TMI Snapshots: Quantifying Relative Sector Sentiment in the Recent Rotation Via Text Mining

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

TMI Snapshot: Update on Text-Mined Inflation Indicators & How They Line Up With the Value Rotation

TMI Thematics:  CNY Momentum Peaking? / Blue Wave Drives US Inflation Expectations, Not Earnings

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>Data from ~30 million participants in the Chase credit card panel (US) has shown a pullback in spending in recent weeks</li>
<li>The pullback appears to be independent of mobility dynamics, as in-person shopping outperformed overall spending</li>
<li>We text-mine the media for first-person accounts of hardship to find an increase in reported layoffs &amp; reduced personal spending, but the magnitude of increase has been encouragingly small (&lt;1x STDEV) so far relative to readings seen in H1</li>
<li>As we highlighted in <a href="https://www.smartkarma.com/insights/tmi-snapshots-quantifying-relative-sector-sentiment-in-the-recent-rotation-via-text-mining" target="_blank" data-smartkarma-citation="insights:45278" rel="noopener">TMI Snapshots: Quantifying Relative Sector Sentiment in the Recent Rotation Via Text Mining</a>, the cyclical rotation is alive and well on mid-term vaccine-driven recovery expectations; but the potential for vol around year-end funding or seasonal dynamics may be amplified by these weak Q4 trends once they appear in official macro releases</li>
</ul>


Data from ~30 million participants in the Chase credit card panel (US) has shown a pullback in spending in recent weeks
The pullback appears to be independent of mobility dynamics, as in-person shopping outperformed overall spending
We text-mine the media for first-person accounts of hardship to find an increase in reported layoffs &amp; reduced personal spending, but the magnitude of increase has been encouragingly small (&lt;1x STDEV) so far relative to readings seen in H1
As we highlighted in TMI Snapshots: Quantifying Relative Sector Sentiment in the Recent Rotation Via Text Mining, the cyclical rotation is alive and well on mid-term vaccine-driven recovery expectations; but the potential for vol around year-end funding or seasonal dynamics may be amplified by these weak Q4 trends once they appear in official macro releases


TMI Snapshot: High-Freq US Spending Data Pullback Looks Independent of Mobility, But Is It Relevant?

United States

TMI Snapshot: High-Freq US Spending Data Pullback Looks Independent of Mobility, But Is It Relevant?