Money management in algorithmic trading - Singapore Forex Trading, Singapore Forex Academy, Singapore Forex Association

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Money management in algorithmic trading

1. Maximization of long-term growth rate:
• Is your goal the maximization of your net worth over the long term? If so, consider using the half-Kelly optimal leverage.
• Are your strategy returns fat-tailed? You may want to use Monte Carlo simulations to optimize the growth rate instead of relying on Kelly’s formula.
• Keeping data-snooping bias in mind, sometimes you can just directly optimize the leverage based on your backtest returns’ compounded growth rate.
• Do you want to ensure that your drawdown will not exceed a preset maximum, yet enjoy the highest possible growth rate? Use constant proportion portfolio insurance.
2. Stop loss:
• Stop loss will usually lower the backtest performance of mean-reverting strategies because of survivorship bias, but it can prevent black swan events.
• Stop loss for mean-reverting strategies should be set so that they are never triggered in backtests.
• Stop loss for momentum strategies forms a natural and logical part of such strategies.
3. Risk indicators:
• Do you want to avoid risky periods? You can consider one of these possible leading indicators of risk: VIX, TED spread, HYG, ONN/OFF, MXN.
• Be careful of data-snooping bias when testing the eff i cacy of leading risk indicators.
• Increasingly negative order fl ow of a risky asset can be a short-term leading risk indicator.