The Missing Piece? Stock Indices Could Be Your EA Portfolio's New Edge!

A beginner-friendly summary of the verification: “The Missing Piece? Stock Indices Could Be Your EA Portfolio’s New Edge!”.

Breakout entry example (XAUUSD daily, real data): buy when price breaks above the recent high.

Breakout entry example (XAUUSD daily, real data): buy when price breaks above the recent high.

What’s the idea?

We’re always on the hunt for trading strategies that don’t just make money, but also play nicely together. Imagine having a bunch of different investments, and when one zigs, another zags – that’s the power of diversification! For a long time, we’ve been trying to find a “true uncorrelated edge” within FX and gold markets, something that genuinely moves independently from our core strategies. And guess what? We finally found a strong candidate: stock market indices! The core idea here was to see if a simple trend-following strategy on major stock indices could offer a robust, profitable edge that was uncorrelated with our existing FX and gold strategies. If it worked, it could be a game-changer for building a more stable, higher-performing portfolio.

How I tested it

To put this idea to the test, I first gathered a massive amount of data. I pulled daily historical price data for six major global stock indices from Yahoo Finance, spanning from 1996 all the way to 2026 (yes, including future placeholders for consistency in our data setup!). The indices included were the US500 (S&P 500), US100 (Nasdaq 100), US30 (Dow Jones), DE40 (DAX), JP225 (Nikkei), and UK100 (FTSE 100). For this initial research, I focused only on daily data. This is an important point: we’re looking at big, overarching trends, not intraday wiggles. Intraday (M1) testing for these indices is definitely on the to-do list for future research, as indices can have significant gaps and rapid movements during the trading day. I then ran two main types of tests:

Index Trend-Following (Breakout Long) Strategy: This strategy is designed to “Go Long” (buy) when an index shows strong upward momentum, essentially riding the trend. We wanted to see if this simple approach could capture significant gains while managing risk.
Turnaround Tuesday Anomaly: I also tested a well-known short-term anomaly called “Turnaround Tuesday,” which suggests that markets tend to reverse direction on Tuesdays after Monday’s close. This was more of a sanity check to see if common short-term “edges” held up.

What happened?

The results from the index trend-following strategy were genuinely exciting – especially when compared to a simple “buy and hold” approach.

Index Trend-Following: A Breakthrough!

First, let’s talk about the big wins. The trend-following strategy on stock indices delivered some truly impressive results:

Massive Drawdown Reduction: A simple “buy and hold” approach for these indices over such a long period would have resulted in huge drawdowns (DD) – think stomach-churning drops of -50% to -83%! Our trend-following strategy slashed these drawdowns down to a much more manageable range of -3% to -8%. In other words, the strategy helped us stay in the market for the good times while largely avoiding the really painful crashes.
Consistent Profitability: Every single one of the six indices showed a Profit Factor (PF) greater than 1.0. A Profit Factor is a simple ratio of your gross profit to your gross loss; anything above 1.0 means you’re profitable. This consistency across all major indices is a strong sign!
High-Quality Edge: The quality of these results was far superior to what we typically see with FX strategies.
After some parameter improvements (tweaking the entry and exit points to allow for longer holding periods), the combined US3 indices (US500, US100, US30) showed a total profit of +54% with a maximum drawdown of only -7.0%.
The Profit Factor (PF) was an astounding 4.17. To put that in perspective, our best FX strategies usually hit around 1.3, and gold strategies around 1.4. A PF of 4.17 means that for every dollar this strategy lost, it made over four dollars in profit! That’s incredibly efficient.
The Sharpe Ratio was 0.76 and the Return-to-Drawdown (r/DD) ratio was 7.6. These metrics tell us how much return we’re getting for the risk we’re taking, and higher numbers are always better.
Crucially, even with different parameter variations, the Profit Factor consistently stayed between 2 and 4, indicating a very robust and reliable edge.

