Expected Value Thinking: How to Make Trade Decisions Like a Professional Futures Trader

The Question That Changes How You Trade

When evaluating whether to take a trade, Cameron Bennion asks a specific question: "If we ran a Monte Carlo simulation of this trade 10,000 times, would you take this trade? If you can unequivocally say yes, execute the trade tomorrow morning. If you cannot, what else do you need?"

This is expected value thinking — the framework that separates professional traders and institutional investors from retail traders who are essentially gambling with an incomplete understanding of probability.

Most retail traders evaluate trades by asking: "Do I think this will go up?" or "Does this feel like a good setup?" Neither of these is a probability-based question. They are prediction questions — and prediction is not how edge works. The 10,000-simulation question is different. It asks: "If I took this exact setup under these exact conditions 10,000 times, would the cumulative outcome be positive?" If yes, the trade has positive expected value and belongs in your system. If no, or if you're uncertain, you don't have enough information to take the trade systematically.

What Expected Value (EV) Actually Means

Expected value is the average outcome per trade if the same trade were taken infinitely many times. The formula:

EV = (Win Rate × Average Win) − (Loss Rate × Average Loss)

Example: A setup with 55% win rate, $300 average winner, 45% loss rate, $200 average loser produces:

EV = (0.55 × $300) − (0.45 × $200) = $165 − $90 = +$75 per trade

A trade with +$75 expected value should be taken every time it appears, without hesitation, regardless of how the last three trades turned out. A trade with negative EV should never be taken, regardless of how compelling the narrative feels in the moment.

The professional traders distinction: they are concerned with EV per trade type, not the outcome of any individual trade. A loss on a +$75 EV setup is not a mistake — it is a statistically expected outcome on a given iteration. A win on a −$20 EV setup is not a success — it is a statistically expected outcome that will erode capital over sufficient sample size.

How to Calculate EV for Your Futures Setups

Building an EV model for a futures setup requires three inputs, all obtainable from a properly maintained trading journal:

Step 1: Define the setup precisely. EV is only meaningful for a specific, repeatable setup with defined entry criteria. "Trade when it looks good" has no calculable EV. "Enter a mean-reversion long at the first touch of the KPL support zone when ES is in LOW regime, with a 4-point stop and 8-point target" has calculable EV. The more precisely the setup is defined, the more meaningful the EV calculation.

Step 2: Collect a meaningful sample. At minimum 30 instances of the exact setup, ideally 50-100 to reduce variance impact. Your trading journal should allow you to filter by setup type and calculate win rate, average winner, and average loser from the filtered results.

Step 3: Calculate and stress-test. Calculate the base EV. Then ask: what does EV look like if win rate drops 10%? If average winner drops 15%? If a bad fill adds $50 to the average loss? A setup that remains positive EV under conservative stress assumptions is a genuinely robust setup. A setup that turns negative EV with a 5% win rate deterioration is fragile and should be sized small or avoided.

The 10,000-Trade Test in Practice

The 10,000-trade framing is not an actual calculation — it is a mental model for shifting from outcome-focused thinking to process-focused thinking. When you are about to take a trade, ask the question literally:

"If I took this exact setup — this entry, this stop, this target, under these market conditions — 10,000 times over my career, would I have positive cumulative P&L?"

If yes with high confidence: take the trade. Size it appropriately. Do not think about whether this particular instance will win.

If yes but with significant doubt: take the trade at reduced size. The doubt signal means your evidence base for this setup is thin or the conditions are uncertain.

If no or uncertain: do not take the trade. The feeling that "this one is different" or "this time it's obvious" is exactly the cognitive bias that causes negative-EV trades to be taken.

How KPL Levels and Systematic Strategies Encode EV

The KPL algorithm's six-year development history is fundamentally an EV optimization process. Each parameter in the model was tested across thousands of instances to determine whether it produced positive expected value in specific market conditions. The result: level identification with documented statistical significance across multiple market regimes.

When you receive a daily KPL output, you are receiving the output of a system that has already answered the 10,000-trade question for the level identification criteria. The remaining question for the manual trader is whether the execution — the specific entry confirmation, stop placement, and target — also passes the 10,000-trade test in current conditions.

This is why regime classification matters: the same KPL level in a HIGH-volatility, trending regime has a different EV profile than the same level in LOW-volatility, range-bound conditions. The level still holds statistical significance, but the optimal execution parameters (wider stops, reduced size) change to maintain positive EV in the different environment.

When EV Thinking Becomes Execution

The most powerful application of EV thinking is in the management of losing streaks. A trader who understands expected value responds to five consecutive losses on a +$75 EV setup by confirming that execution followed the rules (not by modifying the strategy). The five losses do not change the EV of the sixth trade — they are normal statistical variance on a positive-expectancy system.

The trader who responds to five losses by changing stops, modifying targets, or reducing size "until confidence returns" is doing something different: they are optimizing for psychological comfort rather than expected value. The result is always the same — the strategy degrades because the modifications are not evidence-based, and the reduced size means that when the positive-EV streak resumes, the account does not recover what the psychological adjustment cost.

EV thinking is a discipline, not just a calculation. The discipline is treating every trade as one instance of a 10,000-trade series, and making decisions based on the series, not the instance.

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