Forecasting Intraday Value-at-Risk Based on ACD Model in Chinese Stock Market

It is one of die challenging topics to measure the risk of intraday trading activity based on high frequency data in risk management. From the perspective of real-time transactions, this paper uses the tick-by tick data of Shenzhen Development Bank A share in China stock market to study the risk measurement. for the irregular trading data based on the Autoregressive Conditional Duration (ACD) model of price duration. The instantaneous conditional volatility is estimated by using intraday irregular volatility model, which is applied to forecast the irregularly spaced intraday Value-at-Risk (ISIVaR) and carry out the back testing. The empirical results show that the ISIVaR model is good for forecasting the maximum losses in the different. probability of loss.