Common Cycles in Volatility and Cross Section of Stock Returns

Arbeitspapier

We study the relationship between conditional quantiles of returns and the long-, medium- and short-term volatility in a portfolio of financial assets. We argue that the combination of quantile panel regression and wavelet decomposition of the volatility time series provides us with new insights into the pricing of risk and increases the accuracy of our estimates of re-turn quantiles. Our results contribute to the literature on the risk-return relationship with an emphasis on portfolio management under various investment horizons. Moreover, the analytical framework that we introduce should be applicable to a wide range of problems outside of our research area.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IES Working Paper ; No. 19/2017

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Financial Econometrics ; Financial Forecasting and Simulation
• Subject: Return predictability ; Quantiles ; Wavelets ; Panel data

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Barunik, Jozef ; Kraicova, Lucie
• Event: Veröffentlichung
• (who): Charles University in Prague, Institute of Economic Studies (IES)
• (where): Prague
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/174212
• Last update: 10.03.2025, 11:42 AM CET