| Sumario: | R is a high-level statistical language and is widely used among statisticians and data miners to develop statistical applications. This complete hands-on course will help you code some finance and ML projects. In the first section of the course, you will learn some basic things to look at in money management, something very simple, something everybody knows and yet not many people start with. In the second section, you will look at stock market timing and focus on the coding aspect of how the algorithm is designed, then will land on the video on how to use the algorithm. We will also discuss soft thresholds and extend the market timing concept to a generalized framework. In the last section of the course, you will understand Asset Pricing. We will try to answer questions such as What is market beta? What is Capital Asset Pricing Model? Why do we pay attention to the market coefficient? How to construct an efficient portfolio? We will also look at the growth strategy. We will be looking at our data and every period we are going to pick a few TOP performing stocks by looking at the returns of these stocks within the period. In the next period, we are simply going to hold these stocks. By the end of the course, we are going to talk about how to build a web-based application so that we can come up with a software platform for clients to use. What You Will Learn Learn how to time the stock market using probability theory Explore the qualitative nature of stock market timing Know the quantitative nature of stock market timing Learn the basics of asset pricing theory Learn the intermediate and advanced asset pricing practices Build trade-able factor-based algorithms Audience This course is for financial and technology enthusiasts, beginners in programming, and people interested in statistics and data analysis. No programming experience is needed as you will learn everything from this course. About The Author Yiqiao Yin: Yiqiao Yin was a Ph.D. student in statistics at Columbia University from September of 2020 to December 2021. He has a B.A. in mathematics and an M.S. in finance from the University of Rochester. He also has a wide range of research interests in representation learning: Feature Learning, Deep Learning, Computer Vision, and (NLP). Yiqiao Yin is a senior data scientist at an S&P 500 company LabCorp, developing AI-driven solutions for drug diagnostics and development. He has held professional positions as an enterprise-level data scientist at EURO STOXX 50 company Bayer, a quantitative researcher at AQR working on alternative quantitative strategies to portfolio management and factor-based trading, and equity trader at T3 Trading on Wall Street.
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