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Backtest telegram mesaage from whole channel about trading(as in stocks or crypto) using Mahcine Learnig (Named Entity Recognition or Token Classification) for zerodha and angel broking or for NSE or any one else.

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hemangjoshi37a/TelegramTradeMsgBacktestML

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TelegramTradeMsgBacktestML

Table of Contents

  1. Introduction
  2. Test on HuggingFace
  3. Repository Contents
  4. Custom Order
  5. Contact Information
  6. Related GitHub Repositories
  7. Other Products
  8. YouTube Videos
  9. Blog and Apps
  10. Related GitLab Repositories

Introduction

Backtest telegram messages from a whole channel about trading (stocks or crypto) using Machine Learning (Named Entity Recognition or Token Classification).


Test on HuggingFace

Model Screenshot
Link to test this model


Repository Contents

  1. Label Data using LabelStudio
    Convert:
    LabelStudio
    to:
    Labeled Data

  2. Data Conversion Script
    Convert LabelStudio CSV or JSON to HuggingFace-autoTrain dataset:
    Conversion Script

  3. Train NER Model
    Train the NER model using HuggingFace-autoTrain:
    Training

  4. Predict Labels
    Use the model to predict labels on new data in LabelStudio:
    Predict Labels
    Predictions
    Prediction Labels

  5. Python Prediction Function
    Define a Python function to predict labels using the model:
    Prediction Function
    Function Code

  6. Label New Data
    Only label new data from newly predicted-labels-dataset that has falsified labels:
    Label New Data

  7. Backtest Data
    Backtest truly labeled dataset against real historical data of the stock:
    Backtest Data

  8. Evaluate Performance
    Evaluate total gained percentage since inception summation-wise and compounded, then plot:
    Evaluate Performance

  9. Live Telegram Channel Listening
    Listen to the telegram channel for new live messages using the Telegram API for algo trading:
    Live Listening

  10. Flask API
    Serve the app as a Flask web API for web request and respond to it as labeled tokens:
    Flask API

  11. Performance Against Exchange Index
    Outperforming or underperforming results of the telegram channel tips against the exchange index by percentage:
    Performance


Custom Order

Place a custom order on hjLabs.in


📫 How to reach me

                         


Related GitHub Repositories


Other Products


YouTube Videos


Blog and Apps

Blog

Apps


Related GitLab Repositories

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Backtest telegram mesaage from whole channel about trading(as in stocks or crypto) using Mahcine Learnig (Named Entity Recognition or Token Classification) for zerodha and angel broking or for NSE or any one else.

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