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>We run sentiment analysis around Rio Tinto's Juukan Gorge heritage site crisis, text-mining for ESG-related sentiment since news of ethically-challenged practices at RIO broke out</li>
<li>In early June, Rio Tinto revealed it had blasted a 46,000-year-old sacred aboriginal site, sparking widespread controversy and resulting in a management shakeout and parliamentary enquiry</li>
<li>Perceived as an ESG disaster, Rio Tinto continues to underperform FMG and the MSCI Global Metals &amp; Mining Index, though its performance gap with BHP closed in September following executive resignations</li>
<li>Fortescue's performance appears to have been unaffected by the Juukan Gorge crisis, but our sentiment analysis and news attributions see gathering clouds as FMG is recently linked to significant negative stewardship headlines</li>
<li>Our daily RIO ESG sentiment time series has been 74% correlated with RIO performance since May 31 with a 7-day lead</li>
<li>Though entirely dependent on the quality and volume of news flow, NLP-based sentiment analysis can help identify and attribute decoupling between equity performance and newsflow tone, as well as challenge confirmation biases, taking into account the rapid pace of news decay</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>


We run sentiment analysis around Rio Tinto's Juukan Gorge heritage site crisis, text-mining for ESG-related sentiment since news of ethically-challenged practices at RIO broke out
In early June, Rio Tinto revealed it had blasted a 46,000-year-old sacred aboriginal site, sparking widespread controversy and resulting in a management shakeout and parliamentary enquiry
Perceived as an ESG disaster, Rio Tinto continues to underperform FMG and the MSCI Global Metals &amp; Mining Index, though its performance gap with BHP closed in September following executive resignations
Fortescue's performance appears to have been unaffected by the Juukan Gorge crisis, but our sentiment analysis and news attributions see gathering clouds as FMG is recently linked to significant negative stewardship headlines
Our daily RIO ESG sentiment time series has been 74% correlated with RIO performance since May 31 with a 7-day lead
Though entirely dependent on the quality and volume of news flow, NLP-based sentiment analysis can help identify and attribute decoupling between equity performance and newsflow tone, as well as challenge confirmation biases, taking into account the rapid pace of news decay
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:  After Juukan Gorge, Rio Tinto Sentiment Stabilizes.  Reckoning Time For FMG?