In this advanced course, you will cover the major Python financial libraries to gather and manipulate financial data. You will start by working with financial APIs to fetch financial, company, and economic data. We will analyze financial statements from the SEC website, including financial ratios derived from the income statement and balance sheet. You will build a risk management models using Python libraries to create VAR models and Monte Carlo simulation. We will learn how to apply statistical measures such as linear regression to financial uses such as stock prices.
Target Audience: This course is ideal for financial analysts and professionals, risk managers, and portfolio managers, as well as those looking to break into a career in finance technology and data analysis.
This course has a Prerequisite
Python / Data: Participants should be familiar with concepts from Python for Data Science Bootcamp, including built-in data types, data structures, Pandas, and Matplotlib.
Finance Background: Participants should be familiar with financial concepts such as NPV, IRR, financial statements, and stock fundamentals. Those without a background in finance should contact us after registration to access a free on-demand supplemental guide.
Learn more about Python for Finance Bootcamp at Noble Desktop.