New complementary tool
Leci37 opened this issue · 2 comments
My name is Luis, I'm a big-data machine-learning developer, I'm a fan of your work, and I usually check your updates.
I was afraid that my savings would be eaten by inflation. I have created a powerful tool that based on past technical patterns (volatility, moving averages, statistics, trends, candlesticks, support and resistance, stock index indicators).
All the ones you know (RSI, MACD, STOCH, Bolinger Bands, SMA, DEMARK, Japanese candlesticks, ichimoku, fibonacci, williansR, balance of power, murrey math, etc) and more than 200 others.
The tool creates prediction models of correct trading points (buy signal and sell signal, every stock is good traded in time and direction).
For this I have used big data tools like pandas python, stock technical patterns market libraries like: tablib, TAcharts ,pandas_ta... For data collection and calculation.
And powerful machine-learning libraries such as: Sklearn.RandomForest , Sklearn.GradientBoosting, XGBoost, Google TensorFlow and Google TensorFlow LSTM.
With the models trained with the selection of the best technical indicators, the tool is able to predict trading points (where to buy, where to sell) and send real-time alerts to Telegram or Mail. The points are calculated based on the learning of the correct trading points of the last 2 years (including the change to bear market after the rate hike).
I think it could be useful to you, to improve, I would like to share it with you, and if you are interested in improving and collaborating we could, who knows how to make beautiful things.
Thank you for your time
I'm sorry to contact you here ,by issues, I don't know how I would be able to do it.
mail : leciluis@gmail.com or https://github.com/Leci37/stocks-Machine-learning-RealTime-telegram/discussions
would be to combine the power of https://github.com/huseinzol05/Stock-Prediction-Models predictive models with https://github.com/Leci37/stocks-Machine-learning-RealTime-telegram/tree/develop real-time pattern calculation and alerting capabilities.
If you have problems with installation, let me know. I am searching collaborators for this project. If you have experience and want to collaborate text me on email or github Issues
Why this stock prediction project ?
Things this project offers that I did not find in other free projects, are:
Testing with +-30 models. Multiple combinations features and multiple selections of models (TensorFlow , XGBoost and Sklearn )
Threshold and quality models evaluation
Use 1k technical indicators
Method of best features selection (technical indicators)
Categorical target (do buy, do sell and do nothing) simple and dynamic, instead of continuous target variable
Powerful open-market-real-time evaluation system
Versatile integration with: Twitter, Telegram and Mail
Train Machine Learning model with Fresh today stock data