Managing Director

Elan Gore

TMI Data Science

TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade & traditional media.  Our proprietary software, TMI Machine, is a text-mining platform designed with the buy-side & capital markets professional in mind, text-mining the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income & individual equities.  TMI provides custom leading indicators and systematic trading strategies, operating at the nexus of linguistics & statistics drawing on vast experience in investment banking and hedge fund settings in senior quantitative and fundamental roles.  

TMI Data Science was founded by Elan Gore, an award-winning Senior Global Basic Materials Equity Analyst & China Economist with 15 years of experience in North American hedge funds & institutional managers; and Alessandro Porrino, Ph.D., an Algorithmic Trading Analyst and Programmer with 10 years of front-office experience ranging from complex FX option pricing to auto-hedging strategies at Bank of America Merrill Lynch and Standard Chartered.  Mr. Gore holds an MBA in Finance from New York University Stern School of Business, and Mr. Porrino holds a Ph.D. in Systems Engineering from Brunel University London.

Cross Asset Strategy

<ul>
<li>Our text-mining finds cyclicals sentiment momentum now up +3.3x STDEVs, highest in the history of our series and slightly above the highs we last saw in December '17</li>
<li>Defensives sentiment momentum bottomed in the first half of December at -1x STDEV, lowest reading since May, but has since recovered to marginally positive territory potentially aided by recent tech outperformance</li>
<li>In the past year, cyclicals sentiment has been &gt;80% correlated with Global Metals &amp; Materials, 68% correlated with Global Industrials, 35% correlated with Global Financials and uncorrelated with Global Energy</li>
<li>In December, only Global Metals appear to be strongly correlated with the surge in cyclicals sentiment as energy, financials and industrials performance has been flat; one explanation is the stark divergence in '21 estimate revision trends by sector, where materials analysts are struggling to catch up with surging metals prices vs. tepid industrials and energy revisions</li>
<li>Ironically, our copper sentiment indicator registered a +3x STDEV spike in November and remains elevated, preceding the final 2020 melt-up in cyclicals sentiment (as well as the move in copper); back-testing suggests trading MSCI Global Metals based on cyclicals sentiment outperforms a passive position, but trading based on copper sentiment would have generated superior returns - implying that getting the copper trade right is key to getting the overall cyclical trade right at this stage of the economic cycle</li>
<li>Do other cyclical sectors simply catch up with metals &amp; materials in Q1?  Industrials may hold the key to the next leg of cyclical recovery as the market looks through winter seasonality to improved operating leverage starting in Q2; investors may not be as forgiving in the short-term with energy, as long as mobility is depressed; but the promise of post-vaccine normalization remains compelling across the board</li>
</ul><div class="content-highlight"><p>TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. </p></div>


Our text-mining finds cyclicals sentiment momentum now up +3.3x STDEVs, highest in the history of our series and slightly above the highs we last saw in December '17
Defensives sentiment momentum bottomed in the first half of December at -1x STDEV, lowest reading since May, but has since recovered to marginally positive territory potentially aided by recent tech outperformance
In the past year, cyclicals sentiment has been &gt;80% correlated with Global Metals &amp; Materials, 68% correlated with Global Industrials, 35% correlated with Global Financials and uncorrelated with Global Energy
In December, only Global Metals appear to be strongly correlated with the surge in cyclicals sentiment as energy, financials and industrials performance has been flat; one explanation is the stark divergence in '21 estimate revision trends by sector, where materials analysts are struggling to catch up with surging metals prices vs. tepid industrials and energy revisions
Ironically, our copper sentiment indicator registered a +3x STDEV spike in November and remains elevated, preceding the final 2020 melt-up in cyclicals sentiment (as well as the move in copper); back-testing suggests trading MSCI Global Metals based on cyclicals sentiment outperforms a passive position, but trading based on copper sentiment would have generated superior returns - implying that getting the copper trade right is key to getting the overall cyclical trade right at this stage of the economic cycle
Do other cyclical sectors simply catch up with metals &amp; materials in Q1?  Industrials may hold the key to the next leg of cyclical recovery as the market looks through winter seasonality to improved operating leverage starting in Q2; investors may not be as forgiving in the short-term with energy, as long as mobility is depressed; but the promise of post-vaccine normalization remains compelling across the board
TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. 

