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View fusion vis-\`a-vis a Bayesian interpretation of Black-Litterman for portfolio allocation

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  • Trent Spears
  • Stefan Zohren
  • Stephen Roberts

Abstract

The Black-Litterman model extends the framework of the Markowitz Modern Portfolio Theory to incorporate investor views. We consider a case where multiple view estimates, including uncertainties, are given for the same underlying subset of assets at a point in time. This motivates our consideration of data fusion techniques for combining information from multiple sources. In particular, we consider consistency-based methods that yield fused view and uncertainty pairs; such methods are not common to the quantitative finance literature. We show a relevant, modern case of incorporating machine learning model-derived view and uncertainty estimates, and the impact on portfolio allocation, with an example subsuming Arbitrage Pricing Theory. Hence we show the value of the Black-Litterman model in combination with information fusion and artificial intelligence-grounded prediction methods.

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  • Trent Spears & Stefan Zohren & Stephen Roberts, 2023. "View fusion vis-\`a-vis a Bayesian interpretation of Black-Litterman for portfolio allocation," Papers 2301.13594, arXiv.org.
    • Handle: RePEc:arx:papers:2301.13594
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    References listed on IDEAS

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    1. Stefano Giglio & Bryan Kelly & Dacheng Xiu, 2022. "Factor Models, Machine Learning, and Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 14(1), pages 337-368, November.
    2. Nicolae Gârleanu & Lasse Heje Pedersen, 2013. "Dynamic Trading with Predictable Returns and Transaction Costs," Journal of Finance, American Finance Association, vol. 68(6), pages 2309-2340, December.
    3. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    4. Theis Ingerslev Jensen & Bryan T. Kelly & Semyon Malamud & Lasse Heje Pedersen, 2022. "Machine Learning and the Implementable Efficient Frontier," Swiss Finance Institute Research Paper Series 22-63, Swiss Finance Institute.
    5. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
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    1. Trent Spears & Stefan Zohren & Stephen Roberts, 2023. "On statistical arbitrage under a conditional factor model of equity returns," Papers 2309.02205, arXiv.org.

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