whyLucensisnotavailable
Undergraduate of Beijing Normal University
Beijing Normal UniversityBeijing, China
whyLucensisnotavailable's Stars
dunovank/jupyter-themes
Custom Jupyter Notebook Themes
viniesposito/py-mlfactor
Rewriting the code in "Machine Learning for Factor Investing" in Python
abhijeettalole75/Statistical-Analysis-And-Forecasting-of-Crypto-Tickers-for-Crypto-Treading
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 .