Using Black-Litterman Reverse Optimization for Discrete Futures Positions

Summary

This opening installment considers how a trader with limited capital might allocate across futures when contracts cannot be traded fractionally. The author frames the challenge as a portfolio optimization problem: a small account cannot spread capital over as many markets as a large CTA, and large contract sizes can force forecast scaling or market exclusion. The proposed alternative uses a Black-Litterman-inspired process to convert an existing portfolio into implied expected returns, then optimize again under integer-position constraints.

The article explains the usual Black-Litterman sequence: infer equilibrium returns from portfolio weights and a covariance matrix, blend those returns with forecasts, and optimize to obtain adjusted weights. It then adapts the reverse-and-forward steps without changing expected returns, instead adding constraints such as whole-contract positions. The proposed workflow uses the trader’s existing position-generation output, covariance estimates, and a risk-aversion parameter. This is a conceptual proposal, not a demonstrated strategy: the post says implementation difficulties and testing will follow in later installments, and gives no performance evidence or completed method for resolving the practical issues.

Key ideas

• Limited capital and indivisible futures contracts restrict how broadly a small account can diversify.
• Black-Litterman derives implied returns by reversing an optimization based on portfolio weights and covariance.
• The proposed method turns existing desired positions into implied returns, then re-optimizes with integer constraints.
• The article describes an idea and workflow, but defers implementation challenges and empirical tests to later posts.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.