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2010issue C0724-26

Risk of ruin with fractional and reserve betting

The archive frames Risk of ruin as the chance that equity hits a defined failure level, then assigns separate ruin probabilities to a reserve sleeve and a fractional sleeve. Editorial view: multiply those two paths before Expected value is allowed to commit size.

  • Risk of ruin is the probability that account equity reaches a defined failure level given win size, loss size, win rate, starting equity, and a success threshold.
  • A six-input function converts average win, average loss, and win percentage into an Expected value and standard-deviation pair, then maps remaining capital into standardized units between failure and success.
  • At a 30% win rate the archive assigns a 9% ruin probability to the defensive reserve sleeve and a 74% ruin probability to the aggressive fractional sleeve, and their product is 0.0666.
  • Editorial view: multiply those two bounded ruin paths before Expected value arithmetic is allowed to commit size, so a positive edge does not outrun a checkable chance of going to zero.
Entries in this reading3 entries
Current trackRisk of ruin48 readingsMonte Carlo simulation51 readingsExpected value61 readings

What risk of ruin measures

Risk of ruin is framed as the probability that account equity reaches a defined failure level given win size, loss size, win rate, starting equity, and a success threshold.

An earlier tabulated Risk of ruin method used success probability, fraction of capital exposed, and payoff ratio as the core inputs. Those tables are the archive's point of comparison for a later closed-form function.

A six-input closed-form path

A six-input ruin function first converts average win, average loss, and win percentage into an Expected value and standard-deviation pair, then maps remaining capital into standardized units between failure and success.

When the implied win probability equals one half, the function averages two nearby gambler-ruin ratios instead of dividing by a zero edge.

The closed-form function is described as slightly more pessimistic than those earlier simulation tables, moving an example 77% ruin reading to about 79%. Editorial note: that table comparison is the article's contact with Monte Carlo simulation. The formula is not replaced by a new sampling study here.

Two sleeves and a product

At a 30% win rate, the defensive reserve sleeve is assigned a 9% ruin probability and the aggressive fractional sleeve a 74% ruin probability. Their product is 0.0666.

With a 120% average win and 40% average loss at that same 30% win rate, Expected value per trade for the aggressive sleeve is 8%. The archive also projects that the aggressive sleeve fails to return to the reserve level 26% of the time, with an extrapolated $1,006 gain over 30 non-breakeven trades and a combined blow-out probability of about 7%.

Expected value after the ruin product

Editorial reading: the position is two bounded capital paths, not one blended bet. The reserve sleeve and the fractional sleeve each carry a Risk of ruin figure, and size is not committed until those figures are multiplied.

The 8% Expected value on the aggressive sleeve is then read against that 0.0666 product and the about 7% combined blow-out reading, so edge arithmetic does not outrun a checkable chance of going to zero.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
16 of 24 in the Risk of ruin track
20148-9 pp.Next on Risk of ruinPayout identity, expectancy, and path-dependent ruinPayout-identity is the cash credited on a winning settlement, including whether the original stake is returned together with the stated percentage increment.
All readings on this track · 24 readings
  1. 1985Forced-close odds from monthly edge and leverage
  2. 1986Constructing a pre-entry risk filter on price-ratio grids
  3. 1991Ratchet the halt floor and stage exposure against cash
  4. 1992Sizing capital from degraded records and volatility
  5. 1992Filter size by expected value and ruin
  6. 1995Risk of ruin as a pre-entry position filter
  7. 1995Filter leverage by sequence-loss odds
  8. 1996Grading track records by drawdown, expected value, and ruin
  9. 1998When quieter returns lose their survival edge
  10. 1999Loss response versus a precommitted trading process
  11. 1999Reauthorize ruin and drawdown filters after a winning stretch
  12. 2000Sold premium, survivorship, and ruin bounds
  13. 2001Monte Carlo drawdown risk and volatility position sizing
  14. 2001Alertness is a size filter, not a mood
  15. 2002A constant percent risk bound beats a higher win rate
  16. 2010Risk of ruin with fractional and reserve betting
  17. 2014Payout identity, expectancy, and path-dependent ruin
  18. 2015Spreading names is not a substitute for a ruin bound
  19. 2015Prestige labels versus one testable trade procedure
  20. 2015Closed-trade quality screens before sizing risk
  21. 2019Size mini futures from drawdown and leftover margin
  22. 2019Starting account size as a survival filter
  23. 2019Pre-entry ruin and volatility caps for short options
  24. 2020Forced margin, stop-loss, and ruin risk in 2020
By fieldDrawdown and survival54 readingsBy year2010169 readings
All 48 readings tagged Risk of ruin
Also on Risk of ruin5 readings
2014Payout identity, expectancy, and path-dependent ruin2015Spreading names is not a substitute for a ruin bound1992Sizing capital from degraded records and volatility1992Risk of ruin and exposure caps as a pre-trade filter1998When quieter returns lose their survival edge