2019/12/20 by N. Modarresi, Modarresi, N., Saeid Rezakhah +3
Economics, Econometrics and Finance · Mathematics · #60G51 #60H10 #62M09 #62M10 #FOS: Mathematics #Financial Risk and Volatility Modeling #Probability (math.PR) #Stochastic processes and financial applications #Stochastic processes and statistical mechanics
paper · pdf · doi:10.48550/arxiv.1912.10083
openalex publication_date 2019/12/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Continuous-time autoregressive moving average (CARMA) process driven by simple semi-Lévy process has periodically correlated property with many potential application in finance. In this paper, we study on the estimation of the parameters of the simple semi-Lévy CARMA (SSLCARMA) process based on the Kalman recursion technique. We implement this method in conjunction with the state-space representation of the associated process. The accuracy of estimation procedure is assessed in a simulated study. We fit a SSLCARMA(2,1) process to intraday realized volatility of Dow Jones Industrial Average data. Finally, We show that this process provides better in-sample forecasts of these data than the Lévy driven CARMA process after de-seasonalized them.