MODELING THE HIGH-FREQUENCY FX MARKET: AN AGENT-BASED APPROACH

Authored by Edward Tsang, Monira Aloud, Maria Fasli, Alexander Dupuis, Richard Olsen

Date Published: 2017

Sponsors: No sponsors listed

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Model Documentation: Other Narrative Pseudocode

Model Code URLs: Model code not found

Abstract

The development of computational intelligence-based strategies for electronic markets has been the focus of intense research. To be able to design efficient and effective automated trading strategies, one first needs to understand the workings of the market, the strategies that traders use, and their interactions as well as the patterns emerging as a result of these interactions. In this article, we develop an agent-based model of the foreign exchange (FX) market, which is the market for the buying and selling of currencies. Our agent-based model of the FX market comprises heterogeneous trading agents that employ a strategy that identifies and responds to periodic patterns in the price time series. We use the agent-based model of the FX market to undertake a systematic exploration of its constituent elements and their impact on the stylized facts (statistical patterns) of transactions data. This enables us to identify a set of sufficient conditions that result in the emergence of the stylized facts similarly to the real market data, and formulate a model that closely approximates the stylized facts. We use a unique high-frequency data set of historical transactions data that enables us to run multiple simulation runs and validate our approach and draw comparisons and conclusions for each market setting.

Tags

agent-based simulation Agent-based modeling Simulations law stylized facts Financial-markets Artificial stock-market Seasonality Electronic markets Fx markets