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Rebalancing with transaction costs: theory, simulations, and actual data

Author

Listed:
  • Rim Bernoussi

    (Cronos Finance)

  • Michael Rockinger

    (University of Lausanne)

Abstract

In the absence of transaction costs and the presence of independent returns, a buy-and-hold strategy theoretically generates higher expected returns than a fixed-weight strategy, where the portfolio weights are regularly readjusted/rebalanced to some initial level. This higher expected return comes with higher volatility. The resulting trade-off leads to different rankings of the Sharpe ratio depending on the statistical moments of the assets. We also focus on Maximum Drawdown. We theoretically discuss causes affecting the ranking of the Sharpe ratio, and we introduce an easy-to-implement methodology to deal with proportional transaction costs. Under transaction costs, the buy-and-hold strategy as the cheaper approach should be the winner. In various simulation experiments, we investigate the relevance of transaction costs on rebalancing strategies. Eventually, we consider several realistic portfolios with a risk-free asset, bonds, stock indices, commodities and real estate that allow us to demonstrate that in practice rebalancing has value.

Suggested Citation

  • Rim Bernoussi & Michael Rockinger, 2023. "Rebalancing with transaction costs: theory, simulations, and actual data," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(2), pages 121-160, June.
  • Handle: RePEc:kap:fmktpm:v:37:y:2023:i:2:d:10.1007_s11408-022-00419-6
    DOI: 10.1007/s11408-022-00419-6
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    More about this item

    Keywords

    Portfolio rebalancing; Fixed-weight; Portfolio allocation; Buy-and-hold; Transaction costs;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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