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#6 – Volatility Effect in Stocks – Long-Short Version

Authors: Driessen, Kuiper, Beilo

Title: Does Interest Rate Exposure Explain the Low Volatility Anomaly?

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2831157

Abstract:

We show that part of the outperformance of low volatility stocks can be explained by a premium for interest rate exposure. Low volatile portfolios have a positive exposure to interest rates, whereas the more volatile stocks have a negative exposure. Incorporating an interest rate premium explains part of the anomaly. Depending on the methodology chosen the reduction of unexplained excess return is between 20% and 80%. Our results provide evidence that interest rate risk is priced differently in the bond and equity market. Our results imply a strong implicit exposure of low volatility portfolios to bonds.

Notable quotations from the academic research paper:

"A relation between the low volatility anomaly and government bonds makes sense if volatility is thought of as an indicator of how far equity is removed from bonds in the capital structure. In this study our main finding is that the outperformance of low volatility stocks can be explained by differences in interest rate exposure. We find that low volatility portfolios have more exposure to this risk. Our results imply a strong implicit exposure to interest rate risk of low volatility portfolios. We estimate that the duration of the lowest volatility decile corresponds to a 30% weight to bonds. The duration of the highest decile corresponds to a short position of 100% short bonds.

Because of the differences in exposure, the risk premium that we estimate explains part of the excess return of a long short portfolio. We find a monthly compensation of interest rate risk in equities of 0.91%, with a standard error of 0.20%. The differences in interest rate exposure combined with the large estimated risk premium, results in a significantly reduced mispricing of low volatility stocks. We find these results to be robust for taking into account the time variance of the interest rate exposure.

For our study we use ten portfolios over the period from July 1963 to December 2014, defined by sorts on residual variance of individual US stocks using the Fama French 3 factor model. In section 3 we elaborate further on this. We define an interest rate factor as the return of an equal weight portfolio consisting of US government bonds with various maturities. In order to estimate the interest rate exposure we run time series regressions. Fama MacBeth regressions are employed to estimate the premium for the interest rate exposure. Combined these two enable us to evaluate the impact of this effect on the unexpected excess return of the long short portfolio. We use several different estimations of the premium in order to test the robustness of our findings."

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