In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to use various regression methodologies for investment management that you might need to do in your job every day and make you ready for more advanced topics in machine learning. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics and R programming. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. Students are also expected to know of the instructors' 1st course, 'Fundamental of data-driven investment.' The instructor will explain the detail of R programming. It will be an excellent course for you to improve your programming skills but you must have basic knowledge in R. If you are very good at R programming, it will provide you with an excellent opportunity to practice again with finance and investment examples.

Discounted cash flow method means that we can find firm value by discounting future cash flows of a firm. That is, firm value is present value of cash flows a firm generates in the future. In order to understand the meaning of present value, we are going to discuss time value of money, first. That is, the value of $100 today is different from the value of $100 a year later. Then, what should be the present value of $100 that you are going to receive in 1 year? How about the value of $100 dollars that you are going to receive every year for next 10 years? How about forever? After taking this course, you are going to be able to find the present value of these types of cash flows in the future. Unlike most of finance courses, in this course, you are going to learn how to use excel to find present value of future cash flows. In addition to the present value, you are also going to learn how to find future value given investment; interest rate given investment and future cash flows, payments given interest rates, number of periods to wait given investment and interest rate, and so on. After learning the concept and how to find the time value of money, you are going to apply this to real world examples and company valuation. After taking this course, you will be ready to make an estimate of firm value by discounting its cash flows in the future.

In this course, the instructor will discuss the fundamental analysis of investment using R programming. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to do the elemental analysis for investment management that you might need to do in your job every day. Additionally, the study note to do using Python programming will be provided. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. The instructor will explain the detail of R programming for beginners. It will be an excellent course for you to improve your programming skills. If you are very good at R programming, it will provide you an excellent opportunity to practice again with finance and investment examples. Professor Youngju Nielsen creates the course with the assistants of Keonwoo Lim and Jeeun Yuen. =========================================================================================== Coursera Course recommendations before this course for those who are not familiar with basic R programming: <Getting Started with R> https://www.coursera.org/projects/getting-started-with-r <Introduction to Business Analytics with R> https://www.coursera.org/learn/business-analytics-r <Statistics with Python > https://www.coursera.org/specializations/statistics-with-python

This course is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Incorporating real-life case studies, this course covers both the technical and the “soft skills” necessary for investment professionals to stay relevant. In this course, you will learn how to: - Distinguish between supervised and unsupervised machine learning and deep learning - Describe how machine learning algorithm performance is evaluated - Describe supervised and unsupervised machine learning algorithms and determine the problems they are best suited for - Describe neural networks, deep learning nets, and reinforcement learning - Choose an appropriate machine learning algorithm - Describe the value of integrating machine learning and data projects in the investment process - Work with data scientists and investment teams to harness information and insights from within large and alternative data sets - Apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas This course is part of the Data Science for Investment Professionals Specialization offered by CFA Institute.

How do different types of investors think about an investment opportunity? What kind of securities and contracts do they offer? How should a company decide what is a "good deal"? This course is designed to introduce you to the challenges and pitfalls of financing new enterprises. You will learn the basic tools for valuating companies, including using discounted cashflow analysis in Excel and understanding how to apply this model to your entrepreneurial venture. You will then learn how valuation works with different types of securities that investors use to finance startups, from bank loans to venture capital to angel investing.

In this course, will look at industries and economic sectors that neatly define an economy. We will also introduce you to fundamental concepts involved in a company’s annual statements such as balance sheets, cash flows and its income statement, plus explore popular fundamental values used to filter vast amounts of corporate stocks. And finally, we’ll examine mutual funds and ETFs as alternatives to individual stocks for investing. To facilitate a comprehensive understanding of essential concepts discussed, this course includes a series of practical examples, quizzes, reading materials and a final course project.

By the end of the project, you will be able to apply correlation matrix in portfolio diversification. ATTENTION: To take this course, it is required that you are familiar basic financial risk management concepts. You can gain them by taking the guided project Compare Stock Returns with Google Sheets. Note: This course works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions. This course's content is not intended to be investment advice and does not constitute an offer to perform any operations in the regulated or unregulated financial market

In this first course of the specialization, we will discuss the limitations of the Internet for business and economic activity, and explain how blockchain technology represents the way forward. After completing this course, you will be able to explain what blockchain is, how it works, and why it is revolutionary. You will learn key concepts such as mining, hashing, proof-of-work, public key cryptography, and the double-spend problem. You’ll be able to describe seven design principles for blockchain technology, and the challenges facing the people developing it. You’ll also meet the players in the blockchain ecosystem, and consider your own role in stewarding the blockchain revolution.

Investors tend to be their own worst enemies. In this third course, you will learn how to capitalize on understanding behavioral biases and irrational behavior in financial markets. You will start by learning about the various behavioral biases – mistakes that investors make and understand their reasons. You will learn how to recognize your own mistakes as well as others’ and understand how these mistakes can affect investment decisions and financial markets. You will also explore how different preferences and investment horizons impact the optimal asset allocation choice. After this course, you will be more effective in overcoming biases to do the wrong things at the wrong times and tailoring an investment strategy that is best suited on your or your client’s profile and investment needs.

Today, large intermediaries establish trust in our economy and control the movement, storage, and allocation of money and assets. The status quo, however, is rife with inefficiencies. In this course, we’ll address the many challenges of the status quo and discuss how cryptoassets, smart contracts, new identity systems, and new financial business models can help overcome them. You’ll learn how blockchain technology empowers individuals, entrepreneurs, and businesses with the tools they need to help level the playing field and to participate in the value they create. By the end of this course, you’ll learn how and why transacting on the blockchain can help us bring about a future that is faster, fairer, and more distributed than the world we inhabit today.