What an EA's Average Holding Time Reveals About Its True Strategy — How to Check It in Reports, and Where It Falls Short

The conclusion up front: holding time is a strategy description the EA can't fake

EA sales pages are full of descriptions like "trend-following" or "buy the dip." But there's no guarantee that description actually matches the logic running under the hood. When we verify a third-party EA, the first thing we look at isn't the sales copy — it's the average holding time per trade.

Holding time doesn't lie. The gap between entry time and exit time is a direct record of what the EA actually did. And once you know the holding time, you've largely already learned which cost is most likely to kill the strategy. EAs that close out in minutes are vulnerable to spread and slippage; EAs that carry positions for days are vulnerable to swap and weekend gaps. This isn't a matter of one strategy being better than another — it's simply a structural consequence of holding time.

Why holding time lets you estimate vulnerability

The reason is simple: the ratio of target profit range to cost is almost entirely determined by holding time.

An EA with a short holding time is also targeting a smaller price move per trade. The smaller that move, the larger a share spread and slippage take out of the profit. A strategy that performed well in backtesting but turns unprofitable the moment live spreads widen is, more often than not, this type.

Conversely, an EA with a longer holding time targets a larger move per trade, which gives it more cushion against costs. The trade-off is that simply being in a position becomes a risk in itself — economic releases, weekend gaps, accumulating swap. And because trade frequency drops, the sample size shrinks even over the same number of backtest years, which weakens statistical confidence.

Where to look in an MT5 report

The MT5 Strategy Tester summary doesn't include an "average holding time" field. You have to derive it yourself.

1. Open the "Trades" tab in the tester, right-click, and export a report (or CSV) of all executions.
2. Pair each entry time with its corresponding exit time and take the difference. Matching by position ID lets you track partial closes as well.
3. Look beyond the average — check the median, the maximum, and the histogram. This is where the real insight lies.
4. Tally winning trades and losing trades separately.

Step 4 carries the most information. If you see a distribution where wins are short and losses are extremely long, there's a good chance the EA is designed to let losing positions ride, hoping for a reversal. That kind of design tends to produce a high win rate, but it also means a single large loss can wipe out a long string of gains.

Conversely, if losses are short and wins are long, that points to a design where stop-losses are actually functioning and winners are allowed to run. This type often has a win rate below 50%, but as long as PF stays above 1.0, the logic holds together.

Cross-checking against real measured data

Our own EAs show this relationship between holding time and trade count quite plainly. MEGAMAX DONCHIAN (USDJPY H1), tested over 9.4 years, posts PF=1.55, win rate=34.55%, and 631 trades. That's a low-win-rate type where PF still holds up — consistent with a distribution that cuts losses short and lets winners run.

BITCOIN GLACIER (BTCUSD D1), on the other hand, tested over 8 years, shows PF=2.4, win rate=57.1%, but only 28 trades. The numbers look good, but with a trade count this low, treating it — including its average holding time — as statistically meaningful is a stretch. We classify this not as a "good EA," but as an "EA we don't yet have enough evidence on."

It's worth looking at the high-win-rate side too. GOLD PIVOT (XAUUSD M1), tested over 4.5 years, shows PF=1.58, win rate=90.6%, and effective drawdown=49%. A win rate of 90.6% paired with a PF of only 1.58 tells you that a single loss is offsetting a large number of wins. Pulling the holding time distribution shows exactly where this asymmetry shows up. That's the value of checking the time axis, not just the headline numbers. Measured results for each EA are compiled on the measured performance ranking page, and individual verification details are available on the MEGAMAX DONCHIAN and BITCOIN GLACIER pages.

Limitations, and what this method can't tell you

To be upfront about it:

• Holding time tells you the "type," not the "quality." Short-term isn't inherently dangerous, and long-term isn't inherently safe.
• Backtest holding times don't match live trading exactly. Execution delays, requotes, and spread widening all shift exit conditions in live conditions, and the gap can be significant — especially for minute-chart scalping types.
• Averages are heavily skewed by outliers. A single trade left to bleed can swing the average substantially, so always check the median and the distribution alongside it.
• Martingale and grid-style EAs need a different interpretation of holding time. Since positions get added to over time, a simple entry-to-exit difference doesn't reflect what's actually happening.
• Holding time can't reconstruct the entry logic itself. What it reveals is limited to exit design and where the risk sits.

In short, this is a filter for narrowing down candidate EAs — not a pass/fail test. More fundamental checkpoints are covered on our knowledge base page.

Summary

• Average holding time is a record of an EA's actual behavior, and it's more trustworthy than the sales description.
• Short-term types are vulnerable to spread and slippage; long-term types are vulnerable to gaps, swap, and insufficient sample size.
• MT5 doesn't compute this for you — you need to export the trade history and calculate the average, median, and distribution yourself.
• Tallying holding time separately for winning and losing trades carries the most information. If only the losses run extremely long, suspect a design that delays cutting losses.
• Holding time can tell you the strategy's type and where its risk sits — but not whether it's good, and not whether it will hold up in live trading. That takes more than this alone.