The Hundred-Trades Mental Model
Scaling one trade to 100 comparable trades turns abstract EV into total cost and payout counts, while making clear that majority accuracy can still lose money.
When one-trade algebra feels slippery, imagine buying one share in each of 100 genuinely comparable markets. Total cost, winning payouts, and net PnL become visible.
Cost and payout #
If each share costs and exactly of 100 resolve YES,
If the true win probability is , expected wins are and expected PnL is .
Running 65% example #
At and , expected cost is 60, payout is 65, and profit is 5. At , the same 65 expected wins cost 70 and lose 5. At , winning a 65% majority still loses 25.
Majority wins can lose money #
Suppose 80 of 100 contracts bought at 0.90 win:
Accuracy is 80%, yet the strategy loses because each loss costs 0.90 while each win earns only 0.10.
Life example #
A shop can profit on nine cheap items and lose everything on one heavily discounted high-cost return. Counting successful transactions without weighting their money amounts hides the business result.
Application to no-hedge #
Build the 100-trade table from filled no-hedge orders, using each actual execution price and cost. Do not multiply one advertised spread by 100; fills are selected, prices vary, and correlated markets do not supply 100 independent trials.
Self-check: 70 wins out of 100 purchases at 0.75. What is PnL?
Cost is 75, payout is 70, so PnL is -5 despite 70% accuracy.