Evolutionary algorithm in forex trade strategy generation. Manual development of a new trading strategy is a slow process. over again, generating and testing tens of the new unique strategies every second! This process imitates the evolution - the algorithm chooses the fittest strategies (using.

Evolutionary algorithm in forex trade strategy generation

Genetic Trading Algo

Evolutionary algorithm in forex trade strategy generation. 5 Concluding Remarks In the paper, the new evolutionary algorithm for generating profitable strategies on Forex financial trade market is presented. In spite of.

Evolutionary algorithm in forex trade strategy generation


Manual development of a new trading strategy is a slow process. It starts with trader using his experience and knowledge to pick up the elements of the trading strategy like technical indicators, price patterns, entry and exit order types and general strategy design. When the prototype is finished, strategy is tested on the historical data to prove its profitability. The backtest often reveals that the strategy results are not acceptable. So the trader has to alter it, add or change some indicators, try different ideas, different values and then test it again.

It is a long trial-and-error process with numerous iterations, revisions and testing until the strategy achieves acceptable results. Now imagine you have a tool that does all this manual work for you, and does it x faster StrategyQuant requires only a fraction of the second to automatically generate new trading strategy.

It uses various combinations of technical indicators and price patterns as the entry rules, combines it with various order types market, limit, In the end it tests the new strategy on the historical data to find out if it is profitable.

StrategyQuant can do this over and over again, generating and testing tens of the new unique strategies every second! All you have to do is pick up the best ones!

Genetic Evolution takes the process of finding a suitable trading strategies even further. In this mode StrategyQuant first creates a number of random strategies, which are used as the initial population in the evolution. This initial generation of strategies is then "evolved" over successive generations using genetic programming technology.

This process imitates the evolution - the algorithm chooses the fittest strategies using selected performance criteria in every generation, and the group of fittest candidates is then used to produce new generation of trading strategies. What will you get? StrategyQuant was our best decision. We find more and more interesting opportunities with the help of the software. Since we started using StrategyQuant, we have grown from newcomers to algo trading into professionals.

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