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via Udemy |
Go to Course: https://www.udemy.com/course/python-for-algorithmic-trading-technical-indicators/
Certainly! Here is a detailed review and recommendation for the Coursera course based on the provided information: --- **Course Review and Recommendation: Algorithmic Trading with Python** Are you already familiar with Python and eager to explore ways to monetize and diversify your skills? Do you have some trading knowledge and want to dive into algorithmic trading? Or are you simply curious about this exciting field? If you answered "yes" to any of these questions, then this course is an excellent opportunity for you. **Course Overview:** This course is designed to guide learners from basic Python knowledge to creating, backtesting, and implementing trading strategies using Python. Whether you're a beginner in programming or a trader looking to automate and optimize your strategies, this course offers practical, hands-on learning. **What You Will Learn:** - A quick but effective Python crash course tailored for trading applications - How to program trading strategies from scratch, focusing on widely used technical indicators like RSI - Techniques to combine strategies for better risk and return profiles using portfolio optimization methods such as Sortino ratio, Min Variance, and Mean-Variance optimization - Backtesting strategies to evaluate their performance using quantitative metrics like Sortino ratio, drawdowns, and beta - Implementation of live trading, including data import, reference algorithms, and understanding trading risks **Key Tools Covered:** - Python libraries: Numpy, Pandas, Matplotlib - Financial concepts: Long and short positions, diversification, alpha and beta coefficients, Sharpe and Sortino ratios - Advanced portfolio optimization methods like skewness and kurtosis optimization **Why Choose This Course?** Unlike typical programming or trading courses, this course specifically focuses on using programming as a tool for algorithmic trading. Created by a professional with a background in mathematics, economics, and machine learning for finance, it ensures a rigorous and practical approach. Moreover, if you're new to Python, the small yet comprehensive Python module will prepare you adequately for the coding tasks ahead. **Additional Benefits:** - Access to a vibrant community via a free Discord forum for questions and discussions - 30-day satisfaction or refund guarantee **Final Verdict:** This course is highly recommended for anyone interested in bridging the gap between programming and financial trading. It’s practical, well-structured, and backed by expertise in quantitative finance and machine learning. Whether you want to enhance your trading strategies, learn the fundamentals of algorithmic trading, or explore new ways to leverage Python in finance, this course provides the necessary tools and knowledge. **Recommendation:** If you are motivated to learn how to develop, backtest, and deploy automated trading strategies, enrolling in this course will be a valuable investment. It offers a perfect balance between theoretical concepts and practical application, making it suitable for traders, programmers, and curious minds alike. --- Would you like a shorter summary or help with anything else?
You already have knowledge in python and you want to monetize and diversify your knowledge?You already have some trading knowledge and you want to learn about algorithmic trading?You are simply a curious person who wants to get into this subject?If you answer at least one of these questions, I welcome you to this course. For beginners in python, don't panic there is a python course (small but condensed) to master this python knowledge. In this course, you will learn how to program strategies from scratch. Indeed, after a crash course in Python, you will learn how to implement a strategy based on one of the most used technical indicators: the RSI. You will also learn how to combine strategies to optimize your risk/return using the portfolio techniques like Sortino portfolio optimization, min variance optimization, and Mean-Variance skewness kurtosis Optimization.Once the strategies are created, we will backtest them using python. So that we know better this strategy using statistics like Sortino ratio, drawdown the beta.Then we will put our best algorithm in live trading.You will learn about tools used by both portfolio managers and professional traders:Live trading implementationImport the dataSome reference algorithmsHow to do a backtestThe risk of a stockPythonWhat is a long and short positionNumpyPandasMatplotlibWhy do you must diversify your investmentsSharpe ratioSortino ratioAlpha coefficientBeta coefficientSortino Portfolio OptimizationMin variance OptimizationMean-Variance skewness kurtosis OptimizationWhy this course and not another?This is not a programming course nor a trading course. It is a course in which programming is used for trading.This course is not created by a data scientist but by a degree in mathematics and economics specialized in Machine learning for finance.You can ask questions or read our quantitative finance articles simply by registering on our free Discord forumWithout forgetting that the course is satisfied or refunded for 30 days. Don't miss an opportunity to improve your knowledge of this fascinating subject.