John Nolte

I'm an algo trader using stochastic modeling and Monte Carlo simulations to create trading strategies that will survive during live trading.

All my strategies undergo rigorous robustness testing to ensure a high probability of success for the longer term. Most of my strategies have very
simple trading rules and use price action and/or up to two indicators.

I use two different Monte Carlo tests, the first test runs 200 simulations using completely random EA settings, this helps to alleviate any over optimization
of the strategy. The second and final test is for robustness, I run 500 simulations that include:

Random EA settings - 20% chance of up to 20% change.
Randomly skipped trades - 10% chance.
Randomly selected starting candle up to 100 candles.
Random price change - 20% chance of up to 20% of ATR.
Randomized slippage between 1 - 3 pips.
Randomized spread between 2 - 4 pips.

This backtest is as close to live trading as possible. If a strategy is profitable on over 99% of the 500 simulations then I would consider trading it live.

All backtests are done with no less than a 2.0 pip spread, most of the time I will use a 3.0 pip spread on my backtests.

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