This study conducts a high-frequency technical analysis of individual stocks listed on the Tokyo Stock Exchange. We propose novel technical rules that derive the timing of trades according to traditional systemic risks—such as shock-propagation, quote-stuffing, and tail risks—measured by...

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...

Our study investigates traders’ order submission strategies with varying market conditions under information asymmetry. It examines how a reduction in tick size affects informed traders’ order choices in response to changes in market conditions and subsequently influences the information...

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...