Faculty
Science
Supervisor Name
Marcos Escobar-Anel
Keywords
financial modelling, linear regression
Description
Capturing the relation between excess returns and volatility can help making better decisions in the stock market in terms of portfolio allocation and assets risk management. This paper takes the data of a minute-by-minute series of S&P500 from January 2009 to January 2021 as the research object and explores the best structural representation for the excess return as a function of the volatility, for a well-known index. This is implemented via regression models for volatility and excess returns. The results reveal that there’s a structural break in the relationship between the excess return and volatility based on the sign of the excess return, the functional connection could be either linear, logarithmic or quadratic.
Acknowledgements
Thank you to Dr. Marcos Escobar-Anel, the Western USRI program, and the Faculty of Science for their help.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Document Type
Paper
Functional structure of excess return and volatility
Capturing the relation between excess returns and volatility can help making better decisions in the stock market in terms of portfolio allocation and assets risk management. This paper takes the data of a minute-by-minute series of S&P500 from January 2009 to January 2021 as the research object and explores the best structural representation for the excess return as a function of the volatility, for a well-known index. This is implemented via regression models for volatility and excess returns. The results reveal that there’s a structural break in the relationship between the excess return and volatility based on the sign of the excess return, the functional connection could be either linear, logarithmic or quadratic.