Strategies for Profitable Automated Trading in Financial Markets:
In the world of trading, setting clear objectives and employing a systematic approach is key to achieving success. David Bergstrom, a seasoned researcher and Guest Post author with the Twitter handle @dburgh, shares his insights on how to set clear objectives and use minimum thresholds along with objective measures to ensure trading strategies are robust and effective.
## Steps to Set Clear Objectives
1. **Define Trading Goals**: Determine whether your aim is for short-term gains, long-term growth, or a balanced approach. This will guide the development of your trading strategy.
2. **Establish Key Performance Indicators (KPIs)**: Use metrics such as return on investment (ROI), Sharpe ratio, drawdown, and risk-reward ratio to evaluate strategy performance. These metrics will help measure success and identify areas for improvement.
3. **Set Minimum Thresholds for Performance**: Establish a minimum acceptable performance threshold for backtesting and robustness testing. For example, a minimum ROI of 10% per year or a minimum Sharpe ratio of 1.0.
4. **Use Objective Measures for Evaluation**: Use quantitative measures like statistical significance tests to evaluate the strategy's performance.
5. **Risk Management Objectives**: Define risk management objectives such as maximum allowable drawdown or maximum daily loss.
6. **Backtesting and Robustness Testing**: Backtest your strategy on historical data and conduct robustness testing by applying the strategy to different market conditions and scenarios.
7. **Live Trading Objectives**: Set specific objectives for live trading, such as maintaining a consistent risk-reward ratio or achieving a certain level of profitability.
## Objective Measures and Thresholds
- **Return Thresholds**: Set a minimum return threshold that your strategy must meet to be considered successful. - **Risk Thresholds**: Define a maximum risk threshold, such as limiting the maximum drawdown to 20% of the account equity. - **Statistical Significance**: Use statistical tests to ensure that the strategy’s performance is not due to chance. - **Performance Metrics**: Monitor metrics like the Sharpe ratio to ensure the strategy provides a good balance between risk and return.
## Implementation
By setting clear objectives and using objective measures with minimum thresholds, you can ensure your trading strategy is robust and effective across different market conditions. Bergstrom's approach aims to make the decision-making process more objective and less subjective.
For example, in setting objectives with thresholds, one might require the strategy to achieve at least a 12% annual return during backtesting, limit the maximum allowable drawdown to 15% of the account equity, maintain a risk-reward ratio of at least 1:2, and ensure statistical significance at a p-value of less than 0.05.
Bergstrom also advises creating clear objectives for robustness testing, such as ensuring all Monte Carlo simulations or paths are profitable after 50 trades, and having clear rules for when to turn the strategy off, such as when the drawdown is worse than the worst drawdown from Monte Carlo simulation, the strategy trades outside of confidence bands, the strategy becomes too highly correlated with another strategy, or realized results are not matching test results.
David Bergstrom, the creator of Build Alpha software, recommends allowing automated trading systems to trade live with reduced size initially and stresses the need for thorough testing of execution code before risking real money. His website, BuildAlpha.com, is a valuable resource for those interested in learning more about his methods.
In conclusion, by following Bergstrom's guidance and setting clear objectives, using objective measures, and establishing minimum thresholds, traders can increase their chances of success in the volatile world of trading.
Data-and-cloud-computing technology can be employed to streamline the backtesting and robustness testing process in trading, ensuring strategies are repeatedly tested across various market conditions and scenarios. This will help achieve more accurate and consistent results, contributing to the overall success of the trading strategy.
By implementing automated systems like Build Alpha, which is a product of David Bergstrom, traders can easily test and evaluate their strategies, leveraging the power of data-and-cloud-computing technology to improve the decision-making process and make it less subjective.
