Linkedin – Algorithmic Trading and Finance Models with Python, R, and Stata Essential Training 2025-1

Algorithmic Trading and Finance Models with Python, R, and Stata Essential Training. In today’s world, many stock market transactions are carried out using algorithms, or “models,” which are computer programs that buy or sell stocks based on mathematical formulas. The speed and frequency of these transactions are very high and beyond human ability. For anyone who works in the stock market, understanding how these algorithms work is very important. In this course, Professor Michael McDonald teaches you how to develop a tested, rules-based trading strategy and program a simple trading algorithm yourself. Professor McDonald first covers the basics of securities markets, including stocks, bonds, and derivatives, and then discusses predicting values ​​using regression. He then discusses investment and securities principles. You will learn how to build your own algorithms, trade them, and extend them to other securities. In addition, Professor McDonald covers practical examples and case studies of trading using algorithms.

What you will learn:

• Algorithmic Trading: A Deep Understanding of How Trading Algorithms Work
• Python (programming language): Learn the Python programming language to implement algorithms.
• R (Programming Language): Introduction to the R programming language for financial data analysis
• Building and developing trading algorithms: Ability to build and improve trading algorithms
• Testing and evaluating trading strategies: evaluating the performance of algorithms and optimizing them

Who is this course suitable for?

• Financial analysts
• Investors
• Finance and economics students
• Programmers interested in finance

Algorithmic Trading and Finance Models with Python, R, and Stata Essential Training Course Details

• Publisher: Linkedin
• Instructor: Michael McDonald
• Education level: Intermediate
• Training duration: 2 hours and 57 minutes

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Sample course video

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Download file – 323 MB

File(s) password: www.downloadly.ir

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323 MB