2014/04/08 by Maciej Kostrzewski, Kostrzewski, Maciej
Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Economics and business #Financial Risk and Volatility Modeling #Methodology (stat.ME) #Statistical Finance (q-fin.ST) #Stochastic processes and financial applications
paper · pdf · doi:10.48550/arxiv.1404.2050
openalex publication_date 2014/04/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
News might trigger jump arrivals in financial time series. The "bad" and "good" news seems to have distinct impact. In the research, a double exponential jump distribution is applied to model downward and upward jumps. Bayesian double exponential jump-diffusion model is proposed. Theorems stated in the paper enable estimation of the model's parameters, detection of jumps and analysis of jump frequency. The methodology, founded upon the idea of latent variables, is illustrated with two empirical studies, employing both simulated and real-world data (the KGHM index). News might trigger jump arrivals in financial time series. The "bad" and "good" news seems to have distinct impact. In the research, a double exponential jump distribution is applied to model downward and upward jumps. Bayesian double exponential jump-diffusion model is proposed. Theorems stated in the paper enable estimation of the model's parameters, detection of jumps and analysis of jump frequency. The methodology, founded upon the idea of latent variables, is illustrated with two empirical studies, employing both simulated and real-world data (the KGHM index).