ABSTRACT
This chapter discusses certain important quantile regression applications in finance. It provides left tail measures and risk management based on quantile regression. The chapter examines the importance of upper quantile information in financial markets. It presents quantile regression applications in portfolio allocation. Quantile regression provides a convenient way of estimating the conditional distribution. In addition to directly estimating the conditional distributions, quantile regression based methods provide an important complementary way to study the relationship between variables in financial markets. Distributional or quantile dependence is a well-known empirical feature in finance, and there is a large literature in finance on the study of directional predictability in stock prices. Left tail quantiles and expected values of the left tail distribution are easily interpretable measures of risk that summarize information regarding the distribution of potential losses. Quantile regression has important applications in portfolio construction.
