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| Name | Python Tutorial: Welcome to Portfolio Analysis! |
| Video Uploader | Video From DataCamp |
| Upload Date | This Video Uploaded At 18-04-2020 00:02:13 |
| Video Discription | Want to learn more? Take the full course at https://learn.datacamp.com/courses/introduction-to-portfolio-analysis-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Welcome to this course on portfolio analysis. My name is Charlotte and I want to teach you how to analyze portfolios. Having worked as a portfolio manager in the asset management industry, I know how important it is to critically look at portfolios, in order to make the right investment decisions. In this course I will show you what to look for when analyzing portfolios, and how to create optimal portfolios for given levels of risk and return. Investing in the stock market is risky as the value of stock prices can fluctuate heavily. Because of the inherent risk involved with investing in a single stock, most professional portfolio managers diversify their investments to reduce their risk from exposure to any one company. By investing in a collection of stocks, also called a portfolio, investors typically can get a better risk-reward trade-off. So why then, do we need portfolio analysis? Well, when you invest in 1 stock, you easily can calculate the risk and possible pay-off. However, when you decide to create a portfolio of say 50 stocks, understanding even the possible pay-off, or return, becomes difficult. And how about comparing different portfolios of different size, and different lengths of history? How do you actually compare those and decide what the better investment is? That's where portfolio analysis comes in. But first let's clarify a bit of terminology. First of all, a portfolio is a collection of assets owned by an individual. Those assets can be stocks, bonds, commodities, funds etc. People sometimes use fund and portfolio interchangeably. However a fund is actually a pool of investments that is managed by a professional fund manager. Individual investors buy "units" in the fund and the fund manager invests the money directly in a portfolio of stocks and bonds. Lastly, an index is a theoretical collection of assets, that represents a section of the market. For example the Nasdaq Composite index represents US technology stocks. Let's talk about different investment styles. You might have heard about passive investing. A passive investor aims to mimic the investment holdings of a particular index and thereby doesn't try to beat a benchmark or maximize returns. An active investor typically tries to beat a benchmark or to maximize return for a given level or risk. Active investors pay close attention to market trends, shifts in the economy, changes to the political landscape, and factors that may affect specific companies, and use that information to buy and sell stocks. Within the active space, long only investment strategies try to outperform a benchmark, whereas absolute return hedgefunds are not bound by a benchmark and just aim for a best possible risk-return trade-off. When you invest in just one stock, events such as change of management, weak financial performance, difficult industry performance, etc all will all cause your investment to fluctuate heavily. By combining stocks in a portfolio you can reduce some of those fluctuations as positive returns in one stock can absorb negative returns in others. By smartly combining asset with different characteristics and different risk and return profiles, you can reduce the overall risk of your investments. This is called diversification. Let's talk about typical portfolio strategies. The equal weighted portfolio, combines stocks and gives them all the same weight, as the name suggests. The market-cap weighted portfolio creates individual weights based on the size of the companies, measured by market capitalization. Market capitalization is the value of the company calculated by multiplying a company's shares by the current market price of one share. Lastly, a risk-return optimized portfolio has an optimized risk-return trade-off. You'll learn more about this in chapter 4. Let's practice! #DataCamp #PythonTutorial #Portfolio #Analysis #Python |
| Category | Science & Technology |
| Tags | Python | Analysis | Portfolio | PythonTutorial | DataCamp |
