UWA Profiles and Research Repository (University of Western Australia) · 2009 · 33 citations · 0 references
BusinessEconomicsFinanceFinancial EconomicsInvestment ManagementQuantitative FinanceFinancial ForecastingFinancial MathematicsInvestmentInvestment TheoryMicroeconometricsRisk-return AnalysisInference For Quantile FunctionsInvestment Risk AnalysisQuantile DependenceQuantile RegressionQuantile Regression For Risk
Quantile regression is a very powerful tool for financial research and risk modelling, and we believe that it has further applications that can provide significant insights in empirical work in finance. This paper demonstrates its use on a sample of Australian stocks and shows that, while ordinary least squares regression is not effective in capturing the extreme values or the adverse losses evident in return distributions, these are captured by quantile regressions.(1)