Neural network strategy for Gekko
copy the file(s) from /strategies/ into the strategies folder of your gekko install copy the file(s) from /toml/ into the /config/strategies/ folder of your gekko install
Install the modules in your gekko folder:
npm install convnetjs mathjs
config.NNv2 = {
threshold_buy_bear: 2.0,
threshold_buy_bull: 0.5,
threshold_sell_bear: -0.5,
threshold_sell_bull: -0.5,
NN_SMMA_Length: 4,
maFast: 20,
maSlow: 720,
decay: 0.5,
price_buffer_len: 120,
stoploss_threshold: 5
}// the neural network training method to use. Options are 'sgd', 'adagrad', 'windowgrad', 'nesterov'
method = 'adadelta'
// the treshold for buying into a currency. e.g.: The predicted price is 1% above the current candle.close
threshold_buy = 1.00
// the treshold for selling a currency. e.g.: The predicted price is 1% under the current candle.close
threshold_sell = -1.00
// The length of the candle.close price buffer. It's used to train the network on every update cycle.
price_buffer_len = 100
// The learning rate of net - not used for adadelta or adagrad
learning_rate = 0.01
// learning speed - not used for adadelta or adagrad
momentum = 0.9
//l2 decay
decay = 0.1
//minimum number of prictions until the network is considered 'trained'. History size should be equal
min_predictions = 720
//enables stoploss function
stoploss_enabled = false
//trigger stoploss 5% under last buyprice
stoploss_threshold = 0.95