Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot

Predicting cryptocurrency price using RNN-LSTM networks

A Model to Predict any kind of price such as Crypto price or Stock price using LSTM network and python

Cryptocurrency price prediction based on LSTM and FinBERT sentiment analysis

[Python] Adopted Neural Network (LSTM), Time Series (ARIMA) and Sentiment Analysis (NLP) to predict Bitcoin prices

A Flask app to predict the future prices of various Crypto Currencies implemented various supervised and deep learning algorithms such as LSTM (RNN), polynomial regression, using scikit-learn, tensorflow, keras etc.

The goal of this study is to predict prices for Cryptocurrencies using Time series analysis and machine learning techniques. The purpose of this project is to take a sneak peek into the future by forecasting the next 30 days' average daily Realized Volatility (RV) of ETH-BTC using 2 different approaches - the traditional econometric approach to volatility prediction of financial time series GARCH and state-of-the-art LSTM Neural Networks. Quantitative research methodology was used in this study and the The dataset Consist the historical data values of any any crypto-pair such as Open/Close/High/Low prices of any interval such as 15-minutes, Hourly, 1-day interval weekly, monthly. Dataset were obtained using the Binance API .

A LSTM Linear Regression model which is trained to predict the price of crypto currencies. The dataset used here was downloaded from finance.yahoo.com. The dataset contains five years of data. The crypto currency used here was BTC INR. The accuracy with the test data was above 95%.

"LSTM Stock & Crypto Predictor"

Jupyter notebook implementing an LSTM-based cryptocurrency price predictor on log-return data, complete with performance visualizations.

This project aims to demonstrate how to use the yfinance library to obtain historical cryptocurrency data and use it to train an LSTM model to predict future closing prices. The Ethereum-USD (ETH-USD) pair is used as an example, but the same approach can be applied to other cryptocurrencies and financial assets.

We are attempting to use LSTM models that handle time-series data to predict the periods when the strategy will be profitable or non profitable. By determining when to activate or deactivate the strategy based on these predictions, can we reduce the instances of losses and further improve the performance of the breakout strategy?

CSE475 (ML) Project to create a forecasting script with pyTorch using LSTM and Transformers

MLP, LSTM, Transformers models are used to predict the crypto market on the historic price data using social media sentiment data. Hugging Face Sentiment analyzer is used to extract the sentiment of social media posts

Agent-X is a revolutionary, self-evolving autonomous crypto trading bot that deploys a hybrid strategy merging an LSTM price predictor with a technical indicator set to empower the agent with foresightful trading decisions, enhanced by EvoSearch optimiser. It harnesses a Kelly Criterion feature to auto-calibrate risk & scaling dynamically.

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Use an LSTM RNN to predict bitcoin closing prices using historical price data and the Crypto Fear and Greed Index.

A LSTM Linear Regression model which is trained to predict the price of crypto currencies. The dataset used here was downloaded from finance.yahoo.com. The dataset contains five years of data. The crypto currency used here was BTC INR. The accuracy with the test data was above 95%.

Predict Bitcoin prices with ML & DL models! 📈 Uses Ridge, Lasso, Random Forest, MLP, RNN & LSTM with hyperparameter tuning. 📊 Visualizes predictions & ROC curves. 🚀 Fetch data via yfinance, evaluate with MSE/R2. Perfect for crypto enthusiasts! 💸

predict Crypto price with LSTM

LSTM-based cryptocurrency price trend predictor. Features: custom LSTM with attention, technical indicators, data preprocessing, configurable pipeline, and classification metrics. Forecasts short-term crypto trends (up/down/neutral) using historical data.

LSTM-based model predicting hourly cryptocurrency prices using Yahoo Finance data. Includes data fetching, feature engineering with technical indicators, and model training. Designed as a training project with potential for integration into apps like Telegram bots.

Crypto Price Prediction with LSTM uses machine learning and LSTM neural networks to forecast Bitcoin (BTC-USD) prices based on historical data. This project is for educational purposes only and should not be used for actual financial decisions due to cryptocurrency market volatility.

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LSTM, TimeSeries predict ETH Crypto, input = 60 Days, output = 3 Days.

Stock and Crypto Price Prediction with TensorFlow, LSTM, Linear Regression and Streamlit

Predicting popular cryptocurrency prices with LSTM and other analyses on stock and crypto prices

A high performance computer that predicts Bitcoin, BNB and Ethereum crypto currencies using LSTM machine learning algorithm.

real-time AI system predicting short-term market volatility and micro-movements in stocks & crypto. LSTM & Transformer powered