What Is a Good Profit Factor? 1.5 Can Be Pure Noise

You ran a backtest, the report says profit factor 1.8, and you want to know if that is good. Fair question, but the number is answering a smaller question than you think. Profit factor is a ratio of two noisy totals, so what it deserves is

You ran a backtest, the report says profit factor 1.8, and you want to know if that is good. Fair question, but the number is answering a smaller question than you think. Profit factor is a ratio of two noisy totals, so what it deserves is judged by the trade count, the costs and the biggest winner behind it, not by a single threshold.

Profit factor is win rate and payoff in one number

TradingView's help page on profit factor defines it as the absolute value of all winning trades divided by the absolute value of all losing trades. Above 1.0 the strategy made money in the sample, below 1.0 it lost money.

Unpack it with two inputs. Win rate is p, the share of trades that win. Payoff ratio R is your average win divided by your average loss. Then profit factor equals p × R / (1 − p).

That one line explains most of what you see in reports. A 65% win rate with winners half the size of losers sits at 0.93 and loses money. A 35% win rate with winners twice the size of losers sits at 1.08 and makes it.

Win rate	Payoff 0.5	Payoff 1.0	Payoff 1.5	Payoff 2.0
35%	0.27	0.54	0.81	1.08
45%	0.41	0.82	1.23	1.64
55%	0.61	1.22	1.83	2.44
65%	0.93	1.86	2.79	3.71

These are straight arithmetic with fixed wins and losses and no costs. They link to expectancy (average result per trade) through a neat identity: expectancy in R equals (1 − p) × (profit factor − 1). A 45% win rate with 1.5R winners gives a profit factor of 1.23 and an expectancy of +0.125R per trade, the same strategy we used when we simulated half Kelly against full Kelly.

So profit factor is not a separate truth. It is the same edge, repackaged as a ratio.

Costs decide whether a 1.2 stays above 1

Take that same strategy, 45% wins and 1.5R winners, profit factor 1.23. Now charge a round-trip cost of c on every trade, measured in R. Spread, slippage and commission all land in that number.

The cost makes every winner smaller and every loser bigger, so the formula becomes p × (R − c) / ((1 − p) × (1 + c)).

How big is c in practice? It depends on your stop distance. If a stop is 10 ticks away and a round trip costs you 1 tick in spread and slippage combined, c is 0.10R. Tighten the stop to 5 ticks and the same cost is 0.20R, which turns this profit factor into a loss. That is why where your stop sits relative to volatility matters for backtest quality too.

TradingView's broker emulator documentation says to set slippage to a non-zero value for strategies using market or stop orders. If you never touched that setting and the commission fields, your profit factor describes a market with no friction, and no such market exists.

A 100-trade profit factor is a wide range, not a reading

Now the part that makes the number less comforting. We took the strategy above, true profit factor 1.23, and ran 100,000 simulated backtests at each trade count. Trades are independent, wins and losses are fixed at +1.5R and −1R, and there are no costs.

Trades in backtest	Middle 90% of observed profit factor	Showed below 1.0	Showed 1.5 or better
30	0.64 to 2.25	24%	35%
50	0.77 to 1.91	20%	28%
100	0.88 to 1.69	13%	18%
200	0.96 to 1.56	7%	9%
500	1.06 to 1.42	1%	1%

Read the last column slowly. At 30 trades, more than a third of backtests of a modest, honest strategy printed a profit factor of 1.5 or better. At 100 trades it was still about one in five. Nobody was cheating and the strategy never changed. That is just luck in a short sample.

The same lesson sits under the trade counts a backtest needs before you trust it, and the same spread of outcomes shows up in backtest max drawdown against live drawdown. A single profit factor is one draw from this table.

A profit factor of 1.5 on 40 trades is not a result. It is a coin that landed heads a few times.

— The Tradoki desk note

One big winner can carry the number

Fixed +1.5R winners are kind to the metric. Real winners vary, with a few large ones and a pile of small ones. We reran the test with losers fixed at −1R and winners drawn from an exponential spread averaging 1.5R, which keeps the true profit factor at 1.23 but adds tails.

At 100 trades the middle 90% widened to 0.79 to 1.82, and 22% of backtests showed a loss. The single largest winner carried a median 9% of gross profit, and in one run out of twenty about 15% or more. Strip that one trade out and the median profit factor fell from 1.22 to 1.10.

TradingView's strategy report lists this directly in its trades analysis metrics, including the largest profit as a share of gross profit and an outliers line. Look at both before you trust a headline ratio. If removing the best trade moves you toward 1.0, your edge is one trade wide.

What a believable profit factor looks like

Here is where opinion starts, and it is labeled that way. As a rule of thumb, not a measured statistic: after realistic costs and a few hundred trades, a profit factor of roughly 1.2 to 1.6 is believable for a retail strategy. Anything above about 2 on a backtest should push you to look for look-ahead bias, missing costs, tiny samples or parameters tuned to the data before you celebrate.

Our comparison of 15 trading strategies by win rate and risk-reward shows why. Win rate and payoff trade off against each other, and both are fed through the same formula.

Use a short checklist when you read a report:

1. Trade count. Under 100 trades, treat any profit factor as a range, not a number.
2. Costs. Confirm commission and slippage are set to something your broker would actually charge.
3. Largest winner. Look at its share of gross profit and recompute without it.
4. Open positions. Make sure unrealized losses are not hiding behind a clean ratio.
5. Drawdown. Profit factor says nothing about how deep the account went on the way, and two strategies with the same ratio can feel completely different to hold.

Profit factor is a useful summary after you have checked those five things. Before that, it is a headline.

● FAQ

What is a good profit factor for a trading strategy?

The only hard line is 1.0 after costs, because below it the strategy loses money. As a rule of thumb rather than a measured statistic, a figure between roughly 1.2 and 1.6 over a few hundred trades with realistic costs is believable for a retail strategy. A backtest showing 2 or 3 deserves suspicion before celebration.

How do you calculate profit factor?

Divide gross profit by gross loss, both as absolute values, using closed trades only. TradingView's help page defines it exactly that way. In terms of win rate p and payoff ratio R (average win divided by average loss), it equals p times R divided by (1 minus p).

Is a profit factor of 1.5 good?

It can be, but on its own it tells you very little. In our simulation, a strategy with a true profit factor of 1.23 showed 1.5 or better in 18% of 100-trade backtests. Check the trade count, the costs, and how much of the gross profit came from the single largest winner.

How many trades do you need before profit factor means anything?

Hundreds, not dozens. With 30 trades, the middle 90% of outcomes for our test strategy spanned 0.64 to 2.25. At 500 trades the same range narrowed to 1.06 to 1.42.