2025/09/03 by Dimitrakopoulos, Stefanos, Abdelhakim Aknouche, Aknouche, Abdelhakim +1
Economics, Econometrics and Finance · #Financial Markets and Investment Strategies #Monetary Policy and Economic Impact #Capital Investment and Risk Analysis
paper · doi:10.57805/r00gbp20
We propose a new model for transaction data that accounts jointly for the time duration between transactions and for the discreteness of the intraday stock price changes. Duration is assumed to follow a stochastic conditional duration model, while price discreteness is captured by an autoregressive moving average ordinal-response model with stochastic volatility and time-varying parameters. The proposed model also allows for endogeneity of the trade durations as well as for leverage and in-mean effects. In a purely Bayesian framework we conduct a forecasting exercise using multiple high-frequency transaction data sets and show that the proposed model produces better point and density forecasts than competing models.