The first genuinely uncorrelated return stream I found

Stock indices are the first genuine non-correlated diversifier I have found for my trading portfolio. While I have spent years searching for an edge within the price action of FX and gold, the true breakthrough came from moving into a different asset class entirely. I expanded my research dataset to include daily price history from 1996 to 2026 for six major global indices, including the US500, US100, US30, DE40, JP225, and UK100. By applying a long-trend breakout strategy, I found that the massive drawdowns typically associated with buy-and-hold investing (which range from -50% to -83%) were compressed to a range of -3% to -8%. Every index tested showed a profit factor (PF) greater than 1, meaning the gross profit consistently exceeded the gross loss.

Performance Comparison

When comparing the performance of the trend strategy on US indices, the results were significantly more stable than anything I have observed in FX or gold markets.

The Power of Non-Correlation

The most significant finding is that stock indices are almost entirely uncorrelated with my existing assets. The daily correlation between index trends and my core FX strategies is 0.16, and it is -0.03 against gold. Because they are distinct asset classes, they do not move in lockstep. When I combined these indices with my FX and gold strategies (each at a 0.005 risk per trade from 2010 to 2026), the portfolio performance improved significantly:

• Total Return: +85%
• Drawdown (DD): -8.7%
• Profit Factor (PF): 2.62
• Sharpe Ratio: 0.91
• Return/DD Ratio: 9.9 This is the definition of effective diversification. The combined Return/DD ratio of 9.9 and Sharpe ratio of 0.91 outperform the best individual asset’s metrics. Most importantly, the sum of individual drawdowns would have been -20%, but the non-correlated nature of the indices compressed that total drawdown to just -8.7%. This is the first realistic path I have found to break through the performance ceiling of approximately 0.5% monthly return that I previously faced. Before I can move this into a live account, I have a few remaining tasks. I need to verify intraday risk using 1-minute (M1) index data to ensure the strategy does not violate prop firm daily drawdown limits due to market gaps. I also need to conduct forward testing on the index parameters, confirm CFD specifications and costs with my broker, and finally integrate this index sleeve into my main system to conduct a full Monte Carlo evaluation.

How this connects

This verification builds on earlier ones (what failed before and what I tried this time, comparisons between approaches).

• The long-only trend strategy I had written off came back at…
• Walk-forward testing erased most of my profits
• Is there an edge in scalping gold? I went looking

Code to reproduce

You can reproduce this with the following scripts (see repo).

• scripts/research/study_index_trend.py
• scripts/tools/fetch_index_data.py
• strategies/turnaround_tuesday.py