TMI Snapshot:  Financial Conditions, Wall Vs. Main & Biden Stimulus Via Text-Mining

TMI Snapshot: Bubble Fears Subside, Commodity Supercycle Views Spike, Vaccine Sentiment Rises

TMI Snapshot:  Update on Underlying Inflation Expectations from Our Text-Mined Indicators

Introducing TMI Data Science: Delivering Alpha With Custom NLP-Based Leading Indicators

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 sees a +3x STDEV surge in mentions of Fed tapering or withdrawal of accommodation, largest since 2018</li>
<li>This follows a notable spike in the 10-year yield, and comments from regional Fed presidents Harker, Bostic, Kaplan &amp; Evans last week alluding to some tapering as early as this year or "sooner than people expect"</li>
<li>Some in the financial media (i.e. <a href="https://www.bloombergquint.com/opinion/fed-s-taper-talk-directed-at-bitcoin-and-tesla" target="_blank" rel="noopener">Bloomberg</a>) have linked this development to "pervasive talk of asset bubbles" centering on Tesla and Bitcoin</li>
<li>In the aftermath of significant TIPS breakeven widening, we see notably larger magnitude and higher velocity in inflationary/reflationary expressions  (+1.5x STDEV) vs. relatively muted increase in expressions related to asset bubbles &amp; market exuberance (&lt;1x STDEV)  </li>
<li>In addition, our data shows that reporting on the Georgia Democratic Sweep was primarily focused on inflation, compared with coverage around the November elections which discussed a potential Democratic Sweep primarily in the context of increased regulation and higher taxes</li>
<li>As the evolving inflationary mindset is likely far more sticky than localized notions of an asset bubble in certain equities or cryptos, upside to yields may be underestimated along with USD support </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 sees a +3x STDEV surge in mentions of Fed tapering or withdrawal of accommodation, largest since 2018
This follows a notable spike in the 10-year yield, and comments from regional Fed presidents Harker, Bostic, Kaplan &amp; Evans last week alluding to some tapering as early as this year or "sooner than people expect"
Some in the financial media (i.e. Bloomberg) have linked this development to "pervasive talk of asset bubbles" centering on Tesla and Bitcoin
In the aftermath of significant TIPS breakeven widening, we see notably larger magnitude and higher velocity in inflationary/reflationary expressions  (+1.5x STDEV) vs. relatively muted increase in expressions related to asset bubbles &amp; market exuberance (&lt;1x STDEV)  
In addition, our data shows that reporting on the Georgia Democratic Sweep was primarily focused on inflation, compared with coverage around the November elections which discussed a potential Democratic Sweep primarily in the context of increased regulation and higher taxes
As the evolving inflationary mindset is likely far more sticky than localized notions of an asset bubble in certain equities or cryptos, upside to yields may be underestimated along with USD support 
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. 

iShares 20+ Year Treasury Bond ETF (TLT US)

TMI Snapshot: Fed Tapering Talk Surge - Our Data Says This Is More About Inflation Vs. Asset Bubbles