Identifying asset price booms and busts with quantile regressions

Abstract

This paper presents a methodology for detecting asset price booms and busts using non-parametric quantile regressions. The method consists in estimating the distribution of real stock prices as a function of fundamental determinants of stock returns, namely real economic activity and real interest rates. It is shown that changes in fundamentals affect not only the location but also the shape of the conditional distribution of stock prices. Asset price booms and busts are identified as realizations on the tails of that distribution. Then we use several indicators to analyse the behaviour of money and credit around the boom and bust episodes.