Spend 24 hours chasing opportunities and you’ll lose — After marking five years by time zones, I realized the “downtime” when you don’t swing
When I was just starting demo trading, I seriously believed that“There are opportunities everywhere all day long.”So, morning, noon, or night, whenever I found a situation that seemed to be moving, I entered in as many as I could. The demo balance slowly fluctuated up and down, and honestly I felt like I was “doing reasonably well.”
However, when I did the same thing with real (live) money and with a prop firm account,I was shaved off as if by magic. Even though I was winning and losing, by month-end the balance was negative. Later, I reviewed each of my trades one by one and finally understood why.I was firing a lot of unnecessary shots in “times and situations where you should not trade.”.
Forgive my tardiness in introducing myself,lulu.fx. I am a current discretionary trader who mainly trades GOLD (XAUUSD), and I continue to build and test my own EAs. I am currently challenging a prop firm (Firm A).
In this series, “What you learn from testing: Why beginners can’t win in FX,” I write one by one about the real reasons beginners can’t win, discovered by contrasting a vast amount of data with demo trading. This is the fourth installment, and the theme is“Overtrading by not selecting winning situations or times”.“Overtrading”.
The belief that “the more you trade, the more you win” was an illusion
First, I’ll start with the biggest misconception I fell for at the very beginning. When I started demos, I believed“The more entries you make, the more profit opportunities you have.”I would hold positions 10 times or 15 times a day and feel satisfied, thinking, “I worked hard today.”
But this was completely backward. Trading involves costs that come with every trade, not only the gains when you win butthe cost you incur every time you place a trade. The spread (the difference between bid and ask) and slippage (the deviation from the intended price). On demo, these costs hardly mattered, so I didn’t notice, but in real tradingyou pay an “invisible tax” with every trade.
In other words, if you increase the number of trades in a situation without an edge, you’ll likely end up roughly break-even in wins and losses, yetyou will inevitably be eroded by costs. On demo, the balance looked flat, but in real trading, the moment costs kicked in, it turned downward. The reason I felt “winning and losing but somehow decreasing” was this.
What testing revealed: the edge is time-of-day biased
From here on is the part that made sense through testing. I separated my GOLD trades and a large amount of past data by“the time I entered the trade”and analyzed them. Then a clear pattern emerged.
For GOLD,the price movement was straightforward from London time to New York time (roughly 13:00–24:00 Japan time). If a trend developed, it extended smoothly, and pullbacks (brief retracements before continuing) were easy to read. Meanwhile,the early morning hours in Japan (early morning to late morning) had weak movement and lacked direction, and were a time prone to whipsaws. A pattern of entering counter-trend on specific days also had a poor edge when we counted it up.
This makes sense when you think about it. GOLD moves significantly when market participants in London and New York are seriously buying and selling. When there are few people and large sums of money aren’t moving, price action tends to lack “meaning.”In such scenes, trading “just because it’s moving” is merely noise and offers no edge..
What’s important here is the fact that“winning opportunities are clustered in only a small portion of the 24 hours.” Edge is not widely scattered but is concentrated in a few strong windows. Yet in demos I traded indiscriminately across all times without considering the clock.I was blowing the profits from favorable times on the costs of unfavorable times.
That brings us to the free part of this article. From here on, I will revealthe non-trading conditions besides time-of-dayand the“list of things not to trade”that I actually paste next to my desk. Even after halving my number of trades, the end-of-month figures improved.
From here (Read more) we will publish:
- Not just time-of-day, but the market state itself that inverts edge“when market conditions change”.
- Whydemo cannot reveal overtrading (the wrong conclusions that come from naive testing)
- The three lists I post beside my desk“do not trade times, scenes, and timings”
- If I halved the number of trades,my results actually improved—the reasons and the time-filter I’ve added into my EA
- The most difficult thing“the courage not to trade”—how to support this with data rather than willpower