LSTM-Crypto-Price-Prediction
Unverified Trend strategy on Crypto by SC4RECOIN. BotFinder score 18 out of 100.
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
Source: github
BotFinder analysis pending.
LSTM-Crypto-Price-Prediction
LSTM Crypto Price Prediction 🎯 The goal of this project is predicting the price trend of Bitcoin using an lstm-RNN. Technical analysis is applied to historical BTC data in attempt to extract price action for automated trading. The output of the network will indicate and upward or downward trend regarding the next period and will be used to trade Bitcoin throught the Binance API. requirements python-binance Keras (RNN) Scikit (polynomial interpolation) numpy scipy (savgol filter) plotly and matplotlib (if designated graphing flag is set) Label The price of Bitcoin tends to be very volatile and sporadic making it difficult to find underlying trends and predict price reversals. In order to smooth the historical price data without introducing latency, a Savitzky-Golay filter is applied. The purpose of this filter is to smooth the data without greatly distorting the signal. This is done by fitting sub-sets of adjacent data points with a low-degree polynomial by the method of linear least squares. This filter looks forward into the data so it can only be used to generate labels on historic
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