The Dynamic Relationship Between Market Volatility and Dollar Cost Averaging Strategy Returns: An Empirical Investigation

Siyuan Sang (), Ru Bai () and Haibo Li ()
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Siyuan Sang: Beijing Tianrun New Energy Investment Co., Ltd, Algorithm Researcher
Ru Bai: Beijing Tianrun New Energy Investment Co., Ltd, Director of Power Trading
Haibo Li: Beijing Tianrun New Energy Investment Co., Ltd, Associate Director of Power Trading

A chapter in Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025), 2025, pp 72-79 from Springer

Abstract: Abstract This study empirically examines the performance of a Dollar-Cost Averaging (DCA) strategy under varying market volatility conditions. DCA, which involves investing a fixed sum at regular intervals, is popular for its risk-mitigation properties. However, its effectiveness, especially relative to lump-sum investing (B&H)—depends on market dynamics. Using Monte Carlo simulations to generate price paths based on geometric Brownian motion, we analyze DCA returns, volatility clustering, and transaction frequency. Results indicate that while DCA underperforms B&H in steadily rising markets, it can offer risk-adjusted advantages in highly volatile scenarios. The study also discusses practical implications for optimizing DCA by adjusting investment frequency and considering transaction costs.

Keywords: Dollar-Cost Averaging; Market Volatility; Investment Strategy; Monte Carlo Simulation; Geometric Brownian Motion (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-835-6_9

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DOI: 10.2991/978-94-6463-835-6_9

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