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2016issue C0325-29

Expectancy as an execution skill rather than a backtest score

Long-run results depend more on how profits and losses are handled than on being right or wrong on each trade. The historical workflow uses a mechanical trading system, a trading psychology process, and volatility position sizing so that losses can be cut and winners added to, instead of treating a historically positive expectancy as a required edge.

  • Long-run results depend more on how profits and losses are handled than on being right or wrong on each trade.
  • Winner and loser frequencies inferred from history are unstable because market outcomes can follow chaotic, fractal, or power-law behavior rather than a fixed probability distribution.
  • Trading expectancy is the practical use of greater control over average win and loss size than over hit rate, by cutting losses and adding to winners instead of retuning entry rules to manufacture a better historical score.
  • The same 60% hit-rate strategy produced a 19.2% yearly loss or a 28.8% yearly gain depending only on the position-sizing method.
Entries in this reading3 entries
Current trackVolatility position sizing57 readingsMechanical trading system322 readingsTrading psychology process376 readings

Handling profits and losses

Long-run results depend more on how profits and losses are handled than on being right or wrong on each trade.

When a backtest score is treated as an edge

Traders often treat a historically positive system expectancy as a required edge, then discard systems whose backtests look negative even when the issue may be a temporary mismatch with current markets.

Unstable winner and loser frequencies

Winner and loser frequencies inferred from history are unstable because market outcomes can follow chaotic, fractal, or power-law behavior rather than a fixed probability distribution.

A Monte Carlo illustration of size control

In one Monte Carlo exercise averaging millions of 30-trade long baskets in a bear market, random trades that lost 12% on average with about one winner in three became a 1.8% average gain when losses were cut to 3% and winners were added to.

Pause live trading instead of rewriting rules

An equity-curve feedback loop can pause live trading during drawdowns, keep measuring a paper curve, and resume only after the same rules show profitability again, instead of rewriting the system.

What counts as a complete strategy

A complete strategy is an unambiguous combination of entries, stop-losses, and profit exits plus a risk process, not a feeling of rightness or an unquantified discretionary habit. That specification is a mechanical trading system.

What is missing without a quantified edge

Without a quantified edge, a trader cannot know how many losses are normal, how long a losing streak can run while the system is still working, how to set stops, or how to size positions.

How position sizing can invert a working system

The same 60% hit-rate strategy produced a 19.2% yearly loss or a 28.8% yearly gain depending only on the position-sizing method, so ignoring sizing statistics can turn a working system into a losing process. Volatility position sizing is the risk process in that step.

Hope and fear as process signals

Hope after a trade turns against the trader is treated as an exit signal, while fear as profits accumulate is treated as a reason to stay, because the useful process is the opposite of those emotional prompts. That inversion is the trading psychology process joined to the same entries, stops, and exits.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
20 of 25 in the Volatility position sizing track
20178-13 pp.Next on Volatility position sizingVolatility parity equalizes the ticket; implied volatility is a regime dialUsing the same share count or a single futures contract on every trade lets higher-priced or more volatile markets dominate a multi-market book.
All readings on this track · 25 readings
  1. 1988Two-sided optimization for volatility-scaled breakout rules
  2. 1990Weekly range volatility as a tactical regime filter
  3. 1993Heat first, then contract count on a weekly close-only breakout
  4. 1994Shared sigma for trend entries, retests and stops
  5. 1995The promised result as one testable trading procedure
  6. 2001Convert a survival ceiling into a volatility filter
  7. 2002Bound the next loss before the bear trade
  8. 2004Dollar-loss tolerance versus percent-of-equity stops
  9. 2004Bounded risk before entry: stop, size, and leverage
  10. 2006Position sizing as the pre-trade bound on loss and exposure
  11. 2006A trend-regime matrix for volatility position sizing
  12. 2011A premarket range checklist for opening-hour breakouts
  13. 2011Stop-defined share count on a clustered intraday short
  14. 2012Mechanical system design with strategy, signals, and size
  15. 2012Precommit size before a one-day policy shock
  16. 2013R-multiple expectancy, drawdown, and volatility position sizing
  17. 2014Constructing trend-aware slope-divergence rules
  18. 2014Pretrade drawdown fences and volatility sizing
  19. 2015Convert pip value into cash before a forex lot size is chosen
  20. 2016Expectancy as an execution skill rather than a backtest score
  21. 2017Volatility parity equalizes the ticket; implied volatility is a regime dial
  22. 2018Wide-range breakout rules from chart volatility
  23. 2019A structure-based stop, then resize or pass
  24. 2020A cash rule that zeros a trend book on extreme volatility and a short losing window
  25. 2025R-multiples before you size up
By fieldDecision process416 readingsBy year2016134 readings
All 57 readings tagged Volatility position sizing
Also on Volatility position sizing5 readings
1987Volatility-layered mechanical system with fixed contracts1988Two-sided optimization for volatility-scaled breakout rules1994Shared sigma for trend entries, retests and stops2012Mechanical system design with strategy, signals, and size1995The promised result as one testable trading procedure