After a backtest, I would like to create a list of assets or groups to enter the live market.
I would like to find not just the best parameters but the minimum (sharp or CAGR) after training and testing that would give me positive results in a live test.
So let's say, after the training and testing, the best parameters give a sharp that is too low. How do I determine how low is too low? Can I use AI to make this determination a threshold? So if my performance is too low, I would not go into the market or return any assets on the list.
Thank you in advance for your time.
Hello Emma,
A Sharpe Ratio of 1.0 is often considered a reasonable benchmark for a well-constructed investment portfolio or strategy. It suggests that for each unit of risk, you are earning one unit of return above the risk-free rate. A Sharpe Ratio greater than 2.0 is generally regarded as excellent. This indicates that your investment is generating a high return relative to the level of risk it carries.
However, it should be noted that it is essential to use the Sharpe Ratio in conjunction with other performance metrics and to consider the broader context of your strategy. While you can't directly use AI to determine the threshold, you can utilize machine learning techniques to optimize your strategy or to help you predict when it's likely to underperform based on historical data. For example, you can build a model to forecast market conditions that are unfavourable for your strategy.
Hope this helps. Let me know if you have any further queries on this.