TMI Snapshot:  Cyclicals Sentiment Melts Up into Year-End, Impact Concentrated in Materials Sector

<ul>
<li>Following the November melt-up, we text-mine for clues on inventory restocking dynamics going into year-end</li>
<li>While references to a general inventory restocking in the global financial media are up nearly +4x STDEVs, our data suggests this is the second notable raw materials restocking wave since the recovery began, following a more robust restocking seen in August; nonetheless, the current phase is abnormal relative to typical year-end seasonality, highlighting much-anticipated pent-up demand</li>
<li>Our short-term broad commodity sentiment indicator hit +2x STDEVs, its highest reading since January, on 11/23; this followed a significant spike in China macro sentiment earlier in November, which was preceded by a multi-year record in our Copper sentiment indicator in the first half of the month</li>
<li>Current readings see continued positive sentiment momentum in palladium, copper, aluminum and crude, while negative sentiment persists in pulp, uranium and silver</li>
<li>Our sentiment picture for iron ore and steel has been obfuscated by Australia-China tensions, having turned neutral after readings of +3x STDEV and +1.8x STDEV in recent weeks; but our news attributions also identify reports of seasonally declining BF utilization and end demand in recent weeks</li>
<li>While raw materials-specific and short-cycle industrial restocking may pause in the next 6-8 weeks, the broader global finished goods restocking is likely to remain a supportive factor keeping commodities trading in tighter ranges relative to winter averages </li>
</ul><div class="content-highlight"><p>TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. </p></div>


Following the November melt-up, we text-mine for clues on inventory restocking dynamics going into year-end
While references to a general inventory restocking in the global financial media are up nearly +4x STDEVs, our data suggests this is the second notable raw materials restocking wave since the recovery began, following a more robust restocking seen in August; nonetheless, the current phase is abnormal relative to typical year-end seasonality, highlighting much-anticipated pent-up demand
Our short-term broad commodity sentiment indicator hit +2x STDEVs, its highest reading since January, on 11/23; this followed a significant spike in China macro sentiment earlier in November, which was preceded by a multi-year record in our Copper sentiment indicator in the first half of the month
Current readings see continued positive sentiment momentum in palladium, copper, aluminum and crude, while negative sentiment persists in pulp, uranium and silver
Our sentiment picture for iron ore and steel has been obfuscated by Australia-China tensions, having turned neutral after readings of +3x STDEV and +1.8x STDEV in recent weeks; but our news attributions also identify reports of seasonally declining BF utilization and end demand in recent weeks
While raw materials-specific and short-cycle industrial restocking may pause in the next 6-8 weeks, the broader global finished goods restocking is likely to remain a supportive factor keeping commodities trading in tighter ranges relative to winter averages 
TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. 

TMI Indicators: December Commodity Sentiment - Restocking into Winter on Pent-Up Demand Expectations

<ul>
<li>In last month's report we saw late-September USD strength contribute to softer base metals sentiment and a collapse in precious metals sentiment (amid reports of millennial preference for cryptocurrencies as an inflation hedge)</li>
<li>More recently, we saw copper sentiment surge to &gt;3x STDEVs, a multi-year record on our data, as financial media preoccupation with relative Chinese macro strength and strong EV demand met persistent newsflow on imminent labor-related supply disruptions in Chile; our back-testing suggests such anomalous sentiment readings normally lead to temporary pullbacks in the copper price</li>
<li>Gold &amp; silver sentiment fell further in October to levels last seen in April, but we see early signs of bottoming in gold; platinum sentiment improved on hydrogen economy news </li>
<li>Crude oil sentiment fell to its lowest since May, predictably attributed to the prospect of COVID-19 lockdowns spreading globally &amp; Libyan news</li>
<li>Iron ore sentiment has moved into positive territory in the final week of October, driven by 3 consecutive weeks of steel inventory draws in China and a notable rally in rebar prices</li>
<li>Despite deteriorating COVID-19 newsflow, crude weakness and USD strength, sentiment is positive on more commodities relative to late September, with supply disruptions and greater conviction on Chinese macro the key drivers</li>
</ul><div class="content-highlight"><p>TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. </p></div>


