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Hands-on Python for Finance [Video]

More Information
  • General programing skills in Python and working with common Python interfaces
  • Using Numpy, Pandas and matplotlib to manipulate, analyze and visualize data
  • Understand the Time value of money applications and project selection
  • Getting and with working data, time series forecasting methods and linear models
  • Understand Correlation and portfolio construction
  • Be comfortable with Monte Carlo Simulation, Value at Risk and Options Valuation

Did you know Python is the one of the best solution to quantitatively analyse your finances by taking an overview of your timeline? This hands-on course helps both developers and quantitative analysts to get started with Python, and guides you through the most important aspects of using Python for quantitative finance.

You will begin with a primer to Python and its various data structures.Then you will dive into third party libraries. You will work with Python libraries and tools designed specifically for analytical and visualization purposes. Then you will get an overview of cash flow across the timeline. You will also learn concepts like Time Series Evaluation, Forecasting, Linear Regression and also look at crucial aspects like Linear Models, Correlation and portfolio construction. Finally, you will compute Value at Risk (VaR) and simulate portfolio values using Monte Carlo Simulation which is a broader class of computational algorithms.

With numerous practical examples through the course, you will develop a full-fledged framework for Monte Carlo, which is a class of computational algorithms and simulation-based derivatives and risk analytics.

The Github Link to this course is: https://github.com/PacktPublishing/Hands-on-Python-for-Finance-V

Style and Approach

We will use step-by-step tutorials that blend financial and programming concepts. Viewers will work along with the tutorial to create working examples. 

  • Use libraries like Numpy, Pandas, Scipy and Matplotlib for data analysis, manipulation and visualization
  • Implement common Time Series evaluation techniques, including development of forecasting models and linear models for forecasting
  • Make use of Monte Carlo method to simulate portfolio ending values, value options and calculate Value at Risk
Course Length 5 hours 25 minutes
Date Of Publication 28 Feb 2019


Matthew Macarty

Matthew Macarty has taught graduate and undergraduate business school students for over 15 years and currently teaches at Bentley University. He has taught courses in statistics, quantitative methods, information systems and database design.