Which Time Zone Do Traders Earn the Most?

The same system, the same rules, the same strategy. But completely different results at different times. Have you ever thought: Could the reason for the system's failure be your codes, or could it be the time?

Although financial markets seem to be continuously open, they do not offer the same liquidity, player density, and volatility at every hour. Therefore, if you have not analyzed the profit-loss distribution of your system on an hourly basis, what you think is success may be coincidence.

Example:

Let's say a system has a 60% win rate based on the backtest result for a total of 1000 trades. Great. But when you break down these 1000 trades by hours, maybe only the time frame between the London opening and before New York produces a positive expectancy. During other hours, the system either struggles or loses money.

📊 Therefore, time-based filtering reveals the true efficiency of the system. Not only the transaction result but also "when it was acquired" is part of the system.

Technical Recommendation: Log each transaction data along with the timestamp.

🔹 Asia: 03:00–10:00
🔹 London: 10:00–16:30
🔹 New York Opening: 16:30–23:00
🔹 New York Close: 23:00–03:00

Extract the following metrics for each interval:

Win rate
Avg R:R
Expectancy
Drawdown profile
Compare these.

In an analysis conducted in 2023, the average R:R ratio of trades in the spot BTC/USDT pair during Asian hours was 1:1.2, while in the London–NY overlap, this ratio rises to 1:1.9.

So above all, it is not what the system "does" that matters, but "when it does" it.