Over the last 15 years, the economy of India has boomed, and it has been reflected in the NIFTY index. The NIFTY has grown 7x since 1998 as the country has grown its exports. According to the UN one of the primary exports of India are high-value services which contribute 30% to their GDP. We hypothesized that as the strength of the NIFTY grew, the strength of the currency would follow as it is a primarily export economy. 

As the INR strengthens, the ratio to USD falls, making it an almost ideally inversely correlated asset. We first tested this hypothesis by treating the USDINR FX pair as a hedge against the NIFTY but found periods where they were positively correlated and the hedge did not work. Pivoting slightly, we experimented with rotating the portfolio holdings to focus on the peak-performing asset. We used a fixed rolling window to determine the peak performance and then swapped our holdings to focus on that asset. 

We used the QuantConnect LEAN 2.0 backtesting engine to import financial data from any source to run our analysis. The backtests were conducted over a 16-year period and were completed in 5-10 seconds. We saw phenomenal performance due to the strongly trending nature of the NIFTY and USDINR, achieving a Sharpe Ratio achieving 1.3 vs the NIFTY 0.7, and 42x returns vs 7x of the NIFTY. To test the resilience of the strategy, we experimented with the rolling window period to determine if this was critical to the success of the strategy. We used a rotating window from 3 days up to a 30-day window to optimize the variable for the best performance: 

The resulting Sharpe Ratio is fairly robust regardless of the precise value of the rotating window period. We believe there are many potential future improvements to the strategy to be explored, such as using a dynamically determined rolling window to avoid curve fitting. You could also experiment with different portfolios of inversely correlated assets to pick the best basket of assets.