In the following study I am going to present a short survey of the hedge fund industry its
regulation and the existent hedge fund strategies. Statistical arbitrage in particular is
explained in further detail and major performance measurement ratios are presented. In the
second part I am going to introduce a semi-variance model for statistical arbitrage. The model
is compared to the standard Garch model which is often used in daily option trading derivate
pricing and risk management. As investment returns are not equally distributed over time
sources for statistical arbitrage occur. The semi-variance model takes skewness into account
and provides higher returns at lower volatility than the Garch model. The concept is aimed to
be a synopsis of mean reversion and chart pattern detection. The computer model is generated
with respect to Brownian motion and technical analysis and provides significant returns to the
investment. While the market efficiency hypothesis states the impossibility of long-term
arbitrage opportunities market anomalies outstand significantly. Connecting both elements
creates a profitable trading system. The combination of both approaches delivers a sensible
hedge fund concept. The out-of-sample backtest verifies out-performance and implies the need
for further research in the area of higher moment CAPM and additional market timing strategies
as sources of statistical arbitrage.
