Скачать или смотреть What's the BEST Way to BOOST Your Portfolio with Python

Ready to supercharge your portfolio and beat the Nifty 50? In this video, I reveal how I optimize my capital allocations to stock and trading strategies using Python with higher Sharpe ratio. I compared equal-weighted vs. mathematically optimized portfolios on top 10 stocks of Nifty 50 like Reliance, Bajaj Finance, and more.

What you'll learn:
Step-by-step Python code for downloading data from Yahoo Finance (yfinance) and optimizing with RiskFolio-Lib.
Why adjusted close prices matter for accurate backtesting.
Integrating factors like SMB, HML, and WML from India Factor Library.
Performance metrics: CAGR, volatility, and Sharpe ratio explained.
How to apply this to your portfolio for better risk-adjusted returns.

Timestamps:
00:00 - Intro: Why optimize portfolio weights?
00:58 - 01.Setup
01:39 - 02. Data
04:47 - 03. Return Calculations
06:23 - 04. Generic Factors Download
08:22 - 05. Optimization
10:20 - 06. Portfolio Construction
10:53 - 07. Performance Metrics
15:32 - 07. Final Results & Analysis
18:27 - 08. Conclusions

Download the full Python code here: https://saimohanreddy.com/python-code...

If you're into AI in finance, data science, or deploying live trading bots in Python, hit LIKE, SUBSCRIBE, and comment your questions below. What trading strategy should I cover next? Algo trading tips? Backtesting tutorials?

#PortfolioOptimization #PythonTrading #AlgoTrading #Nifty50 #SharpeRatio #QuantitativeFinance #Backtesting

Disclaimer: This is educational content, not financial advice. Past performance isn't indicative of future results. Consult a professional for investments.