Decoding Recessions with NLP: Harnessing Sentiment Analysis in Asset Allocation

Applying NLP-based recession sentiment to allocation to enhance returns, improve risk-adjusted performance, and reduce drawdowns.

New multiasset research from the Quantitative Solutions group applies NLP based recession sentiment to asset allocation and portfolio construction. Results show that sentiment aware approaches can enhance returns, improve risk adjusted performance, and reduce drawdowns versus conventional benchmark portfolios.  

 

RESEARCH HIGHLIGHTS:

  • Realtime recession sentiment complements traditional “hard” data, capturing shifts that can move markets.
  • Sentiment driven approaches adjust exposure at extremes, supporting both diversification and tactical responsiveness.
  • Back testing results suggest higher returns, improved Sharpe ratios, and smaller drawdowns versus broad equity benchmarks over long samples.
  • As overlays to balanced portfolios, sentiment signals improved risk adjusted outcomes and reduced drawdowns, without relying on leverage.
  • Incorporating real assets alongside sentiment-informed overlays increased resilience in inflationary environments.

4989735