Publication Type

Master Thesis

Publication Date



There has been increasing research on the cross-sectional relation between stock return and volatility. Conclusions are, however, mixed, partially because volatility or variance is modeled or parameterized in various ways. This paper, by using the Jiang and Tian (2005)'s model-free method, estimates daily option implied volatility for all US individual stocks from 1996:01 to 2006:04, and then employs this information to extract monthly volatilities and their idiosyncratic parts for cross-sectional regression analyses. We follow the Fama and French (1992) cross-sectional regression procedure and show that each of the 4 monthly measures of change of total volatility, total volatility, expected idiosyncratic variance, and expected idiosyncratic volatility is a negative priced factor in the cross-sectional variation of stock returns. We also show that the negative correlation between return and total volatility or expected idiosyncratic variance or expected idiosyncratic volatility strengthens as leverage increases or credit rating worsens. However, leverage does not play a role in the relation between return and change of total volatility. Finally, responding to recent papers, we show that the investor sentiment does not have a significant impact on the cross- sectional relation between return and volatility.


idiosyncratic volatility discount, pricing, profitability, rate of return, stock price forecasting, stocks

Degree Awarded

MSc in Finance


Finance and Financial Management | Portfolio and Security Analysis


LIM, Kian Guan; TING, Christopher

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.