Expectancy Per Trade Versus Expectancy Per Hour

[Fairman]

Expectancy Per Trade Versus Expectancy Per Hour

Traders usually measure edge per trade. A second measure deserves attention: how much you make per unit of time and effort.

Imagine two strategies. One yields +0.3R per trade, but only two trades appear per week. The other yields +0.1R per trade and generates twenty trades. The second produces 2R per week against 0.6R for the first, even though its per-trade edge is smaller.

But frequency has costs. More trades mean more spreads and commissions, more screen time, more decisions, and more exposure to execution errors. Low-edge strategies are also more sensitive to costs. A 0.1R edge can vanish if the spread consumes 0.1R per trade.

So the useful comparison is net expectancy after costs, multiplied by trade frequency, and weighed against your time and the risk of burnout.

It also affects the speed of learning. A strategy with more trades produces a meaningful sample faster, which helps evaluate whether it works. A swing strategy with ten trades a year takes a long time to verify.

Choose a style that matches your life. A trader with a full-time job and two hours in the evening cannot run a strategy requiring constant attention.

Practical step: compute your net expectancy per week, in R, for your current approach, and compare it with the time you spend.

[LondonNewsTrader]

The per-hour framing suits news trading in an odd way. A release-based approach might only offer a handful of genuine opportunities a week, so per trade it can look attractive and per hour it looks poor, until you count the hours honestly. If the plan is to be at the screen for ten minutes around 13:30 and then close the platform, the hourly figure can be very good. If you sit there all afternoon waiting and take a few marginal trades out of boredom, both numbers suffer.

So I'd split the time measure in two: hours spent watching and hours with an open position. The gap between them tells you a lot about where the forced trades come from.

[Fairman]

Worked comparison. Strategy A: plus 0.3R per trade, two trades a week, so about plus 0.6R a week. Strategy B: plus 0.1R per trade, but 15 trades a week, so about plus 1.5R a week. B looks worse per trade and better per week, but it also costs a lot more screen time and is more sensitive to costs. A small rise in spread or slippage could push B's edge close to zero, while A would barely notice. B also needs you at the screen for many hours, with more chances for mistakes. So I'd also measure R per hour of screen time, after costs. For a part time trader, A often wins on that measure even though B produces more.

[Fairman]

The per-hour view also helps with burnout. If a strategy needs eight hours a day for a small edge, the cost isn't only money, it's energy. A slower strategy with fewer hours may be the one you can actually sustain. A strategy you follow for three years beats one you abandon after three months because it wore you out. Signs of burnout are taking trades you'd normally skip, dreading the session and checking the phone constantly outside trading hours. If those show up, it might be the strategy's time demands rather than your discipline that needs fixing.

[Fairman]

How I'd use this in practice: you don't always have to pick one. Run the slow strategy as the base, since it needs little time, and use the faster one only in its best window, for example from the London open at 8am Lagos until about 10am. That way you get most of the faster strategy's edge from its best hours, without the long sessions where results usually fade. Track the two separately in the journal for a couple of months. Often the fast strategy's results improve once it's limited to its best window.