Next Article in Journal
Asymmetric Realized Volatility Risk
Previous Article in Journal
International Diversification Versus Domestic Diversification: Mean-Variance Portfolio Optimization and Stochastic Dominance Approaches
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Refining Our Understanding of Beta through Quantile Regressions

W. A. Franke College of Business, Northern Arizona University/20 McConnell Dr., Flagstaff, AZ 86011-5066, USA
*
Author to whom correspondence should be addressed.
J. Risk Financ. Manag. 2014, 7(2), 67-79; https://doi.org/10.3390/jrfm7020067
Submission received: 24 December 2013 / Revised: 28 April 2014 / Accepted: 5 May 2014 / Published: 21 May 2014

Abstract

The Capital Asset Pricing Model (CAPM) has been a key theory in financial economics since the 1960s. One of its main contributions is to attempt to identify how the risk of a particular stock is related to the risk of the overall stock market using the risk measure Beta. If the relationship between an individual stock’s returns and the returns of the market exhibit heteroskedasticity, then the estimates of Beta for different quantiles of the relationship can be quite different. The behavioral ideas first proposed by Kahneman and Tversky (1979), which they called prospect theory, postulate that: (i) people exhibit “loss-aversion” in a gain frame; and (ii) people exhibit “risk-seeking” in a loss frame. If this is true, people could prefer lower Beta stocks after they have experienced a gain and higher Beta stocks after they have experienced a loss. Stocks that exhibit converging heteroskedasticity (22.2% of our sample) should be preferred by investors, and stocks that exhibit diverging heteroskedasticity (12.6% of our sample) should not be preferred. Investors may be able to benefit by choosing portfolios that are more closely aligned with their preferences.
Keywords: Beta; risk preferences; portfolio management; quantile regression; hetero-skedasticity Beta; risk preferences; portfolio management; quantile regression; hetero-skedasticity
Graphical Abstract

Share and Cite

MDPI and ACS Style

Atkins, A.B.; Ng, P.T. Refining Our Understanding of Beta through Quantile Regressions. J. Risk Financ. Manag. 2014, 7, 67-79. https://doi.org/10.3390/jrfm7020067

AMA Style

Atkins AB, Ng PT. Refining Our Understanding of Beta through Quantile Regressions. Journal of Risk and Financial Management. 2014; 7(2):67-79. https://doi.org/10.3390/jrfm7020067

Chicago/Turabian Style

Atkins, Allen B., and Pin T. Ng. 2014. "Refining Our Understanding of Beta through Quantile Regressions" Journal of Risk and Financial Management 7, no. 2: 67-79. https://doi.org/10.3390/jrfm7020067

APA Style

Atkins, A. B., & Ng, P. T. (2014). Refining Our Understanding of Beta through Quantile Regressions. Journal of Risk and Financial Management, 7(2), 67-79. https://doi.org/10.3390/jrfm7020067

Article Metrics

Back to TopTop