Investment Thesis

This volatility arbitrage strategy is based on the belief that markets are somewhat inefficient, particularly in terms of price deviations that arise from short-term volatility, which can create opportunities for mean-reversion trades. The strategy capitalizes on these inefficiencies, specifically by utilizing contrarian indicators such as Bollinger Bands, the Relative Strength Index (RSI), and trend-following signals. The algorithm assumes that prices will revert to the mean (the middle line of the Bollinger Bands) after significant deviations, especially when accompanied by oversold or overbought conditions indicated by RSI and confirmed by the trend filter. 

This strategy is active as it attempts to exploit these short-term mispricing through systematic, rule-based decision-making. Rather than simply passively tracking the market, it actively seeks to identify opportunities for profitable trades based on technical indicators that suggest a reversal in price direction. 

The strategy is long-short and market-neutral, as it simultaneously takes long positions when securities are oversold and short positions when they are overbought. By using both long and short trades, the algorithm aims to reduce market exposure and maintain a balanced portfolio that is less susceptible to overall market direction. The position sizes are controlled to manage risk, with a cap on portfolio exposure and a stop-loss mechanism to mitigate potential losses. 

In summary, this strategy operates under the assumption that markets are not perfectly efficient, and that short-term price movements create opportunities for traders to capitalize on mean-reversion tendencies. It is active, long-short, and market-neutral, with a clear focus on exploiting volatility while managing risk effectively. 

Author

Quant League Competitions

January 2025