How to download Bonus split dividend buy back data from NSE using python | Corporate Actions
Mar 20, 2025
π Algo Traders! Want to automate corporate actions data from NSE?
In this video, I'll show you how to extract Bonus, Splits, Dividend, and Buyback data directly from the NSE (National Stock Exchange of India) using a simple Python utility. This data is crucial for backtesting, event-driven trading, and portfolio management.
Download the Python source code from our community website (link below):
https://fabtrader.in/how-to-fetch-corporate-actions-data-bonus-splits-dividends-buy-back-from-nse/
Watch full playlist of all videos relating to Downloading live data from NSE:
https://www.youtube.com/playlist?list=PLrlkL2FbEO3FnCAbl6a2D87Rq2Ty36zTb
#AlgoTrading #NSEIndia #PythonTrading #CorporateActions #BonusShares #StockSplit #DividendStocks #TradingStrategy #Buyback #StockMarketIndia
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About Me π
My name is Vivek! I achieved my Financial Freedom in 2022 and am an avid Algo Trader. I I am passionate about Trading, Investing and building wealth, which helped me in my F.I.R.E journey.
About FabTrader π₯
Fabtrader is an humble effort to create a community of like-minded individuals who are passionate about alog trading using python. I share my journey, trading and investment strategies, tools and the methods that I personally use. So, whether youβre a budding programmer, an aspiring trader, or someone dreaming of financial independence, youβre not alone. Together, weβll decode the complex algorithms of personal finance. Please join me in building this community, something remarkable, Together!
Disclaimer π’
The content posted on this channel is based on my personal experiences and meant for educational purposes only. None of it should be construed as investment action or advice. I am not registered with the SEBI, IRDAI, PFRDA or related authorities. Investing involves risks, including the loss of principal. Always conduct your own research and consult a qualified financial advisor before making any investment decisions. FabTrader assume no liability for any financial losses or decisions made based on the information presented
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