We are the Anchain.ai Bitcoin Price Prediction team from UC Berkeley's Data-X course. Our product is called BTC Predictor.

Predict any cryptocurrency with any pair (USDT/ETH/BTC/BNB/ETC) on Binance through Deep Learning (commonly known as Artificial Intelligence for those who do not know the difference between AI/Ml/Dl).

Predicting the behavior of $BTC-USD by training a memory-based neural net on historical data

Openclaw 🦞 AI Polymarket Trading Bot — TypeScript bot built with Openclaw AI agent. Predicts crypto price on Polymarket 5m BTC Up/Down markets and tracks results (paper or live) and automatically executes trading according to the prediction result.

This project leverages the Binance API to acquire real-time data for Bitcoin (BTC) and Ethereum (ETH). The data is then used to train a Long Short-Term Memory (LSTM) neural network model for predicting cryptocurrency prices.

Project shows that real-time Twitter data can be used to predict market movement of Bitcoin Price. The goal of this project is to prove whether Twitter data relating to cryptocurrencies can be utilized to develop advantageous crypto coin trading strategies. By way of supervised machine learning techniques, have outlined several machine learning pipelines with the objective of identifying cryptocurrency market movement. The prominent alternative currency ex- amined in this paper is Bitcoin (BTC). Our approach to cleaning data and applying supervised learning algorithms such as logistic regression, Decision Tree Classifier, and LDA leads to a final prediction accuracy exceeding 70%. In order to achieve this result, rigorous error analysis is employed in order to ensure that accurate inputs are utilized at each step of the model.

💰 Bitcoin price guessing game - High/Low in 10 seconds.

This repository contains a Python script that fetches historical Bitcoin (BTC) price data, calculates technical indicators, and applies a trading strategy based on machine learning. The purpose of the script is to assess the performance of the strategy using the XGBoost algorithm, which predicts long, short, or neutral positions.

Python tutorial for predicting the price of BTC using regression models.

Predict prices of BTC and ETH with TensorFlow and Keras

Implemented a trading strategy using XgBoost to create a predictive model on the direction and variations of the BTC/USDT pair.

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 .

Predicts Bitcoin prices using RNN LSTM

Predict BTC, SOL, ETH, GOLD prices

FactorModel & TimeSeries Analyze For Predicting BTC, ETH.

This repository contains implementations of Long Short-Term Memory (LSTM) models for predicting the closing prices of three major cryptocurrencies: Bitcoin (BTC), Solana (SOL), and XRP. The project leverages historical OHLC data to train deep learning models capable of forecasting future price trends.

Information Flow in Crypto Order-Books | This repository uses ML models to predict the future price of ETH based on order books of ETH and BTC.

A sophisticated Rust-based trading bot for Polymarket, kalshi, predict.fun that monitors BTC and ETH 15-minute price prediction markets and executes momentum-based trades when opportunities are detected.

Options Spreads Trading Bot using LSTM to predict BTC prices, then executing optimal trades with Selenium automation on CME trade simulator. Won 3rd place against humans in UIUC SP22 Trading Challenge.

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%.

Program which connects to the Binance API to predict BTC price movements using the XGBoost machine machine learning library. Predictions are applied on the current prices to purchase or sell BTC in personal wallet.

predicting BTC/USD price

Using a LSTM Deep Learning model to predict future market opening prices of BTC/USD using timesteps. Comprehensive backtesting illustrating Cumulative returns, average holding time, maximum loss and profit attained by the trading model. Risk management techniques for stop-loss orders and position sizing are also included.

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Predict BTC Price target using machine learning classification algorithm

A Python script using LSTM to predict BTC prices. By using streamlit user can interact with the model.

Created a bot for trading BTC-USDT cryptocurrency. Used lagged features, Time-Series, XGBoost and Linear Regression to predict the final value of bitcoin. Received 98% APY (annual return) on cross-validation.

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%.

Built an AI model for the Allora Forge competition to predict 1-day BTC/USD log returns using the Allora Model Development Kit. Worked with a teammate who sourced resources while I handled the machine learning. Tested across multiple phases using insights from various GitHub repos and documented progress.

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