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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.
Entries in this reading3 entries

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

The mean $1 scalping run (2.63% hit rate, 35-to-1 payoff) only loses about $57 after 1,000 bets, yet the best run in the sample finishes near +$511 and the worst near -$496. A hard peak-to-trough cap can therefore reject a mix that still passes the shared -5.26% expectancy screen. Endpoints follow the printed max, mean and min returns; the path in between was read from the article’s scalping equity chart.
The mean $1 scalping run (2.63% hit rate, 35-to-1 payoff) only loses about $57 after 1,000 bets, yet the best run in the sample finishes near +$511 and the worst near -$496. A hard peak-to-trough cap can therefore reject a mix that still passes the shared -5.26% expectancy screen. Endpoints follow the printed max, mean and min returns; the path in between was read from the article’s scalping equity chart.Roulette single-number analogue · 1,000 sequential $1 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.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
16 of 22 in the Expected value track
201559-61 pp.Next on Expected valueSignal, confirm, and invalidate before the tradeTechnical study classifies present price and volume as the visible result of supply and demand. It is not a forecast of the next day, week, or month.
All readings on this track · 22 readings
  1. 1995A pre-trade checklist that bounds loss before the order
  2. 1998Ledger audit of exits, payoff, and overlap
  3. 1998A return-to-loss filter for drawdown-aware evaluation
  4. 2000Pair historical volatility with return-to-loss filters
  5. 2001Credit-spread construction that can fail before any order is sent
  6. 2002Evaluating mechanical systems in a traders market
  7. 2002Profitability as a bound implied by RWL and commission
  8. 2004A day-trading breakeven matrix for size and win rate
  9. 2006Sit out, size and expectancy as one procedure
  10. 2006A testable intraday procedure from setup to stand-down
  11. 2007A planned liquidity offer at the inflection point
  12. 2011A style-neutral expectancy filter for system evaluation
  13. 2011Separate buying power from posted risk capital
  14. 2012Design before you trade: testing mechanical systems
  15. 2014Ideal trader hindsight as a pretrade filter
  16. 2014When expectancy and drawdown limits disagree
  17. 2015Signal, confirm, and invalidate before the trade
  18. 2015Price the win, stall, and loss before a stock entry
  19. 2016Construct expectancy by bounding losses and winner size
  20. 2017Estimate expectancy before you accept the trade
  21. 2017Size ladder tests for drawdown caps and expected value
  22. 2017Evaluate a high-yield correlation break as one locked procedure
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