Different build modes
There are two build modes to choose from:
StrategyQuant first generates initial population of random candidates (using the Random Generation mode) and then uses genetic evolution process to evolve the population and produce better and better candidates with each generation.
The process ends when predefined number of generations is reached or when there’s no further improvement.
- in theory it should lead to strategies better than the initial random generation
- this means that the already good strategies in the first generation can be further improved
- search for profitable strategy in the trillions of possible combinations can be more effective with the power of genetic evolution
- evolution can be slower
- sometimes the evolution can lead to the dead end, so the generation should be watched
- the group of generated strategies is limited by population size
In this mode StrategyQuant continually generates and tests new random strategies, one after another, until it is stopped.
The top candidates (based on predefined criteria) are stored into Databank so you can review them later.
- faster and simpler than genetic evolution
- it can run until it is stopped, so if you let it run for a few days it can generate and evaluate millions of strategies
- once the strategies are generated they are not further evolved – but you can always use them as an initial population for the next genetic evolution