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Download PDF by Izumi K.: An Artificial Market Model of a Foreign Exchange Market

By Izumi K.

During this learn, we proposed a brand new method of foreign currency echange industry experiences, a man-made industry method. the unreal industry technique built-in fieldwork reports and multiagent versions with a view to clarify the micro and macro relation in markets.

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46 Chapter 5 Construction of a Multiagent Model In this chapter we propose a multiagent model of a foreign exchange market, based on the field data in chapter 4. 4, and describe the interaction based on GAs in our model. 1, the framework of the model is described. 2, the flow of the algorithm of the model is explained using an example. 1 Framework of the Model The multiagent model of a foreign exchange market in this study is named A GEnetic-algorithmic, Double Auction market SImulation in TOkyo Foreign exchange market.

12) Step 5: Adaptation In the proposed model, different agents have different prediction methods j (combinations of the weights wi,t ). After the rate determination, each agent improves his prediction method using other agents’ prediction. The model uses genetic algorithms to describe the interaction between agents in learning. Because the weights are also different for each week t, it is very important how they change in time. Each agent is assumed to change his way of 56 prediction in order to improve prediction.

As a result of analysis of these field data, we proposed some hypotheses about dealers’ behavior pattern: decision rules, learning rules, and interaction pattern. 2. Construction of a multiagent model: a multiagent model of the market is implemented based on the hypotheses. The minimal com30 ponent of the model is each rule which agents have. Each rule may change or interact with other rules the way the hypotheses describe. As a result of the dynamics of rules, the model simulate rate dynamics at the macro level.

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An Artificial Market Model of a Foreign Exchange Market by Izumi K.


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