Hands-on Python for Finance
The practical guide to using data-driven algorithms in Finance
Bullstrack
Hands-on Python for Finance udemy course
The practical guide to using data-driven algorithms in Finance
What you'll learn:
- Learn how to code in Python
- Take your career to the next level
- Be able to work with Python’s conditional statements, functions, sequences, and loops
- Work with scientific packages, like NumPy
- Understand how to use the data analysis toolkit, Pandas
- Plot graphs with Matplotlib
- Use Python to solve real-world tasks
- Get a job as a data scientist with Python
- Acquire solid financial acumen
- Carry out in-depth investment analysis
- Build investment portfolios
- Calculate risk and return of individual securities
- Calculate risk and return of investment portfolios
- Apply best practices when working with financial data
- Use univariate and multivariate regression analysis
- Understand the Capital Asset Pricing Model
- Compare securities in terms of their Sharpe ratio
- Perform Monte Carlo simulations
- Learn how to price options by applying the Black Scholes formula
- Be comfortable applying for a developer job in a financial institution
Requirements:
- You’ll need to install Anaconda. We will show you how to do it in one of the first lectures of the course.
- All software and data used in the course are free.
Description:
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.
About the Author
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.
Who this course is for:
- This course is for developers and analysts with some background in programming language and are interested in a concrete framework for using Python to augment or replace spreadsheet applications for financial tasks.
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Course Details:
- 5.5 hours on-demand video
- 1 downloadable resource
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
Hands-on Python for Finance udemy free download
The practical guide to using data-driven algorithms in Finance
Demo Link: https://www.udemy.com/course/hands-on-python-for-finance/
