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Directionally Correct Views in Portfolio Optimization

Author

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  • Ojas Kumar
  • Sreejit Dey
  • Sarvesh Ravichandran Iyer
  • Sandeep Juneja

Abstract

Portfolio optimization techniques often use historical data to estimate parameters for Markowitz-type or ML models. Effective allocation requires a way to align the available data with conditions expected over the investment horizon. Inspired by the Black-Litterman framework, we ask whether incorporating expert views leads to better portfolio allocations. In a simple Markowitz setting, we show that even a small amount of directionally correct information can materially improve investment decisions. We also discuss how expert views can be incorporated in end-to-end portfolio models using entropy-based ideas. Somewhat surprisingly, our empirical results indicate that simpler Markowitz-type model perform as well as an end-to-end model, once directionally correct experts are incorporated.

Suggested Citation

  • Ojas Kumar & Sreejit Dey & Sarvesh Ravichandran Iyer & Sandeep Juneja, 2026. "Directionally Correct Views in Portfolio Optimization," Papers 2610.31074, arXiv.org.
    • Handle: RePEc:arx:papers:2610.31074
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    File URL: https://arxiv.org/pdf/2610.31074
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