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2000issue C091-7

Sold premium, survivorship, and ruin bounds

A smooth run of daily credits can be a forensic clue that the book is sold premium. Reconstruct the payoff, send it through rising and falling path sets, and set a ruin cap before the streak is allowed to increase size.

  • Sellers treated infrequent payoffs as expensive lottery tickets and booked incoming premium as profit, which made out-of-the-money option contracts the most mispriced class in the early sample.
  • A long sequence of small gains can encourage larger size, then a single loss large enough to erase the book.
  • Collected gains without returned losses are a weak filter, because a winning path can attract capital just before ruin.
  • A budgeted maximum loss over an extended period is the stated alternative to stops on a sold-premium, negative-carry book.
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A smooth daily credit is a clue

Editorial reading: treat a smooth daily credit as a forensic clue. Reconstruct whether the book is sold premium, then demand a multi-regime path set and a pre-trade ruin cap before the streak is allowed to increase size.

In the historical workflow, out-of-the-money option contracts were the most mispriced class in the early sample, because sellers treated infrequent payoffs as expensive lottery tickets and booked incoming premium as profit.

The streak that invites size

Selling option premium can produce a long sequence of small gains that encourages larger size, then a single loss large enough to erase the book.

A product that pays 1 unit on each of 10 days and then loses 12 on the eleventh can have a higher chance of showing a profit than a loss while still having a negative expectation.

Collected gains are a weak filter

A four-year winning bonus path followed by a fifth-year wipeout can build a track record that attracts capital just before ruin, so collected gains without returned losses are a weak filter.

Unusual moves and engineered exposure

Daily profit-and-loss noise does not scale linearly with move size. A market move 10 times larger than usual is not 10 times more informative and may carry closer to 1,000 times the information.

A single engineered exposure measure cannot describe the distribution of future unusual events, because those events sit outside the parametric history used to compute the measure.

Path sets, not survivors

Trying every lookback window until a back-tested rule wins, or judging a method only from its survivors, overstates skill. The full starter population and both rising and falling regimes are needed to see whether the rule is a hidden short-option book.

Stops on a negative-carry book

Stops on sold-premium books often fail in whippy markets because a sequence of stops can force buybacks. A budgeted maximum loss over an extended period is the stated alternative for a negative-carry book.

The same payoff in a cash name

Holding an expensive name through a speculative buildup can mimic a short-option payoff: steady marks during the rise, then a loss far larger than a half-cut once the rare break arrives.

Who can survive a frequency error

A buyer of cheap convexity can be wrong about event frequency and still survive if the payoff is large. A seller cannot afford a probability error, because one unmatched rare event can exhaust the account in minutes.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
12 of 24 in the Risk of ruin track
20011-5 pp.Next on Risk of ruinMonte Carlo drawdown risk and volatility position sizingA Monte Carlo simulation can replay closed-trade profit or loss together with assigned risk in randomly chosen order across many sequences.
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
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