Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Sequential Monte Carlo Optimization for Index Tracking with Transaction Costs

Version 1 : Received: 14 March 2024 / Approved: 14 March 2024 / Online: 14 March 2024 (15:15:15 CET)

How to cite: Hamilton-Russell, L.; O’Callaghan, T.M.; Savin, D.; Schlögl, E. Sequential Monte Carlo Optimization for Index Tracking with Transaction Costs. Preprints 2024, 2024030859. https://doi.org/10.20944/preprints202403.0859.v1 Hamilton-Russell, L.; O’Callaghan, T.M.; Savin, D.; Schlögl, E. Sequential Monte Carlo Optimization for Index Tracking with Transaction Costs. Preprints 2024, 2024030859. https://doi.org/10.20944/preprints202403.0859.v1

Abstract

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

Keywords

index tracking; sequential Monte Carlo; transaction costs; portfolio management

Subject

Business, Economics and Management, Finance

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