A0213
Title: Jump clustering, stock price efficiency and predictability of jumps in financial markets
Authors: Jian Chen - University of Reading (United Kingdom) [presenting]
Abstract: The focus is on the clustering behaviours of assets' return jumps modelled by a self/cross-exciting process embedded in a stochastic volatility model. Based on the model, we carry out two exercises. Firstly, we relate the jump clustering behaviours to information flows and propose a new measurement of stock price efficiency. We show the capability of our new measurement to capture the speed at which stock prices possess new information, especially at the firm-specific level. Secondly, we propose a forecasting framework for asset return jumps and assess their predictability. We sample latent states with a particle filter in the out-of-sample and perform one-step-ahead probabilistic predictions on upcoming jumps. We further develop a statistic based on predicted probabilities of positive and negative jumps and show its usefulness in forecasting returns. We conduct empirical studies in the US stock market, commodity futures markets, and foreign exchange markets.
