A multi-factor model of heterogeneous traders in a dynamic stock market

This study develops an agent-based computational stock market model in which each trader’s buying and selling decisions are endogenously determined by multiple factors: namely, firm profitability, past stock price movement, and imitation of other traders. Each trader can switch from being a buyer to a seller, and vice versa, depending on market conditions. Simulation findings imply liquidity in the stock market decreases as more traders try to behave in a similar way to other traders. Stock return volatility is increasing in memory length when the information set of a trader includes only the fundamental of stock. On the other hand, when all traders consider only the past stock price movement, stock prices undergo boom and bust cycles with the occasional no-trade states. Furthermore, when traders consider three factors equally, the stock return is characterized by more pronounced fat-tail property and lower volatility.