Turnaround Tuesday: No Edge Here

On the flip side, our test of the “Turnaround Tuesday” anomaly showed that not every popular market “trick” holds up. After 1285 trades, this strategy only managed a +1% profit with a PF of 1.01. This essentially means no real edge after accounting for trading costs. Short-term anomalies often turn out to be break-even propositions once you factor in transaction fees and slippage. It’s a good reminder that not all “market wisdom” translates into profitable trading.

The Uncorrelated Power: FX + Gold + Indices

This is where things got really exciting! We measured the daily correlation between our successful index trend strategy and our core FX and gold strategies. The results were fantastic:

Indices vs. Core FX: A correlation of just 0.16.
Indices vs. Gold: An even lower correlation of -0.03. In plain English, these numbers mean that the index trend strategy is almost completely uncorrelated with our FX and gold strategies! They march to the beat of different drums. This is precisely what we hoped for, as stock indices are a different asset class altogether, driven by different fundamental factors than currencies or commodities. To truly demonstrate the power of this uncorrelated edge, I combined our index strategy with our FX and gold strategies into a single portfolio (allocating 0.005% risk to each, from 2010-2026). The combined results were outstanding:
Total Profit: +85%
Maximum Drawdown: -8.7%
Profit Factor: 2.62
Sharpe Ratio: 0.91
Return-to-Drawdown Ratio: 9.9 Here’s the kicker: both the combined r/DD (9.9) and Sharpe Ratio (0.91) surpassed the best individual strategy’s performance (7.6 and 0.86, respectively). This is solid proof that uncorrelated diversification truly works! If we had simply added up the drawdowns of the individual strategies, we’d be looking at a combined -20%. But by combining them in an uncorrelated way, the portfolio drawdown was compressed to a mere -8.7%. It’s like having a team where each member has different strengths, and together they are far more resilient than any one person alone.

What I learned

This research marks a significant milestone for our project. We’ve been tirelessly searching for a “true uncorrelated edge” since our earlier studies (Research 20 and 22), something that could genuinely diversify our portfolio beyond the confines of FX and gold. We strongly suspected that such an edge wouldn’t be found within the price movements of FX or gold themselves, but rather in a completely different asset class – and we were right! Stock market indices provide that genuine uncorrelated edge. This discovery opens up a realistic and powerful path to:

Bundle high-quality trading streams: We can now combine profitable strategies from different asset classes.
Increase leverage within our drawdown budget: Because the strategies are uncorrelated, they don’t all suffer at the same time. This allows us to take on more overall risk (and thus aim for higher returns) for the same level of portfolio drawdown.
Boost monthly profits: This is the first verifiable route we’ve found that could potentially push our monthly profit targets beyond the “ceiling” of around 0.5% per month that we often encounter when sticking to a single asset class. This isn’t just a marginal improvement; it’s a fundamental shift in how we can approach portfolio construction and risk management. It means building a more robust and potentially more profitable trading system.

The Road Ahead

While these results are incredibly promising, there’s always more work to do before integrating this into a live trading system. Here are the key next steps:

Intraday Risk Validation: We need to acquire M1 (one-minute) index data and rigorously test the strategy for intraday risk. Stock indices can experience significant price gaps and large, rapid fluctuations, so it’s crucial to confirm that our strategy can handle these dynamics without hitting any proprietary daily drawdown limits.
Forward Testing: The parameters we’ve optimized need to be put through forward testing (testing on new, unseen data) to confirm their robustness over time.
Broker & Cost Confirmation: We need to verify the exact CFD (Contract for Difference) specifications and trading costs with real brokers. It’s great to see that some brokers, like Fintokei, already offer major indices like US30, USTEC (US100), and DE40.
Full System Integration: Finally, we’ll integrate this index “sleeve” into our overall trading system and run comprehensive Monte Carlo simulations to re-evaluate the entire portfolio’s performance and risk profile. The journey continues, but with this discovery, we’ve taken a massive leap forward in building truly diversified and resilient algorithmic trading strategies!

How this connects

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

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