Good volatility, bad volatility, and the cross-section of stock returns at different investment horizons
|Author:||Mgr. Tony Ryan Hlali Sako, B.Eng.,|
|Year:||2018 - summer|
|Leaders:|| doc. PhDr. Jozef Baruník Ph.D.
|Work type:|| Masters
|Awards and prizes:|
|Abstract:||Abstract Starting with the assumption that diﬀerent investors have diﬀerent investment time preferences and diﬀerent risk tolerances within their given investment time-frames, this paper investigates the value of employing multiresolution analysis to model volatility and risk-pricing. In terms of estimation and fore- casting performance we were able to reduce by at least half the volatility fore- casting errors, with even better results at longer horizons. In regards to risk pricing we learn that extreme aggregate volatility (i.e. tail risk) is priced but regular volatility is not. Additionally we ﬁnd that whilst aggregate volatility is generally more important over the long-horizon, during periods of market turmoil it is much more signiﬁcant over the short-horizon. Finally we show that stocks with high sensitivity to aggregate volatility have lower subsequent returns supporting the idea that they become attractive as a hedge against market volatility. JEL Classiﬁcation C12, C13, C21, C22, C31, C32, C51, C52, C53 Keywords Realized Volatility, Wavelet, Long-Memory Models, Cross-Section, Volatility Forecast, High-Frequency Data Author’s e-mail tony firstname.lastname@example.org Supervisor’s e-mail email@example.com|