2014issue C1228-30
When expectancy and drawdown limits disagree
Two opposite payoff and hit-rate mixes can share one expected-value reading and still fail the same drawdown-limit screen. This note holds that mean fixed and asks which style a hard peak-to-trough cap would still allow before any order is sent.
- Expected value is a first pre-trade filter: a mean from win bias and payoff multiple that opposite styles can still share.
- After that mean is fixed, the risk-reward ratio still sets path-volatility, so a high-payoff mix is noisier than a near-even mix.
- A drawdown-limit screen would not treat those styles as interchangeable, because the high-payoff path can sink far below the shared mean.
- An account-survival cap can still reject a style after the expected-value reading is already known, before any order is sent.
Three filters before an order is sent
The historical workflow treats expected value, risk-reward geometry, and a hard drawdown bound as three separate pre-trade filters. Expected value is a pre-trade mean outcome computed from win bias and payoff multiple. It is used as a first filter that opposite styles can still share.
Win bias is the fraction of outcomes that hit the payoff side of a style. The risk-reward ratio is the payoff multiple that, together with win bias, sets both the expected-value reading and the width of the equity path. A drawdown limit is a cap on peak-to-trough equity loss used to reject a style whose path can sink far below the shared mean.
Opposite mixes can share one mean
Two opposite payoff-and-hit-rate mixes can return the same expected-value reading when expectancy is computed as win bias times one plus the payoff multiple, minus one. Under a 2.63 percent win rate with a 35-to-1 payoff and a 47.4 percent win rate with a 1-to-1 payoff, that shared expected value is a 5.26 percent loss.
Path-volatility after the mean filter
With that expected value held fixed, the high-payoff mix produced a series standard deviation near 5.77 percent versus about 0.99 percent for the near-even mix, so changing the risk-reward pairing still moves path noise after the expectancy filter is passed. Path-volatility is how far realized equity wanders around the expected-value mean across a long sequence of bets.
Across 1,000 repetitions of 1,000-bet sequences, profit-and-loss scatter around the common mean was much wider for the high-payoff mix, with a distribution standard deviation of 34.8 percent versus 8.7 percent. A volatility identity that scales with one plus the payoff multiple and with the square root of win-rate variance predicted roughly a 5.8-to-1 noise gap between the two mixes, consistent with the simulated standard deviations.
Why a drawdown limit still splits the styles
The high-payoff mix reached a maximum drawdown of 68.6 percent, against 15.4 percent for the near-even mix, so a drawdown-limit screen would not treat the two styles as interchangeable. High-payoff paths with a 2.63 percent win rate included losing streaks longer than 100 consecutive losing bets at least five times inside one 1,000-bet run.
Realized win rate drifted away from the design bias, stretching the high-payoff style from about 51.1 percent profit at a 4.4 percent realized win rate to about a 49.6 percent loss at a 1.4 percent realized win rate.
Scalping equity over 1,000 $1 roulette bets

Each path is one 1,000-bet run drawn from 1,000 Monte Carlo iterations of $1 single-number roulette bets (R=35, B=2.63%). Interior points are approximate readings off the plotted curves.
All readings on this track · 22 readings
- 1995A pre-trade checklist that bounds loss before the order
- 1998Ledger audit of exits, payoff, and overlap
- 1998A return-to-loss filter for drawdown-aware evaluation
- 2000Pair historical volatility with return-to-loss filters
- 2001Credit-spread construction that can fail before any order is sent
- 2002Evaluating mechanical systems in a traders market
- 2002Profitability as a bound implied by RWL and commission
- 2004A day-trading breakeven matrix for size and win rate
- 2006Sit out, size and expectancy as one procedure
- 2006A testable intraday procedure from setup to stand-down
- 2007A planned liquidity offer at the inflection point
- 2011A style-neutral expectancy filter for system evaluation
- 2011Separate buying power from posted risk capital
- 2012Design before you trade: testing mechanical systems
- 2014Ideal trader hindsight as a pretrade filter
- 2014When expectancy and drawdown limits disagree
- 2015Signal, confirm, and invalidate before the trade
- 2015Price the win, stall, and loss before a stock entry
- 2016Construct expectancy by bounding losses and winner size
- 2017Estimate expectancy before you accept the trade
- 2017Size ladder tests for drawdown caps and expected value
- 2017Evaluate a high-yield correlation break as one locked procedure