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On Data-Driven Drawdown Control with Restart Mechanism in Trading
Conference paper   Open access

On Data-Driven Drawdown Control with Restart Mechanism in Trading

Chung-Han Hsieh
IFAC-PapersOnLine, Vol.56(2), pp.9324-9329
07/2023

Abstract

algorithmic trading;Control applications;drawdown control;financial engineering;stochastic systems;robustness Control and Systems Engineering

This paper extends the existing drawdown modulation control policy to include a novel restart mechanism for trading. It is known that the drawdown modulation policy guarantees the maximum percentage drawdown no larger than a prespecified drawdown limit for all time with probability one. However, when the prespecified limit is approaching in practice, such a modulation policy becomes a stop-loss order, which may miss the profitable followup opportunities, if any. Motivated by this, we add a data-driven restart mechanism into the drawdown modulation trading system to auto-tune the performance. We find that with the restart mechanism, our policy may achieve a superior trading performance to that without the restart, even with a nonzero transaction costs setting. To support our findings, some empirical studies using equity ETF and cryptocurrency with historical price data are provided.

url
https://doi.org/10.1016/j.ifacol.2023.10.219View
Published (Version of record) Open

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