Research method
Monte Carlo simulation
Monte Carlo simulation is a canonical archive-taxonomy method; this registry entry defines its inputs, output and use boundary.
- Output
- Conditional forecast or research filter
- Input
- Ordered price, volume or breadth observations
- Horizon
- A defined sampling interval and lookback
- Best use
- Compare an explicit quantitative baseline with an out-of-sample result.
- Input: Ordered price, volume or breadth observations.
- Output: forecast.
- Use boundary: Compare an explicit quantitative baseline with an out-of-sample result.
The graph3
How the method is built, and where it has been read
Depends on
Often reviewed together
Expected value4 readings
Often reviewed together
Volatility position sizing5 readings
Often reviewed together
Risk of ruin5 readings
Read in the archive24 of 51 readings
1984When random walks fail to explain market averages1986Evaluating advance-decline plus-day runs against chance baselines1989Known-bias price streams for system evaluation1989Measured range, scale-in ladders, and spread replay as a cash-reserve design1989Constructing holdout-checked synthetic prices from chaos maps1991Constructing tick engines to match price-change histograms1991Closing the feedback loop in auction market simulations1992Constructing fractal templates from successive index changes1992Sizing capital from degraded records and volatility1992Risk of ruin and exposure caps as a pre-trade filter1994Evaluating eight-year election regimes1995A Kelly-style leverage grid and reshuffled paths1995Optimal f as a leverage bound for commodity account growth1995Stock leverage from compounded returns and margin cost1995Constructing equity versus leverage with resampled trades1995A normalized dispersion screen for trend-following1996Constructing and optimizing volatility position-sizing profiles1996Employment-release direction as a later-month persistence test1996Constructing fade rules from an empirical deviation histogram1997Testing bond and stock seasonality before you trade1997Why failed random-walk tests still need careful Monte Carlo work1998Return-path volatility and the recovery burden1998When quieter returns lose their survival edge1999Monte Carlo checks beyond a single historical path
This registry entry describes a research method. It is not investment advice and does not make a performance claim.