This study investigates high-frequency herding behavior in TOPIX 100 index-listed stocks and its impact on stock prices over different time horizons around tick size reduction on the Tokyo Stock Exchange. Our results show that high-frequency herding exists, especially at very short time...

This paper explores a possible cause of persistence in stock return volatility. Artificial stock markets are examined with different learning mechanisms, i.e. imitative and experiential learning. The simulation result shows that an economy with imitative learning gives rise to persistence of...

Recent research has shown a variety of computational techniques to describe evolution in an artificial stock market. One can distinguish the techniques based on at which level the learning of agents is modeled. The previous literature describes learning at either individual or social level. The...

This paper introduces an order-driven market with heterogeneous investors, who submit limit or market orders according to their own trading rules. The trading rules are repeatedly updated via simple learning and adaptation of the investors. We analyze markets with and without learning and...

Recent empirical research has documented that the state of the limit order book influences stock investors' strategies. Investors place more aggressive orders when the same side of the order book is thicker, and less aggressive orders when it is thinner. We conjecture and demonstrate that this...

This paper conducts an intraday technical analysis of individual stocks listed on the Nikkei 225. In addition to the price-based technical rules popularly examined in the literature, we uniquely propose and statistically investigate technical rules that utilize information regarding (1) the...