5, 10 or 20 seats+ for your team - learn more
Are you ready to “explode” into the financial analysis-side of data science? Volatility is a factor in determining financial risk and it even makes appearances in option pricing formulas. In fact, volatility analysis is the backbone of finance modeling. In this liveProject series, you’ll learn to predict and model volatility, optimize model parameters, and choose the best financial model by analyzing and comparing prediction results. With the projects in this series, you’ll be managing financial risk like a pro with reliable and accurate volatility forecasts.
In this liveProject, you’ll play the part of a freelance consultant who’s been hired to assess a company’s financial risk. Using the traditional volatility modeling packages ARCH and GARCH, you’ll model the volatility of S&P-500 stock prices—a good proxy for the entire financial market—and measure model performance. Then, you’ll optimize the model parameters using information criteria such as Bayesian Information Criteria (BIC). When you’ve completed the project, you’ll have a solid understanding of the logic of these traditional models and be ready to apply it to other models.
Now that you’ve tackled volatility modeling in a traditional way, in this liveProject, your employer has challenged you to uplevel your volatility modeling by taking a more dynamic, data-dependent approach. By the end of this project, you’ll have firsthand experience modeling volatility using support vector machines with different kernels, neural networks, and deep learning models. What’s more, you’ll have the skills to determine if the machine learning-based models outperform the traditional parametric models.
These liveProjects are for intermediate Python programmers and data scientists who want to leverage their Python skills for finance applications. To begin these liveProjects you will need to be familiar with the following:
In this liveProject series, you’ll learn skills and techniques for volatility forecasting in financial modeling using traditional models as well as machine learning models. The valuable knowledge and skills you’ll master here can help take your career to the next level:
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