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How to move towards Quantitative Trading :

1) Learn Python
2) Learn key trading libraries & Pandas
3) Data visualisation using seaborn & matplotlib
3) Statistics for Financial Markets
4) Backtest your strategies
5)Optimise & Automate
6) ML insights for trading

#quant #trading
1) This is a good basic course on Udemy to learn about Python required for trading

udemy.com/course/python-…

#python
2) Learn about Pandas( cruciwl for data cruncing & handling time series data)
learnpython.org/en/Pandas_Basi…

Also install talib: an essential library for a trader. It has inbuilt functions for all technical indicators making our life easy.

mrjbq7.github.io/ta-lib/doc_ind…

#pandas
3) Learn about Matplotlib & seaborn

It is required for data visualisation and helps in interpreting data.

edureka.co/blog/python-ma…
4) Statistics

If you want to be a quant trader, you need to know basic statistics such as normal dist., correl,cointegration,std dev,beta etc and also few probability concepts.

These are useful in creating option writing strategies based on volatility

khanacademy.org/math/statistic…
5) Backtesting
This is the crux of quant trading. Discard or accept your ideas by doing a detailed backtest.

Test across different market conditions and stress test on black swan days to check robustness of the strategy

Backtrader:
backtrader.com

#backtest
6) Optimise & Automate

Try to remove your emotions by automating your strategies using API

kite.trade/individuals

This is difficult to do if your are a newbie as several risk management parameter needs to be considered.
7) Machine Learning

ML can provide data insights to refine existing strategies.
ML is a vast subject in itself so you can skip this if your are new to coding.
analyticsvidhya.com/blog/2015/06/m…
#DataScience #MachineLearning
8) If you want to fast track the learning process:

You can join our Quantitative Trading Program. We have conducted this at large multi-million dollars trading desks.
Check brochure for details:
drive.google.com/file/d/1pLgtoe…

If interested can connect with team on +91 89283 81567
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