DYNAMIC PREDICTOR SELECTION AND ORDER SPLITTING IN A LIMIT ORDER MARKET
DYNAMIC PREDICTOR SELECTION AND ORDER SPLITTING IN A LIMIT ORDER MARKET
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DOI：
10.1017/s136510051700044x
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发表时间：
2017-08
影响因子：
0.9
通讯作者：
Ryuichi Yamamoto
中科院分区：
文献类型：
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作者：
Ryuichi Yamamoto
最近的实证研究已经证明了股票市场的集群式波动和收益分布的肥尾，但随着时间的推移，收益是不相关的。某些基于主体的理论模型试图从投资者的分序或动态切换策略的角度来解释实证特征，这两种策略都是实际股票投资者经常使用的。然而，很少有理论研究对模型中的行为假设进行区分，并比较假设对经验特征的影响。研究也没有同时复制市场微观结构的收益特征和经验特征，如订单选择模式。本研究构建了一个人为的限价单市场，在这个市场中，投资者将订单分成小块，或者随着时间的推移交替使用基本面和趋势跟踪预测指标。我们证明，一方面，具有订单分裂和动态预测器选择策略的市场可以独立地复制具有接近零回报自相关性的聚类波动率和肥尾。然而，我们也表明，在这两种类型的经济体中，秩序选择的模式与之前某些实证研究中发现的模式并不匹配。因此，我们得出结论，在现实中，这两种策略可以产生经验回报特征，但投资者也可能在实际股票市场中使用其他策略。我们还证明，随着市场中交易者数量的增加，这两种策略对波动性持久性的影响往往更大；这一发现表明，对于资本存量较大的实证现象，分序策略和动态预测器选择更为重要。
Recent empirical research has documented the clustered volatility and fat tails of return distribution in stock markets, yet returns are uncorrelated over time. Certain agent-based theoretical models attempt to explain the empirical features in terms of investors' order-splitting or dynamic switching strategies, both of which are frequently used by actual stock investors. However, little theoretical research has discriminated among the behavioral assumptions within a model and compared the impacts of the assumptions on the empirical features. Nor has the research simultaneously replicated the return features and empirical features on market microstructure, such as patterns of order choice. This study constructs an artificial limit order market in which investors split orders into small pieces or use fundamental and trend-following predictors interchangeably over time. We demonstrate that, on one hand, the market that features strategies with order splitting and dynamic predictor selection can independently replicate clustered volatility and fat tails with near-zero return autocorrelations. However, we also show that patterns of order choice do not match those found in certain previous empirical studies in both types of economies. Thus, we conclude that, in reality, the two strategies can work to generate the empirical return features but that investors may also use other strategies in actual stock markets. We also demonstrate that the impact of both strategies on the volatility persistence tends to be greater as the number of traders increases in the market; this finding implies that the order-splitting strategy and dynamic predictor selection are more crucial for the empirical phenomena pertaining to larger capital stocks.