Time Latency in High-Frequency Trading Within Cointegrated Financial Markets

This study conducts an empirical analysis of time latency in high-frequency trading (HFT) utilizing intraday data sourced from Bloomberg, particularly emphasizing the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and TAIEX Futures. Employing the vector error correction generalized autoregressive conditional heteroskedasticity (VEC GJR-GARCH) model, the research evaluates the congruence of assessment models with established financial theories across various time latency intervals. The results reveal that the 1-minute and 15-minute intervals are the most effective for capturing HFT dynamics within cointegrated financial markets. Furthermore, the findings support the efficient market hypothesis (EMH), underscoring the critical role of futures markets in influencing and leading spot prices, thus facilitating the process of price discovery.