Volatility forecasting for low-volatility investing

Christian Conrad, Onno Kleen, Rasmus Lonn

Research output: Working paperPreprintAcademic

Abstract

Low-volatility investing often involves sorting and selecting stocks based on retrospective risk measures, for example, the historical standard deviation of returns. In this paper, we use the volatility forecasts from a wide spectrum of volatility models to sort and select stocks and estimate portfolio weights. Our portfolios are more closely aligned with the ex-post optimal portfolio and deliver large, significant economic gains compared to traditional benchmarks after transaction costs. Importantly, we find that choosing portfolio weights by optimally combining the volatility forecasts from the different models delivers the strongest forecast and financial performance in real-time.
Original languageEnglish
DOIs
Publication statusPublished - 1 Aug 2022

Bibliographical note

JEL Classification: C22, C55, C58, G11

Erasmus Sectorplan

  • Sectorplan SSH-Breed

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