IDEAS home Printed from https://ideas.repec.org/a/mbr/jmonec/v11y2016i1p1-13.html
   My bibliography  Save this article

The Impact of Asymmetric Risk on Expected Return

Author

Listed:
  • Davallou , Maryam

    (Shahid Beheshti University)

  • Sadrynia , Mostafa

    (University of Economic Science)

Abstract

The main goal of the present study is testing asymmetric risk pricing and comparing it with pricing of traditional risk measures in Tehran Stock Market. Accordingly, a sample consisting of 101 companies listed in Tehran Stock Market during 2002-2013 went under investigation. In order to test asymmetric risk pricing, regression model of panel data was applied. The results revealed a positive and significant relationship between traditional measures (Standard Deviation and Semi Standard Deviation) and asymmetric risk measures (parametric VaR, HR risk, historical VaR, and historical HR) and expected return. Therefore, in addition to the significant correlation between risk and return, pricing model based on asymmetric risk and traditional risk was approved, too. Again, it was shown that controlling the effect of variables such as financial leverage, firm size, book-to-market ratio of equity (B/M) and liquidity, momentum and inverse is not able to change the direction of the relationship. Furthermore, the explanatory power of traditional and asymmetric risk criteria are the same.

Suggested Citation

  • Davallou , Maryam & Sadrynia , Mostafa, 2016. "The Impact of Asymmetric Risk on Expected Return," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 11(1), pages 1-13, January.
    • Handle: RePEc:mbr:jmonec:v:11:y:2016:i:1:p:1-13
    as

    Download full text from publisher

    File URL: http://jme.mbri.ac.ir/article-1-253-en.pdf
    Download Restriction: no
    File URL: http://jme.mbri.ac.ir/article-1-253-en.html
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. Ang, Andrew & Hodrick, Robert J. & Xing, Yuhang & Zhang, Xiaoyan, 2009. "High idiosyncratic volatility and low returns: International and further U.S. evidence," Journal of Financial Economics, Elsevier, vol. 91(1), pages 1-23, January.
    3. Javed Iqbal & Sara Azher, 2014. "Value-at-Risk and Expected Stock Returns: Evidence from Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 19(2), pages 71-100, July-Dec.
    4. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    5. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    2. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    3. Long, Huaigang & Zhu, Yanjian & Chen, Lifang & Jiang, Yuexiang, 2019. "Tail risk and expected stock returns around the world," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 162-178.
    4. Lee, Kuan-Hui & Yang, Cheol-Won, 2022. "The world price of tail risk," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    5. Jang, Jeewon, 2017. "Stock return anomalies and individual investors in the Korean stock market," Pacific-Basin Finance Journal, Elsevier, vol. 46(PA), pages 141-157.
    6. Blau, Benjamin M. & Griffith, Todd G. & Whitby, Ryan J., 2018. "The maximum bid-ask spread," Journal of Financial Markets, Elsevier, vol. 41(C), pages 1-16.
    7. Ayadi, Mohamed A. & Cao, Xu & Lazrak, Skander & Wang, Yan, 2019. "Do idiosyncratic skewness and kurtosis really matter?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    8. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    9. 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.
    10. Guo, Hui & Qiu, Buhui, 2014. "Options-implied variance and future stock returns," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 93-113.
    11. Rossi, Francesco, 2011. "Risk components in UK cross-sectional equities: evidence of regimes and overstated parametric estimates," MPRA Paper 38682, University Library of Munich, Germany, revised 31 Mar 2012.
    12. Sati P. Bandyopadhyay & Alan Guoming Huang & Kevin Jialin Sun & Tony S. Wirjanto, 2017. "The return premiums to accruals quality," Review of Quantitative Finance and Accounting, Springer, vol. 48(1), pages 83-115, January.
    13. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    14. Kuntara Pukthuanthong-Le & Nuttawat Visaltanachoti, 2009. "Idiosyncratic volatility and stock returns: a cross country analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 19(16), pages 1269-1281.
    15. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.
    16. Calomiris, Charles W. & Love, Inessa & Martínez Pería, María Soledad, 2012. "Stock returns’ sensitivities to crisis shocks: Evidence from developed and emerging markets," Journal of International Money and Finance, Elsevier, vol. 31(4), pages 743-765.
    17. Cotter, John & Sullivan, Niall O' & Rossi, Francesco, 2015. "The conditional pricing of systematic and idiosyncratic risk in the UK equity market," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 184-193.
    18. 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.
    19. Yang, Nien-Tzu & Chu, Hsiang-Hui & Ko, Kuan-Cheng & Lee, Shiou-Wen, 2018. "Continuing overreaction and momentum in a market with price limits," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 56-71.
    20. Mu-Shun Wang, 2013. "Idiosyncratic Volatility and the Expected Stock Returns for Exploring the Relationship with Panel Threshold Regression," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(2), pages 113-129, May.

    More about this item

    Keywords

    Asymmetric risk; Traditional risk; Expected return;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mbr:jmonec:v:11:y:2016:i:1:p:1-13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: M. E. (email available below). General contact details of provider: https://edirc.repec.org/data/mbcbiir.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.