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

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

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

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>Back in November, we text-mined for GICS sector-level sentiment shifts as the post-election cyclical rotation arrived (see <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>)</li>
<li>At the time, we saw Financials sector sentiment surge along with Materials, while Industrials sentiment remained subdued; these sentiment readings have been somewhat reflected in performance, as since October 31 the S&amp;P Financials (XLF) is up +28%, S&amp;P Materials (XLB) +21%, and S&amp;P Industrials (XLI) +18%</li>
<li>All cyclical sectors are now in positive territory sentiment-wise, with Consumer Discretionary and Financials sentiment now looking quite extended at multi-STDEV readings</li>
<li>Industrials sector sentiment stood out as relatively depressed for months, but is breaking out of its range in the last 10 days</li>
<li>As we noted in our post on cyclicals sentiment last week (<a href="https://www.smartkarma.com/insights/tmi-snapshot-cyclicals-sentiment-melts-up-into-year-end-impact-concentrated-in-materials-sector" target="_blank" data-smartkarma-citation="insights:46660" rel="noopener">TMI Snapshot:  Cyclicals Sentiment Melts Up into Year-End, Impact Concentrated in Materials Sector),</a> the rotation theme has been particularly strongly correlated to the Materials sector (metals in particular) and there is potentially room for laggard cyclicals - namely industrials - to catch up as recent sentiment readings imply </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>


Back in November, we text-mined for GICS sector-level sentiment shifts as the post-election cyclical rotation arrived (see TMI Snapshots: Quantifying Relative Sector Sentiment in the Recent Rotation Via Text Mining)
At the time, we saw Financials sector sentiment surge along with Materials, while Industrials sentiment remained subdued; these sentiment readings have been somewhat reflected in performance, as since October 31 the S&amp;P Financials (XLF) is up +28%, S&amp;P Materials (XLB) +21%, and S&amp;P Industrials (XLI) +18%
All cyclical sectors are now in positive territory sentiment-wise, with Consumer Discretionary and Financials sentiment now looking quite extended at multi-STDEV readings
Industrials sector sentiment stood out as relatively depressed for months, but is breaking out of its range in the last 10 days
As we noted in our post on cyclicals sentiment last week (TMI Snapshot:  Cyclicals Sentiment Melts Up into Year-End, Impact Concentrated in Materials Sector), the rotation theme has been particularly strongly correlated to the Materials sector (metals in particular) and there is potentially room for laggard cyclicals - namely industrials - to catch up as recent sentiment readings imply 
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:  Revisiting Cyclical Sector Sentiment - Industrials Showing Signs of Life