Articlediamond2018

OLS versus quantile regression in extreme distributions

18 citations0/0 files storedContaduría y Administración

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Financial Markets and Investment Strategies Financial Analysis and Corporate Governance Advanced Statistical Methods and Models

Abstract

Financial data mostly have fat tail and an analyst is much concerned about the tail part. Most of the study in finance extensible uses linear regression but when it comes to tail analysis it becomes ineffective. So, the present study tries to address the same by using Quantile regression in the tail analysis to study the value effect in 10 portfolios formed from BSE 500 stocks based on P/B ratio. The study result clearly indicates that Quantile regression estimates give more comprehensive and vibrant picture of the unpredictable effect of the predictors on the response variables.

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References

1993Common risk factors in the returns on stocks and bonds 1997Modelling Extremal Events 1995Another Look at the Cross-Section of Expected Stock Returns 1993Beta and Return 2003Handbook of heavy tailed distributions in finance 1998The effect of school quality on student performance: A quantile regression approach 1997On The Robustness of Size and Book‐to‐Market in Cross‐Sectional Regressions 1977The Capital Asset Pricing Model and the Investment Horizon

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