Dive into the world of quantitative analysis in trading and learn how to turn historical market data into actionable insights. This video introduces the basics of Python for trading, covering data acquisition, statistical analysis, pattern identification, and strategy backtesting. Discover how to analyze price trends, build predictive models, and visualize your results using Python's powerful libraries. Perfect for beginners ready to explore trading automation and quantitative strategies, this session will guide you step-by-step into creating your first algorithmic trading strategy!
🔍 Key Highlights:
Basics of Python for trading
Data analysis and visualization
Statistical methods for trading insights
Backtesting trading strategies
Turning patterns into profitable trades
🚀 Perfect For: Beginners and professionals eager to explore trading automation and quantitative trading strategies. Follow along to create your own algorithmic trading strategy using Python's robust libraries like Pandas, NumPy, and Matplotlib.
🎓 Additional Learning Resources:
▶️ Trading in the Age of AI: How to Stay Ahead! https://www.youtube.com/live/nLtudB57...
▶️ ChatGPT and Algo Trading: Exploring Opportunities & Challenges https://www.youtube.com/live/RswCmPFn...
▶️ Full Algorithmic Trading Python Course: https://bit.ly/4bGQF9e
📚 FREE Ebooks:
🎁 Machine Learning In Trading | Step-By-Step Implementation of ML Models: https://bit.ly/4bGQF9e🎁 Algorithmic Trading | A Rough & Ready Guide: https://bit.ly/3UGgTms🎁 Python Basics | With Illustrations From Financial Markets: https://bit.ly/49BP1UQ
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About the Speaker:
Vivek Krishnamoorthy has straddled the worlds of industry and academia. Previously, he worked as a credit analyst in Corporate & Institutional Banking with ICICI Bank in Singapore and India. At EPAT, Vivek helps the participants learn to backtest trading strategies in Python, and time series modelling.
Vivek has also worked as an assistant professor of finance at SIBM, Pune. He has conducted numerous corporate training sessions for mid and senior-level executives in corporate finance, financial modelling, and portfolio theory at Larsen & Toubro, Credit Suisse, and other organizations.
When he was a research scholar at McMaster University, Canada, he taught economics and finance courses to undergraduate and graduate students there. He is the co-author of the books, “Python Basics: With illustrations from the Financial Markets (2019)” and “A rough-and-ready guide to algorithmic trading (2020)”.
He has a Bachelor’s in Electronics & Telecom Engineering from VESIT (Mumbai University) and an MBA from Nanyang Technological University (NTU), Singapore.
Take the next step in your trading journey!
🔗 Explore the Executive Programme in Algorithmic Trading (EPAT) today: https://bit.ly/47Cwrdu
Keywords: Quantitative Trading, Python Trading, Algo Trading, Trading Strategies, Quantitative Analysis, Backtesting, Machine Learning, Financial Markets, Python For Trading, EPAT, Quant Strategies, Data Analysis, Predictive Models, Financial Engineering, Algorithmic Trading Insights
Hashtags:
#QuantTrading #PythonTrading #AlgoTrading #TradingStrategies #QuantitativeAnalysis #Backtesting #MachineLearning #FinancialMarkets #PythonForTrading #EPAT #TradingAutomation #DataScience #FinanceTools #QuantResearch #AlgoTrader #TradeSmart #FinancialFreedom #StockMarkets #InvestmentStrategy
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