SmartDCA superiority

Calvet, Emmanuel, Herranz-Celotti, Luca, Valimamode and Karim

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Abstract: Dollar-Cost Averaging (DCA) is a widely used technique to mitigate volatility in long-term investments of appreciating assets. However, the inefficiency of DCA arises from fixing the investment amount regardless of market conditions. In this paper, we present a more efficient approach that we name SmartDCA, which consists in adjusting asset purchases based on price levels. The simplicity of SmartDCA allows for rigorous mathematical analysis, enabling us to establish its superiority through the application of Cauchy-Schwartz inequality and Lehmer means. We further extend our analysis to what we refer to as $\rho$-SmartDCA, where the invested amount is raised to the power of $\rho$. We demonstrate that higher values of $\rho$ lead to enhanced performance. However, this approach may result in unbounded investments. To address this concern, we introduce a bounded version of SmartDCA, taking advantage of two novel mean definitions that we name quasi-Lehmer means. The bounded SmartDCA is specifically designed to retain its superiority to DCA. To support our claims, we provide rigorous mathematical proofs and conduct numerical analyses across various scenarios. The performance gain of different SmartDCA alternatives is compared against DCA using data from S\&P500 and Bitcoin. The results consistently demonstrate that all SmartDCA variations yield higher long-term investment returns compared to DCA.

Date: 2023-08
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