The optimization module can be accessed by on clicking the optimization button (i.e wand icon) from My Strategies.
Select the strategy and instrument from the drop down. Only one strategy/instrument pair can be optimized at a time.
You can then choose an appropriate optimization algorithm:
Genetic: Genetic applies a genetic evolution to the population. The population is selected among the parameters ranges to be optimized. For example an indicator parameter within a certain range. By choosing an appropriate object function we can chose to minimize or maximize our objective function. By default the hyper parameters are pre-set for the genetic algorithm. The Problem type and objective function can be changed.
Grid Search: A grid is an brute force approach to optimization that will test all combination of parameters. Note that there is limit on the number of combination set depending on your user profile.
In the Parameters section you can input the components and the ranges of values to be optimized. At least one parameters needs to be filled.
Other parameters such as Timing and trade settings can be set for optimization. These options are identical to Backtesting
Once the optimization is executed it is shown on the same screen. On the left hand side the backtest result is shown which is based on the optimization parameters. On the the right hand side the walkforward result is shown which is the result of executing the optimized strategy on unseen data.
To open the strategy with the optimized parameters click on the open icon and this opens a new dialog to save the optimized strategy. This new strategy has its parameters replaced with the ones found during the optimization and can be executed like any other strategy.