. Not just something that looks good on a chart. Not something that worked twice last month. Something that has been tested properly, across multiple markets, across time, and across real data.
For me, that foundation has been seasonal patterns, and the main reason is their consistency.
We have just completed the full back testing of all the 2025 seasonal patterns on our platform. The results were not based on opinions or visual observations. They were based on actual performance data
taken from the many thousands of seasonal patterns available on the platform last year.
We tested the performance of five seasonal models: the
5-year, 10-year, 20-year, all-years, and post-election patterns, and across three different levels of price-to-seasonal correlation:
no correlation filter, >50% correlation, and >70% correlation. This produced a total of 15 separate test combinations. The testing criteria was straightforward. We measured whether price finished positive between the start and end dates of bullish seasonal periods, or negative during bearish periods.
Entries were not optimised and no trade management was applied. The purpose of the test was purely
to measure the effectiveness of the seasonal dates identified by the seasonal software.
Out of the five seasonal patterns tested,
the most consistent across the board was the 20-year pattern with an overall success rate of 68%. This has been the case every year since the software was launched three years ago. The only exception was the US post-election pattern in two asset classes, where
major forex pairs achieved a 79% success rate and metals reached 75%. Even so, on average the 20-year pattern remained the strongest overall performer.
When we look at correlation, the results are equally clear.
Markets where price was aligned with the seasonal pattern performed significantly better than those with no correlation. The >70% correlation group produced slightly higher success rates than the >50% group, but the number of qualifying patterns dropped substantially.
Because of that trade-off between accuracy and sample size, our preference remains the >50% correlation filter. Both correlation groups outperformed the non-correlated patterns by a meaningful margin.
Using the strongest combination,
the 20-year seasonal pattern with >50% price correlation, there were 473 qualifying patterns in 2025.
Across those 473 patterns,
the overall success rate was 68%.
For context,
2024 delivered a 67% success rate and 2023 delivered 74%.
For the third consecutive year, the 20-year seasonal pattern has been the most successful benchmark.
That is precisely why it remains the default setting on our seasonal platform. It isn’t there by accident. It’s there because the data continues to justify it.
Many providers publish seasonal charts using varying lookback periods, 16 years here, 24 years there, often with no consistency and without any published back testing to demonstrate effectiveness. We take the opposite approach.
We test the patterns, we track outcomes, and we measure performance year after year.
When you are building a trading strategy, that consistency matters.
Looking deeper into the 2025 results, the asset class breakdown is equally revealing. The strongest performance came from stock indices,
which delivered an 84% success rate across the year. US sector ETFs followed closely at 83%. Metals came in at 69%, Forex at 67%, while Energy lagged significantly at only 50%, which pulled the overall average lower.
This is important. Seasonal trading is not just about knowing when markets tend to move. It is also about knowing which asset classes are currently responding best to their seasonal tendencies. If indices are delivering 84% seasonal alignment while energy is closer to 50%, capital allocation decisions become clearer. Our platform makes this visible through performance tracking and top-performing lists,
allowing traders to focus on markets that are not only moving, but moving in line with their seasonal character.
How Can We Use This Data to Build a Sustainable Trading Strategy?
Using the optimum seasonal combination outlined above helps you identify high-probability trading windows. Periods where the statistical edge is already in your favour. Your job then becomes building a watchlist of markets showing these characteristics, waiting for price confirmation, and applying sensible risk management when entering positions.
This is also where you can outperform the raw 68% success rate from the testing. The back test measures only whether price moved in the expected direction between seasonal dates.
In real trading, you can improve results further by entering at optimal points based on price behaviour rather than simply holding for the entire seasonal window.
Take Monster (MNST) last year as an example.
MNST showed a strong correlation (yellow line) with its 20-year seasonal pattern (orange pattern) throughout 2025 and was a very clean seasonal market to trade last year. Price action tracked closely with its historical average path, and that alignment tells you the seasonal foundation is intact. Markets behaving like this are exactly where your focus should be.
Now look at the price chart of MNST.
There were six optimal seasonal periods highlighted by our seasonal software (blue bars at the bottom of the seasonal chart). If we focus on the final two periods, Nov 19th to Dec 4th, and Dec 4th to Dec 26th, these represent two clear trading windows where you should be preparing for opportunities. It is important to remember that there is rarely just one possible entry. Entries should always be based on a method you are comfortable with and can repeat consistently.
There are a couple of approaches here that would make sense.
Possible entry No-1
First, we have the earnings gap on Nov 7th. Earnings events are generally something to avoid trading directly, so waiting for price to stabilise afterwards is sensible. Price then consolidated for five days inside the earnings range while pushing towards the upper end of that range, showing buyers remained in control. When price broke the high on Nov 17th, that provided one acceptable entry point. Note that this occurred two days before the official seasonal start date, but testing shows that optimal entries often appear up to seven days before or after seasonal windows begin, so you need to be alert early. This is a very tradeable setup. Although because price was already extended above the moving averages at the breakout point, I would personally prefer to enter on a smaller intra-day timeframe to maximise the return from whats left of the move.
Possible entry No-2
The second opportunity came as price retraced towards the 20 EMA (blue line) as price entered the second seasonal window on Dec 4th. Price again consolidated for several days before showing clear selling exhaustion followed by a bullish inside candle. This is the type of structure I generally prefer — price closer to the averages, not already overbought, tight consolidation, signs of sellers losing control, and buyers stepping back in. Breaking the seven-day range high at 74.40 provided the entry, and price then pushed nicely higher for seven days towards the end of the seasonal window, where a trailing stoploss would have taken you out around 76.80 for a nice 3% gain.
I wouldn't expect all traders to trade both of these set ups but rather have a preference for one of the other. This is completely normal and is important for every traders to understand what and where they trade so they can consistently repeat that entry.
Bringing your trading strategy together.
This example illustrates how seasonal patterns can act as a stable foundation for a complete trading strategy, when combined with sound technical entries and risk management.
- The seasonal data identifies when conditions are favourable.
- Technical analysis helps determine when to enter.
- Risk management controls downside when trades fail and also locks in profit.
The seasonal edge does not eliminate losing trades. Even a 68% success rate means losses occur. What it does is shift probabilities in your favour over a meaningful sample size.
For three consecutive years, the 20-year seasonal pattern has delivered the strongest results across hundreds of markets. The 2025 results, 68% success across 473 qualifying patterns, reinforce what we have already seen in 2024 and 2023.
Seasonal trading is not theory. It is measurable, testable, and repeatable.
If you want to build a sustainable trading strategy, start with something that has already proven itself. Use data to identify where the edge exists, apply a consistent entry model, and manage risk properly.
Build from what works. Then refine the execution.
That is how you create something sustainable.
Happy trading
Ray Gilmour
Founder & Senior analyst at Markets Made Clear.com