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The apex of my CSE tenure at UIET Kurukshetra University in 2018, This project focuses on Zerodha, involving live online trading in the NSE-BSE with real money, utilizing Artificial Intelligence techniques. The project employs Python programming, incorporating live trading bots, indicator screeners, and back testers through REST API and websockets.

Home Page: https://kite.zerodha.com/dashboard

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kiteconnect zerodha api restapi websocket indicator bots trading trading-strategies trading-bot

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stock_market_live_trading_using_ai's Issues

Stock Screener

Hi.
Please help me!
I need a stock screener to scan stocks listed in KSE-100 index and return me only those stocks in which 6EMA line has crossed above 18EMA line recently (within a period of 7 days).
My email Address: [email protected]
I shall be really grateful.

Missing documentation

Hi, Where is the documentation on how to use this bot, how to setup it up / install it or even run it?

I am using Visual Studio Enterprise 2019

API KEY REQUEST

Can you please share api keys along with user id and password for KiteConnect Api? I need these urgently for my college project which is inspired by your work. I really need the api keys, I don't have 2k with me right now and the project has to be presented in this month anyhow

Contact: [email protected]

It would be really helpful if you can make some time for a phone-call, I need to talk to you about how to go ahead with the project.

New complementary tool

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 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 I am also willing, and if not file it in the box.

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