Volatility forecasting for low-volatility investing

Christian Conrad, Onno Kleen and Rasmus Lönn

International Journal of Forecasting, 2026, vol. 42, issue 2, 570-586

Abstract: Low-volatility investing often involves sorting and selecting stocks based on retrospective risk measures, for example, the historical standard deviation of returns. In contrast, we employ volatility forecasts from various volatility models to sort, select, and estimate portfolio weights on the 500 largest US stocks. We find that exploiting a large set of time-series models delivers large, significant economic gains compared to traditional benchmarks. After accounting for transaction costs, a low-volatility portfolio based on volatility forecasts from a panel heterogeneous autoregression model and a portfolio based on forecast combinations perform best and can be easily implemented in real time.

Keywords: Forecast combinations; Forecast-based portfolios; HAR models; Low-volatility allocations; Volatility forecasting (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:42:y:2026:i:2:p:570-586

DOI: 10.1016/j.ijforecast.2025.08.006

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