Machine Learning for Smart Beta from Coursera

What's inside

Syllabus

Week 1

Building on the concepts learned in previous courses 'The Fundamental of Data-Driven Investment' and 'Using R for Regression and Machine Learning in Investment', this course will cover 'Smart beta'. Smart betas products have the characteristics of both passive investment(having predetermined rules) and active investments(allows for factor investment). Smart beta products' investment mechanisms are open to the public, so we will recreate a MSCI smart beta product in R. Follow along the step-by-step reconstruction of the MSCI Enhanced Value Index and create your own smart beta portfolio.

Week 2

In order to effectively utilize machine learning in investment, it is important to understand the various characteristics of data. This module covers how to check the prediction accuracy of a machine learning model and prevent overfitting. Get hands on experience in R to manipulate data into a form suitable for machine learning models from regression models to classification trees.

Week 3

The asset selection method based on a score derived from a benchmark index has the problem that the selected assets do not reliably capture underlying information. To solve this problem, a non-traditional method, namely machine learning is used to create an improved multi-factor approach. Familiarize yourself with CART(Classification and Regression Tree), bagging, boosting and ensemble methods to enhance your smart beta portfolio in R.

Week 4

In this final module, we wrap up the discussion by creating a multifactor model applying all the knowledge we have learned so far. Investors have taken a steady interest in multifactor models that take into account the cyclicality of factors. Further, we expand the discussion into the use of factors in bond investment and a new method of active factor allocation.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Addresses Smart Beta products' construction methods, offering hands-on experience in replicating one

Incorporates machine learning methodologies for factor selection and model enhancement, providing practical experience

Utilizes R programming, catering to those familiar with data analysis and statistical modeling

Enhances understanding of data characteristics and overfitting prevention techniques

Delves into advanced asset selection methods using CART, bagging, boosting, and ensemble approaches

Assumes familiarity with fundamental concepts of data-driven investment and R programming

Career center

Learners who complete Machine Learning for Smart Beta will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine learning engineers develop and implement machine learning models. They work with data scientists to identify the best models for a given problem, and they build the software to implement these models. This course can help you develop the skills you need to be a successful machine learning engineer. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a machine learning engineer.

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Portfolio Manager

Portfolio managers are responsible for managing the investments of their clients. They make decisions about which stocks, bonds, and other investments to buy and sell. This course can help you develop the skills you need to be a successful portfolio manager. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a portfolio manager.

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Risk Manager

Risk managers are responsible for identifying and managing the risks associated with investments. They develop strategies to mitigate these risks and protect the value of their clients' portfolios. This course can help you develop the skills you need to be a successful risk manager. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a risk manager.

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Financial Analyst

Financial analysts use their knowledge of the financial markets to help companies make investment decisions. They may also provide advice to individuals on how to invest their money. This course can help you develop the skills you need to be a successful financial analyst. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a financial analyst.

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Quantitative Analyst

Quantitative analysts use mathematical and statistical techniques to analyze financial data. They develop models to predict the performance of stocks, bonds, and other investments. This course can help you develop the skills you need to be a successful quantitative analyst. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a quantitative analyst.

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Investment Analyst

Investment analysts provide research and analysis on companies and industries to help investors make informed investment decisions. This course can help you develop the skills you need to be a successful investment analyst. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as an investment analyst.

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Data Scientist

Data scientists use their knowledge of mathematics, statistics, and computer science to solve business problems. They develop algorithms to analyze data and extract insights. This course can help you develop the skills you need to be a successful data scientist. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a data scientist.

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Software Engineer

Software engineers design, develop, and maintain software systems. They work with users to understand their needs and develop software that meets those needs. This course can help you develop the skills you need to be a successful software engineer. You will learn how to use R programming to analyze financial data, and you will gain experience in using machine learning to create investment models. This course can help you build a foundation for a career as a software engineer.

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Trader

Traders buy and sell stocks, bonds, and other financial instruments for their own account or for the account of their clients. This course can help you develop the skills you need to be a successful trader. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a trader.

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Statistician

Statisticians use their knowledge of mathematics and statistics to collect, analyze, and interpret data. They develop models to predict future events and make informed decisions. This course can help you develop the skills you need to be a successful statistician. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a statistician.

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Data Analyst

Data analysts use their knowledge of mathematics, statistics, and computer science to analyze data and extract insights. They develop models to predict future events and make informed decisions. This course can help you develop the skills you need to be a successful data analyst. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a data analyst.

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Actuary

Actuaries use their knowledge of mathematics and statistics to assess risk and uncertainty. They develop models to predict the likelihood of future events, such as death, disability, and retirement. This course can help you develop the skills you need to be a successful actuary. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as an actuary.

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Investment Banker

Investment bankers help companies raise money by issuing stocks and bonds. They also advise companies on mergers and acquisitions. This course can help you develop the skills you need to be a successful investment banker. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as an investment banker.

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Economist

Economists study the production, distribution, and consumption of goods and services. They develop models to explain economic behavior and predict economic outcomes. This course can help you develop the skills you need to be a successful economist. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as an economist.

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Financial Advisor

Financial advisors provide financial advice to individuals and families. They help their clients make informed decisions about their investments, retirement planning, and other financial matters. This course can help you develop the skills you need to be a successful financial advisor. You will learn how to use machine learning to create investment models, and you will gain experience in using R programming to analyze financial data. This course can help you build a foundation for a career as a financial advisor.

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Machine Learning for Smart Beta

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