In last month's report we saw late-September USD strength contribute to softer base metals sentiment and a collapse in precious metals sentiment (amid reports of millennial preference for cryptocurrencies as an inflation hedge)
More recently, we saw copper sentiment surge to &gt;3x STDEVs, a multi-year record on our data, as financial media preoccupation with relative Chinese macro strength and strong EV demand met persistent newsflow on imminent labor-related supply disruptions in Chile; our back-testing suggests such anomalous sentiment readings normally lead to temporary pullbacks in the copper price
Gold &amp; silver sentiment fell further in October to levels last seen in April, but we see early signs of bottoming in gold; platinum sentiment improved on hydrogen economy news 
Crude oil sentiment fell to its lowest since May, predictably attributed to the prospect of COVID-19 lockdowns spreading globally &amp; Libyan news
Iron ore sentiment has moved into positive territory in the final week of October, driven by 3 consecutive weeks of steel inventory draws in China and a notable rally in rebar prices
Despite deteriorating COVID-19 newsflow, crude weakness and USD strength, sentiment is positive on more commodities relative to late September, with supply disruptions and greater conviction on Chinese macro the key drivers
TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. 

TMI Indicators:  November Commodity Sentiment - Base Overshoots, Ferrous Improves, Gold Bottoming?

<ul>
<li>As the street warms up to a potential Biden victory, arguments for improving equity breadth and cyclical rotation are starting to emerge again</li>
<li>Financial media references to a cyclical rotation saw a multi-STDEV spike in June, which coincided with a significant and notably enduring lift in the ratios of US industrials-to-staples and transports-to-staples </li>
<li>Our testing highlights the US transports-to-staples ratio as the most correlated with the cyclical rotation theme, but we see similar action in the copper/gold ratio and EM currencies</li>
<li>In the past 10 days, our text-mined data shows an incipient pro-cyclical move, but its momentum has yet to fully turn net-positive</li>
<li>Calls for a cyclical rotation softened through the September correction, COVID-19 second wave fears and more recent fiscal stimulus uncertainty; but the cyclical/defensive sector ratios endured as the structural reframing of a Biden presidency as an inflation-positive outcome went mainstream</li>
<li>While historically "cyclical rotation" and "value rotation" were strongly correlated, we have seen a decoupling in these themes due to the heavy burden of the COVID-19 crisis on financials and energy</li>
<li>Economists have pointed to the increased likelihood of a vaccine in H1 as a driver of recent bullishness and inflationary optimism, but observations from text mining and from the Superforecaster survey (Good Judgement Project) do not suggest new positives here</li>
<li>Predictably, at this stage of post-pandemic recovery the focus of cyclical rotation is on industrials and materials (particularly mining &amp; construction materials), with a Biden win implying elevated infrastructure spend</li>
</ul><div class="content-highlight"><p>TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. </p></div>


As the street warms up to a potential Biden victory, arguments for improving equity breadth and cyclical rotation are starting to emerge again
Financial media references to a cyclical rotation saw a multi-STDEV spike in June, which coincided with a significant and notably enduring lift in the ratios of US industrials-to-staples and transports-to-staples 
Our testing highlights the US transports-to-staples ratio as the most correlated with the cyclical rotation theme, but we see similar action in the copper/gold ratio and EM currencies
In the past 10 days, our text-mined data shows an incipient pro-cyclical move, but its momentum has yet to fully turn net-positive
Calls for a cyclical rotation softened through the September correction, COVID-19 second wave fears and more recent fiscal stimulus uncertainty; but the cyclical/defensive sector ratios endured as the structural reframing of a Biden presidency as an inflation-positive outcome went mainstream
While historically "cyclical rotation" and "value rotation" were strongly correlated, we have seen a decoupling in these themes due to the heavy burden of the COVID-19 crisis on financials and energy
Economists have pointed to the increased likelihood of a vaccine in H1 as a driver of recent bullishness and inflationary optimism, but observations from text mining and from the Superforecaster survey (Good Judgement Project) do not suggest new positives here
Predictably, at this stage of post-pandemic recovery the focus of cyclical rotation is on industrials and materials (particularly mining &amp; construction materials), with a Biden win implying elevated infrastructure spend
TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. 

