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

TL;DR
SmartDCA is an improved investment strategy that adjusts asset purchases based on market prices, outperforming traditional DCA through rigorous mathematical analysis and extensive numerical testing on stock and cryptocurrency data.
Contribution
This paper introduces SmartDCA and its variants, providing the first rigorous mathematical proof of its superiority over traditional DCA, including bounded versions using novel mean definitions.
Findings
SmartDCA outperforms DCA in long-term returns across multiple scenarios.
Higher $ ho$ values in $ ho$-SmartDCA enhance performance.
Bounded SmartDCA maintains superiority while controlling investment size.
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 -SmartDCA, where the invested amount is raised to the power of . We demonstrate that higher values of lead to enhanced performance. However, this approach may result in unbounded investments. To address this concern, we introduce a bounded version of SmartDCA, taking…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEconomic theories and models · Financial Markets and Investment Strategies · Stochastic processes and financial applications
