| Summary: | 博士 === 國立中央大學 === 物理學系 === 106 === We build an agent-based model of an order-driven market with double auction. At first, we start with the comparison of non-interaction agents with no strategies and the herding agents who submit market orders. The simulation results reproduce some stylized facts
such as fat-tailed distribution of volatility and volume imbalance. The herding effect is implemented by aggregation of agents who take market orders into opinion groups. The number of opinion groups in a simulation step is determined from previous volatilities of the
market as different agents compare the price change over different time intervals. Besides confirming that when herding is included the tail of the distribution of volatility is enhanced, we found several new results. First, the autocorrelation time of volatility is much shorter than the memory of most of the agents because limit orders have strong influence on the location
of best bid and best ask. Second, from the relation between bid-ask imbalance and price return we find that herding reduces the chance for a small imbalance to produce a large price change. We find that the relation between spread and volatility in our preliminary model
does not agree with empirical data, we think limit orders have strong effects on the stylized features. Next, we compare the effects of three mechanisms. Our first mechanism is opinion aggregation, i.e., herding of agents in response to price volatility in the market is studied.
The second mechanism is the way that limit orders placed by the agents are affected by the size of the spread in the limit order book. The third mechanism is the enhanced trading activities in the presence of large volatility.
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