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2024 | OriginalPaper | Buchkapitel

Multi-period Portfolio Optimisation Using a Regime-Switching Predictive Framework

verfasst von : Piotr Pomorski, Denise Gorse

Erschienen in: New Perspectives and Paradigms in Applied Economics and Business

Verlag: Springer Nature Switzerland

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Abstract

Regime-switching poses both problems and opportunities for portfolio managers. If a switch in the behaviour of the markets is not quickly detected it can be a source of loss, since previous trading positions may be inappropriate in the new regime. However, if a regime-switch can be detected quickly, and especially if it can be predicted ahead of time, these changes in market behaviour can instead be a source of substantial profit. The work of this paper builds on two previous works by the authors, the first of these dealing with regime detection and the second, which is an extension of the first, with regime prediction. Specifically, this work uses our previous regime-prediction model (KMRF) within a framework of multi-period portfolio optimisation, achieved by model predictive control, (MPC), with the KMRF-derived return estimates accuracy-boosted by means of a novel use of a Kalman filter. The resulting proposed model, which we term the KMRF+MPC model, to reflect its constituent methodologies, is demonstrated to outperform industry-standard benchmarks, even though it is restricted, in order to be acceptable to the widest range of investors, to long-only positions.

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Fußnoten
1
https://​github.​com/​bukosabino/​ta. Last accessed 29 March 2023.
 
3
The exponential weighted moving average (EMA) of a quantity (e.g., a return) is calculated as \(EMA_{C_t} = C_t \times (\frac{2}{n+1}) + EMA_{C_{t-1}} \times [1 - (\frac{2}{n+1})]\), where \(C_t\) is the current value of the quantity and n is a moving time window, such as 10 days.
 
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Metadaten
Titel
Multi-period Portfolio Optimisation Using a Regime-Switching Predictive Framework
verfasst von
Piotr Pomorski
Denise Gorse
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-49951-7_1