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DMS, AE, DAA: methods and applications of adaptive time series model selection, ensemble, and financial evaluation

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  • Parley Ruogu Yang
  • Ryan Lucas

Abstract

We introduce three adaptive time series learning methods, called Dynamic Model Selection (DMS), Adaptive Ensemble (AE), and Dynamic Asset Allocation (DAA). The methods respectively handle model selection, ensembling, and contextual evaluation in financial time series. Empirically, we use the methods to forecast the returns of four key indices in the US market, incorporating information from the VIX and Yield curves. We present financial applications of the learning results, including fully-automated portfolios and dynamic hedging strategies. The strategies strongly outperform long-only benchmarks over our testing period, spanning from Q4 2015 to the end of 2021. The key outputs of the learning methods are interpreted during the 2020 market crash.

Suggested Citation

  • Parley Ruogu Yang & Ryan Lucas, 2021. "DMS, AE, DAA: methods and applications of adaptive time series model selection, ensemble, and financial evaluation," Papers 2110.11156, arXiv.org, revised Jul 2022.
    • Handle: RePEc:arx:papers:2110.11156
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    References listed on IDEAS

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    1. Eric Benhamou & David Saltiel & Beatrice Guez & Nicolas Paris, 2019. "Testing Sharpe ratio: luck or skill?," Papers 1905.08042, arXiv.org, revised May 2019.
    2. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, September.
    3. Justin Sirignano & Rama Cont, 2019. "Universal features of price formation in financial markets: perspectives from deep learning," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1449-1459, September.
    4. James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
    5. Pierangelo De Pace, 2013. "Gross Domestic Product Growth Predictions Through The Yield Spread: Time‐Variation And Structural Breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-24, January.
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