Statistical arbitrage and risk management at AFC Capital Limited (AFCCL)

Abstract

The global financial industry has evolved greatly in last three decades. Complex Financial engineering has led to innovation of a wide variety of financial instruments. Many of these evolved due to the necessity of hedging against unanticipated price fluctuations but speculation is a greater motive today. Being a financial institution AFC Capital Limited seeks to asses profitable investment strategies. Traders deploy quantitative methods to scan for active trading strategies. One of the widely used strategies include statistical arbitrage with proprietary modifications to suit for different markets worldwide. A significant part of every trade involves risk management. This paper seeks to develop active trading strategies based on arbitrage opportunities and managing risk with quantitative methods. A statistical arbitrage involves analyzing mispricing between instruments and exploit the discrepancy. We look at these opportunities from classic research examples to shed some light on the strategy. In the risk management part we look at GARCH and Artificial Neural Network methods to quantify possible risk. These models feature volatility forecast and enables a trader to spot the inherent risk present in those instruments.