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1995issue C021-14

Stock leverage from compounded returns and margin cost

Leverage is debt divided by equity, restated inside each long stock trade's return so one ratio can be varied after commissions, dividends, holding days, and margin interest. The archive then resamples completed trades to judge whether a single bounded setting still leaves the account intact.

  • Leverage is debt divided by equity, and under a 50 percent initial margin rule the highest ratio is 1, not 2.
  • A leverage study on one stock needs at least 30 completed trades. Marking unfinished trades to market is treated as an unreliable way to pad the sample.
  • Commissions and dividends cut the worked long-only win rate from 68 percent to 49 percent, and the unlevered average trade return must stay positive before leverage is considered.
  • An average equity-versus-leverage curve can look favorable while individual paths stay uneven, so a leverage choice is personal rather than universal.
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How ending equity is built

With full reinvestment, ending equity is the starting equity multiplied through by one plus each trade's return on equity. Return on equity for a long stock trade can be written from share prices, commissions, dividends, holding days, and margin interest, then restated so a single leverage value can be varied.

Leverage is defined as debt divided by equity, and under a 50 percent initial margin rule the highest debt-to-equity ratio is 1, not 2. Leverage control and margin management keep that bound, and the interest and loss burden, visible before entry and throughout the position.

Completed trades, commission, and interest

A leverage study on one stock needs at least 30 completed trades. Marking unfinished trades to market is treated as an unreliable way to pad the sample.

Commission paid from equity reduces the financed share amount, so the price-to-price-plus-commission factor is always less than 1 and slightly lowers the interest charge.

A fully leveraged one-year long that rises 5 percent while margin interest is 10 percent produces a zero return on equity once interest is deducted. In the worked long-only example, adding commissions and dividends cut the win rate from 68 percent to 49 percent, while the unlevered average trade return stayed positive, which the compounding test requires before leverage is considered.

Resampling one leverage setting

The resampling exercise used a commission-adjusted factor of 0.996, at least 70 simulated rows, and 100 collected outcomes as a practical sample for judging leverage. That check is a Monte Carlo simulation of the same completed-trade sequence.

Across those simulations, leverage was worse than cash only 4 percent of the time, and at a debt-to-equity setting of 0.75 the losing cases stayed within 10 percent of the original stake. An average equity-versus-leverage curve can look favorable while individual paths to that average remain uneven, so a leverage choice is personal rather than universal.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
6 of 26 in the Monte Carlo simulation track
19961-1 pp.Next on Monte Carlo simulationConstructing and optimizing volatility position-sizing profilesA vps-profile lets the control U change only at K discrete values of S, and each change is stored as an independent entry in the change-vector.
All readings on this track · 26 readings
  1. 1989Known-bias price streams for system evaluation
  2. 1989Constructing holdout-checked synthetic prices from chaos maps
  3. 1991Closing the feedback loop in auction market simulations
  4. 1994Evaluating eight-year election regimes
  5. 1995Constructing equity versus leverage with resampled trades
  6. 1995Stock leverage from compounded returns and margin cost
  7. 1996Constructing and optimizing volatility position-sizing profiles
  8. 1996Constructing fade rules from an empirical deviation histogram
  9. 1998Return-path volatility and the recovery burden
  10. 1999Monte Carlo checks beyond a single historical path
  11. 2002Monte Carlo equity paths from win rate and profit factor
  12. 2003Checking a small system edge with Monte Carlo simulation
  13. 2003Evaluate a mechanical trading system with a stop-loss order and Monte Carlo simulation
  14. 2005Evaluating momentum rank rotation under portfolio constraints
  15. 2009Bounded risk and rank rotation in portfolio construction
  16. 2010A calendar for walk-forward robustness and Monte Carlo evaluation
  17. 2012Treat the optimize view as an evaluation protocol
  18. 2013Entry, exit and abstention as one testable procedure
  19. 2014Evaluating stop and target bounds before fading large moves
  20. 2014Evaluating system exits when markets get noisier
  21. 2015Memory-bearing synthetics for dominant-cycle spectra
  22. 2015Constructing next-session implied-volatility forecasts by reordering closes
  23. 2016Mechanical systems as a gated factory
  24. 2017Four-sleeve Monte Carlo annual-loss bounds
  25. 2018When to retire a mechanical system with Monte Carlo drawdown limits
  26. 2020Treat mechanical system design as a revalidation lifecycle
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