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Tracking the Low-Volatility Anomaly Across Behavioral Space

In: Finance and the Behavioral Prospect

Author

Listed:
  • James Ming Chen

    (Michigan State University)

Abstract

In his popular guide to asset allocation, neurologist-turned-financial-analyst William J. Bernstein offers a bit of jarring advice to investors: “Good companies are usually bad stocks; bad companies are usually good stocks.”1 Bernstein’s practical prescription stems from an academic insight: “Growth opportunities are usually the source of high betas.”2 In principle, these high betas should impart higher risk and higher returns to growth stocks: “[B]ecause growth options tend to be most valuable in good times and have implicit leverage, which tends to increase beta, they contain a great deal of systematic risk.”3 Nevertheless, even though “growth options hinge upon future economic conditions and must be riskier than assets in place,” the historical pattern cuts in the opposite direction: “[G]rowth stocks earn lower average returns than value stocks.”4 From these observations flows Bernstein’s advice to the individual investor: “Favor a value approach in your stock and mutual fund choices.”5

Suggested Citation

  • James Ming Chen, 2016. "Tracking the Low-Volatility Anomaly Across Behavioral Space," Quantitative Perspectives on Behavioral Economics and Finance, in: Finance and the Behavioral Prospect, chapter 0, pages 73-92, Palgrave Macmillan.
  • Handle: RePEc:pal:qpochp:978-3-319-32711-2_4
    DOI: 10.1007/978-3-319-32711-2_4
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