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Explaining the Low-Volatility Anomaly with Adaptive Factor Selection

Article arXiv papers · Author: Robert A. Jarrow et al.
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Summary

The paper offers a factor-based explanation for the low-volatility anomaly. It applies an Adaptive Multi-Factor model, estimated with the Groupwise Interpretable Basis Selection algorithm, to identify basis assets associated with low- and high-volatility portfolios.

The reported portfolios load on substantially different factors, leading the authors to argue that volatility is connected to existing risk exposures rather than acting as an independent risk. They attribute the low-volatility portfolio's outperformance to the equilibrium performance of its factor exposures. The paper also reports that its adaptive model outperforms the Fama-French five-factor model in and out of sample. The provided description does not specify the data, sample period, model details, or performance measures, so those claims cannot be assessed from this summary alone.

Key ideas

  • The study uses an adaptive multi-factor model to explain low- and high-volatility portfolio returns.
  • Groupwise Interpretable Basis Selection identifies basis assets related to those portfolios.
  • The portfolios' different factor loadings support an explanation based on existing risk exposures.
  • The authors report better in-sample and out-of-sample performance than the Fama-French five-factor model.
  • The supplied description omits data details and performance metrics.

Tags

EquitiesVolatilityFactor investingPortfolio construction
Full text
# The Low-volatility Anomaly and the Adaptive Multi-Factor Model


# The Low-volatility Anomaly and the Adaptive Multi-Factor Model









The paper provides a new explanation of the low-volatility anomaly. We use the Adaptive Multi-Factor (AMF) model estimated by the Groupwise Interpretable Basis Selection (GIBS) algorithm to find those basis assets significantly related to low and high volatility portfolios. These two portfolios load on very different factors, indicating that volatility is not an independent risk, but that it's related to existing risk factors. The out-performance of the low-volatility portfolio is due to the (equilibrium) performance of these loaded risk factors. The AMF model outperforms the Fama-French 5-factor model both in-sample and out-of-sample.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.