Intelligent Portfolio Rebalancing

Introducing a statistical portfolio rebalancing test based on resampled portfolio optimization.

Resampled Portfolio Rebalancing distribution and test statistic based on marginal return / risk. Figure from the Portfolio Construction and Risk Management book.

Portfolio rebalancing is often handled in an ad hoc way, despite its crucial importance for any investment portfolio.

Chapter 6 of the Portfolio Construction and Risk Management book¹ introduces a new method for assessing the similarity between the current portfolio and a desired portfolio that we are considering rebalancing towards.

Hence, instead of just rebalancing at fixed frequencies, we can statistically assess how much our current portfolio deviates from the desired one and potentially rebalance at times that are favorable in terms of transaction costs, for example, as new money comes into the portfolio or execution is particularly cheap.

The new rebalancing method builds on the Resampled Portfolio Stacking² approach, which is also introduced in Chapter 6 of the Portfolio Construction and Risk Management book. Compared to Exposure Stacking, which was introduced by Kristensen and Vorobets (2024)³, Resampled Portfolio Stacking allows us to use other targets than the portfolio exposures. For example, we can use the marginal risk contributions, the marginal return contributions, or a ratio between the elements of the two vectors.

The benefit of the new method is that it allows us to incorporate differences in risk contributions, including complex diversification interactions for any investment risk measure.

The fundamental idea is to perform B resampled portfolio optimizations having the same characteristics as our target portfolio. This could, for example, be the same overall risk and tracking error targets in addition to the natural constraint of having the same investment restrictions.

The new rebalancing method is thoroughly described in the Portfolio Construction and Risk Management book, which you can get access to here⁴. The book also includes accompanying Python code with practical examples of how you can use the new rebalancing approach and much more related to Entropy Pooling and fully general CVaR optimization⁵.

1. Portfolio Construction and Risk Management Book Substack post: https://antonvorobets.substack.com/p/portfolio-construction-and-risk-management-book-91526e1c0c17

2. Portfolio Optimization and Parameter Uncertainty Substack post: https://antonvorobets.substack.com/p/portfolio-optimization-and-parameter

3. Portfolio Optimization and Parameter Uncertainty SSRN article: https://ssrn.com/abstract=4709317

4. Portfolio Construction and Risk Management book crowdfunding: https://igg.me/at/pcrm-book

5. Entropy Pooling and CVaR Portfolio Optimization in Python Substack post: https://antonvorobets.substack.com/p/entropy-pooling-and-cvar-portfolio-optimization-in-python-ffed736a8347