Statistical Arbitrage for Crypto Currencies

Developed a pairs trading reversal strategy across 100 cryptocurrencies, achieving a 1.89 backtested Sharpe ratio (net) and strong alpha generation.
Cleaned and processed intraday pricing data for 300 cryptocurrencies from 2018-2024.
Utilized correlationand cointegration analysis to identify highly correlated pairs, constructing trading signals based on residual returns from linear regression.
Also, developed Cross-sectional and Time-Series Momentum strategies for the same, with a 1.43 backtested Sharpe ratio (net).
Combined all of the strategies based on their volatilities to generate a combined strategy with a back tested SR of 1.6+ and IR of 0.9.
Additionally also replicated Deep Learning for Statistical Arbitrage on crypocurrencies which helped in obtaining a Sharpe Ratio of 1.67, high-out-of-sample mean returns and also helped in lowering the transaction costs by 17%.