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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

Multiple Countries / Cross Asset Strategy

<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. 

Vanguard FTSE Emerging Markets ETF (VWO US)

Consumer Staples Select Sector SPDR Fund (XLP US)

TMI Thematics: Cyclical Rotation Through The Lens of Text Mining