We have already implemented a lot of interesting things in the previous articles. We have a trading strategy or several trading strategies that we can implement in the EA. Besides, we have developed a structure for connecting many instances of trading strategies in a single EA, added tools for managing the maximum allowable drawdown, looked at possible ways of automated selection of sets of strategy parameters for their best work in a group, learned how to assemble an EA from groups of strategy ...
In the previous articles, we have seen how powerful both Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are and how they can be deployed to help beat the market by providing us with valuable trading signals. In this one we are going to attempt combining two of the most powerful techniques CNN and RNN and observe their predictive impact in the stock market. But before that let us briefly understand what CNN and RNN are all about. more...
We will analyze all of Deriv’s synthetic markets individually, starting with their best known synthetic market, the Boom 1000. The Boom 1000 is notorious for its volatile and unpredictable behavior. The market is characterized by slow, short and equally sized bear candles that are randomly followed by violent, skyscraper sized bull candles. The bull candles are especially challenging to mitigate because the ticks associated with the candle normally aren’t sent to the client terminal, meaning ...
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