TMI Thematics: Cyclical Rotation Through The Lens of Text Mining

<ul>
<li>After 3 months of consistent decline, our China Property Sentiment Indicator is showing notable signs of recovery</li>
<li>News attribution suggests this is primarily driven by decreasing negative coverage as the Evergrande liquidity crisis was averted limiting broader contagion; continued momentum on developer spin-offs of property management subsidiaries; and strong Golden Week consumption metrics related to home furnishings &amp; building products (a secondary parameter in our indicator)</li>
<li>Our text mining already incorporates recent negative news on shrinking land premiums, as well as coverage on (expectedly) heavy discounting during Golden Week sales; but the overall tone of coverage remains "less negative" in the month-to-date</li>
<li>The TMI China Property Sentiment Indicator has been 58% correlated with Chinese real estate equities (via CHIR ETF), 40%-54% with Chinese HY (via KCCB ETF), and 65% with copper prices (on a T24M basis)</li>
</ul><div class="content-highlight"><p>TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. </p></div>


After 3 months of consistent decline, our China Property Sentiment Indicator is showing notable signs of recovery
News attribution suggests this is primarily driven by decreasing negative coverage as the Evergrande liquidity crisis was averted limiting broader contagion; continued momentum on developer spin-offs of property management subsidiaries; and strong Golden Week consumption metrics related to home furnishings &amp; building products (a secondary parameter in our indicator)
Our text mining already incorporates recent negative news on shrinking land premiums, as well as coverage on (expectedly) heavy discounting during Golden Week sales; but the overall tone of coverage remains "less negative" in the month-to-date
The TMI China Property Sentiment Indicator has been 58% correlated with Chinese real estate equities (via CHIR ETF), 40%-54% with Chinese HY (via KCCB ETF), and 65% with copper prices (on a T24M basis)
TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. 

TMI Snapshots: China Property Sentiment Indicators Recover Post "Three Red Lines" & Evergrande Drama

United States

Copper is a chemical element with symbol Cu (from Latin: cuprum) and atomic number 29. It is a soft, malleable and ductile metal with very high thermal and electrical conductivity. A freshly exposed surface of pure copper has a reddish-orange color. It is used as a conductor of heat and electricity, as a building material and as a constituent of various metal alloys, such as Sterling silver used in jewelry, cupronickel used to make marine hardware and coins and constantan used in strain gauges and thermocouples for temperature measurement.

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Copper (COPPER COMDTY)

TMI Snapshot: Cyclicals Sentiment Melts Up into Year-End, Impact Concentrated in Materials Sector

Our text-mining finds that cyclicals sentiment is surging into year-end. While a consensus theme, materials equities have benefited...

Elan Gore

TMI Indicators: December Commodity Sentiment - Restocking into Winter on Pent-Up Demand Expectations

We text-mine for clues on the current restocking, and believe the anticipation of pent-up demand is likely to keep the commodities trading in a...

Elan Gore

TMI Indicators: November Commodity Sentiment - Base Overshoots, Ferrous Improves, Gold Bottoming?

Our text-mined commodity sentiment indicators see an overshoot in copper sentiment, a notable turnaround in iron ore sentiment, and potential signs...

Elan Gore

TMI Thematics: Cyclical Rotation Through The Lens of Text Mining

As the equity melt-up sees renewed "cyclical rotation" calls, we text-mine the global financial media to find early signs of recovery in the theme...

Elan Gore

TMI Snapshots: China Property Sentiment Indicators Recover Post "Three Red Lines" & Evergrande Drama

After 3 months of consistent slowdown and a dip into outright negative territory, our China Property Indicator is showing signs of recovery News...

Elan Gore

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