FX Spot Trading and Risk Management from A Market Maker’s Perspective
Due to the rapid development of computing technology and faster growth of financial industry, Foreign Exchange high-frequency trading has become substantially more prominent to today's market players, especially to bankers and market makers. This research aims at introducing today's FX high-frequency trading structure and discussing how a market maker can effectively reduce downside risk when market faces a huge upward or downward stress. An Exponential Moving Average operator is introduced and implemented using a Matlab software for tick-by-tick data analysis. Simulation framework for market high-frequency data and client trading flow is also introduced and implemented using the Matlab software. Real-time P&L calculation is introduced and used to determine the performance of a proposed risk hedging strategy. On the other hand, due to the financial crisis we experienced in 2007, 2008, and 2009, we analyze the tail risk of foreign exchange market. Extreme Value Theory (EVT) has been applied to real EUR/USD data, which contains eight-year daily closing exchange rate. An extension of from EVT to Value-at-Risk (VaR) calculation is introduced. We also consider the volatility clustering issue in asset returns and demonstrate how GARCH model can be applied for VaR calculation. Lastly, we propose a method of using VaR as a high-frequency risk measure for risk hedging strategies during intra-day trading.
Cite this version of the work
Mu Yang (2011). FX Spot Trading and Risk Management from A Market Maker’s Perspective. UWSpace. http://hdl.handle.net/10012/6159