay for a shipping analyst, for example?  Someone whose knowledge is only relevant in short bursts every few years. This is also a problem for the independent research analyst who covers this sector.  Large houses could avoid this sector completely.  Small sectors, such as shipping, can be (more or less safely) ignored – in markets like Korea where they can move the index dial maybe this is not the case.  A further option is to hire or develop specialists with complementary skills in these markets so they remain relevant through the cycle.  The correct use of technology will enable individuals to cover more and more in the future, in my opinion.

For medium and small size fund houses the issue revolves around access to expertise (in this case I am not explicitly talking about expert networks as inside information issues cause problems for many).  Medium and small houses need access to external research. Prior to MIFID II this would almost force smaller houses to trade more to generate commission dollars to get research access.  We are all aware of the premium tiers of service at IBs and the amounts to get such service.  In effect, the buy side shared the sell side’s product.  Thousands upon thousands of buy-side firms sharing tens, maybe a hundred, sell-side firms resources.  Large houses generated the most commission, but medium and small houses got access to this research, which was, in effect, paid for by the larger houses.

As suppliers of investment research, there are many, many high-quality individuals looking at the same things.  Some will have greater knowledge and understanding in some areas and some will have a better reading of the market for making buy calls and some will have a better reading to make sell calls.  Some are better at making such calls in absolute terms and some are better making them relative to a country benchmark and yet others are better making them against regional or global benchmarks.  Some will fit better with one client’s style whilst others will fit better with other styles.

Oddly enough, even though they may appear to be more challenged now, the mid and small sized investment houses could be forced into the correct solution.  By providing a ‘virtual’ research department that alters its composition in line with the buy-side institutions needs, a solution can be found that shares resources effectively without diluting their value.  A research report that can be read by anyone is viewed as having limited value.  A bespoke, collaborative piece generated by AI and HI (Human Intelligence) has much more value.

Independent research needs to decide if they are media like – low fee high readership – like a high-end FT, or if they are bespoke consultancy providers.  There is space for both models in the marketplace.  There are also risks in both models, with the overhead for the media model being huge, for example.  Bespoke consultancy is exceptionally difficult to scale, but advances in technology are bringing scalable bespoke solutions much closer.

Does it make sense for multiple people to read the latest monetary report from the Korean Central bank? Or does it make sense for one individual to do so and summarise in a specific database friendly way?  Does it make sense for multiple people to listen to the earnings call of company A or read the presentation of company B or read the IPO prospectus of company C (to be fair I am pretty sure that most people don’t have the time to read these)?  Or does it make the most sense for one person to do this and summarise for a database?  There is so much duplication and inefficiency in investment research.

An additional factor to consider in such a model is the benefit it could have to consumers of wealth management products.  Roboadvisors are both adding new clients but also eating into the lower end of the wealth management client base.   This is not the place to discuss the pros and cons of roboadvisors, but the relationship model offered to more wealthy clients would be pressured by the changes we are seeing in research delivery.  The simple delivery of other’s views will not survive this revolution in the delivery of investment thought.  There will always be a place for individuals to ‘sell’ the initial benefits of a given system of research, but the management of that relationship will become less lucrative.

One thing is very clear, the future of investment research will be very different to its past.

Conclusions

Being the iTunes of investment research is not enough in an industry undergoing such significant change, not when it is clear that the more effective business models such as Spotify and others are eating at the iTunes model.  Differentiated models that treat information as ingredients that are supplied effectively to the synthesisers is a possible way forward.

Differentiated models are needed that treat information as Lego building blocks to be put together in a variety of different ways, collaboratively, to achieve different ends.  The days of the long form report written by an individual which is then stocked in a library, put on a website, emailed (or added to iTunes) are limited.  The way research is produced, delivered, and consumed will be drastically different from the model we see today.  Technology will provide each individual at each point of time, a differentiated and unique build of relevant, high-quality information in a structure which allows a decision maker to rapidly make investment decisions.

 

The Future of Research

by Mark Artherton – Founder & CEO of LR Investment Services

Posted on Smartkarma as an independent insight on 19th October 2017
Read more of Mark’s work by clicking here!