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Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle

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Listed author(s):
  • Robert F. Stambaugh
  • Jianfeng Yu
  • Yu Yuan

Abstract

Short selling, as compared to purchasing, faces greater risks and other potential impediments. This arbitrage asymmetry explains the negative relation between idiosyncratic volatility (IVOL) and average return. The IVOL effect is negative among overpriced stocks but positive among underpriced stocks, with mispricing determined by combining 11 return anomalies. The negative effect is stronger, consistent with asymmetry in risks and other impediments inhibiting arbitrageurs in exploiting overpricing. Aggregating across all stocks therefore yields a negative relation, explaining the IVOL puzzle. Further supporting our explanation is a negative relation over time between the IVOL effect and investor sentiment, especially among overpriced stocks.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18560.

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Date of creation: Nov 2012
Publication status: published as Robert F. Stambaugh & Jianfeng Yu & Yu Yuan, 2015. "Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle," Journal of Finance, American Finance Association, vol. 70(5), pages 1903-1948, October.
Handle: RePEc:nbr:nberwo:18560
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Find related papers by JEL classification:
  • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
  • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
  • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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Cited by:

  1. Wang, Huijun & Yan, Jinghua & Yu, Jianfeng, 2017. "Reference-dependent preferences and the risk–return trade-off," Journal of Financial Economics, Elsevier, vol. 123(2), pages 395-414.
  2. Azi Ben-Rephael & Bruce I. Carlin & Zhi Da & Ryan D. Israelsen, 2017. "Demand for Information and Asset Pricing," NBER Working Papers 23274, National Bureau of Economic Research, Inc.
  3. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2014. "The long of it: Odds that investor sentiment spuriously predicts anomaly returns," Journal of Financial Economics, Elsevier, vol. 114(3), pages 613-619.
  4. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
  5. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
  6. Robert F. Stambaugh & Yu Yuan, 2015. "Mispricing Factors," NBER Working Papers 21533, National Bureau of Economic Research, Inc.
  7. Itamar Drechsler & Qingyi Freda Drechsler, 2014. "The Shorting Premium and Asset Pricing Anomalies," NBER Working Papers 20282, National Bureau of Economic Research, Inc.
  8. Yang, Chunpeng & Zhou, Liyun, 2016. "Individual stock crowded trades, individual stock investor sentiment and excess returns," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 39-53.
  9. Liu, Qi & Lu, Lei & Sun, Bo & Yan, Hongjun, 2015. "A Model of Anomaly Discovery," International Finance Discussion Papers 1128, Board of Governors of the Federal Reserve System (U.S.).
  10. Coqueret, Guillaume, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 180-201.
  11. Robert F. Stambaugh, 2014. "Investment Noise and Trends," NBER Working Papers 20072, National Bureau of Economic Research, Inc.
  12. Cao, Jie & Han, Bing, 2016. "Idiosyncratic risk, costly arbitrage, and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 1-15.

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