ashishpapanai / stockDL
A financial deep learning library for stocks price prediction and comparison with traditional investment strategies. The Library is based on LSTM-Neural Networks and Conv1D + LSTM Neural Networks. Investments are subject to market risks, The AUTHOR HOLDS NO RESPONSIBILITY for any financial loss.
☆34Updated 3 years ago
Alternatives and similar repositories for stockDL:
Users that are interested in stockDL are comparing it to the libraries listed below
- This notebook is devoted to exploring some aspects of the Capital Asset Pricing Model (CAPM) using Python☆18Updated 5 years ago
- everything quantitative finance related☆22Updated 4 years ago
- A 3 part series of Jupyter notebooks to help one find alpha in the stock market with AI☆19Updated last year
- A collection of various computational methods to optimize a user's investment portfolio using Modern Portfolio Theory and optimizing vari…☆40Updated 4 years ago
- Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prad…☆13Updated 3 years ago
- This is a sentiment trading strategy, written in Python, and applying NLP on 10-K's from the SEC EDGAR database.☆10Updated 3 years ago
- demonstration of quantstats library☆14Updated 3 years ago
- Compilation of technical analysis tools (EMA, Bollinger bands), fundamental analysis, machine learning models (LSTM, Random forest, ARIMA…☆13Updated 3 years ago
- Developing a long/short equity investment portfolio with Machine Learning predictions using data acquired from web-scraping. Flatiron Mod…☆39Updated 4 years ago
- Machine Learning for Quantitative Finance☆24Updated 6 years ago
- Python Jupyter Notebooks for Financial Portfolio Optimization☆35Updated 6 years ago
- ☆17Updated this week
- A framework for historical volatility estimation and analysis.☆34Updated 4 years ago
- Backtesting the thesis paper entitled: Trading volatility Trading strategies based on the VIX term structure☆29Updated 2 years ago
- 📈This repo describes a framework that leverages sentiment stability of a financial 10-K report as the trading signal (alpha factor)☆11Updated 4 years ago
- Resources for the Machine Learning for Finance workshop at Texas State University (November 2022).☆16Updated 2 years ago
- This project explores stock trading modelling with the use recurrent neural network (RNN) with long-short term memory (LSTM) architecture…☆26Updated 5 years ago
- Trading Algorithms using technical indicators☆31Updated 4 years ago
- A software to shortlist and find the best options spread available for a given stock and help it visualise using payoff graphs.☆88Updated last year
- Optimization techniques on the financial area for the hedging, investment starategies, and risk measures☆41Updated 4 years ago
- Predicting index movements with Google Trends search volume alternative data☆16Updated 4 years ago
- Backtesting a simple Buy Low Sell High Strategy☆9Updated 3 years ago
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated 6 months ago
- ML Application of Algorithmic Trading☆21Updated 3 years ago
- Short Term Trading Strategy developed using technical Indicators like RSI-MACD-ADX-Bollinger Bands and study the effect of Broad Market D…☆17Updated 7 years ago
- Visualising correlations between different ETFs using network analytics and Plotly☆34Updated 2 years ago
- Codes for the paper Stock Trading Volume Prediction with Dual-Process Meta-Learning accepted by ECML PKDD 2022☆35Updated 2 years ago
- detecting regime of financial market☆35Updated 2 years ago
- By means of stochastic volatility models☆43Updated 5 years ago
- Image Classification for Trading Strategies - Project for Machine Learning Class☆38Updated 3 years ago