Host: The Japanese Society for Artificial Intelligence
Name : The 38th Annual Conference of the Japanese Society for Artificial Intelligence
Number : 38
Location : [in Japanese]
Date : May 28, 2024 - May 31, 2024
Recent developments of machine learning techniques have made AI traders more prominent in financial markets, drawing attention to their market impact. We focus on the GARCH(1,1) model, a key financial time series model, to analyze the influence of AI traders. The GARCH model is the most common method for modeling conditional variance capable of replicating volatility clustering, but its micro-foundations have not yet been fully understood. We categorize market investors into noise traders, fundamental traders, and AI traders and construct the GARCH model with artificial markets using them. We explore how each group affects the GARCH model's parameters and examine the role of AI traders in market dynamics and volatility, using theoretical models and simulations.
