Finance and Python
Class is in session
Finance and Python
3 Weeks
·Cohort-based Course
Ready to learn finance or improve your financial knowledge with Python? If so, you are in the right spot. Let's get started!
Class is in session
Finance and Python
3 Weeks
·Cohort-based Course
Ready to learn finance or improve your financial knowledge with Python? If so, you are in the right spot. Let's get started!
Get notified about the next cohort
Hosted by
Abdullah Karasan
Faculty at UMBC | Senior Data Science Consultant at TFI TAB | Author at O'reilly
Course overview
Describe the transformation students will have in your course
Then use this section to go into more detail about the value students will receive in your course...
This course is for you because
01
You have enthusiasm towards financial and Python and looking for right direction to learn these top most valuable skills
02
You’re a financial analyst or decision maker in your current role or you want to switch your career into financial modeler
03
You are familiar with Python and specifically want to learn how to adapt Python to Finance while increasing your Python skills
04
Knowing financial modeling takes you to a whole new level in your career.
What will you do?
Learn Python Basics
With its unique libraries and user friendly environment, Python enables you to tackle challenging problems finance.
Main Financial Concepts
Give students an idea of how they can expect to grow throughout your course. Include specificity and precise results so students can benchmark exactly what they’ll learn.
Data Extracting with Python APIs
Accessing data is important but not easy. However, Python makes it easier to extract financial data using APIs such as Yahoo Finance, Quandl, Fred and more.
Asset Pricing with CAPM
Capital Asset Pricing Model (CAPM) is one of main building block in asset pricing. So, it would be wise to start learning financial modeling with CAPM. CAPM is nothing but regression-based application and it has appealing and intuitive findings.
Time Series Analysis with Financial Data
Learning time series analysis enable you to conduct many analysis. Here, we will apply different time series models to a stock price and evaluate the result.
Simulation Analysis
How happens if you do not have the data? or How do you create a hypothetical environment in which you can control for the change of a variable? The answer is simulation analysis. Using Python, you will simulate stock prices and I bet you will like it!
Portfolio Analysis
Portfolio analysis is at the heart of investment strategies and you will learn many different aspects of portfolio analysis with Python. Some of the topics that you will learn are forming a portfolio, calculating Sharpe and Treynor ratios, and drawing efficient frontier.
Volatility Modeling
If you are looking for insight for financial markets, volatility is something you should know. Learning volatility modeling helps you to better understand the markets. Also, it is one of the main inputs of the financial models. You will understand all these in this part.
Risk Management with Python
This part is devoted to tackle this question: How is the financial risk measured? When you learn how it is measured, you will be able to assess the riskiness of the portfolio. Value at Risk (VaR) and Expected Shortfall (ES) will be our focus.
Three Homeworks
You will complete three homeworks before the course ends.
Capstone Project
Once you are done with the course content, you will apply these techniques to the idea that you bring forth.
Meet your instructor
Abdullah Karasan
Finance and Python
Dr. Karasan is a faculty at University of Maryland at Baltimore County (UMBC) and Senior Data Science Consultant at TFI TAB Food Services. After studying Economics and Business Administration, he obtained his master's degree in applied economics from the University of Michigan, Ann Arbor, and PhD in financial mathematics from the Middle East Technical University, Ankara. He is a former Treasury employee of Turkey and also worked as Data Science Mentor at Springboard and delivered live lectures for O'Reilly. He is the writer of the book "ML for Financial Risk Management with Python " and published several papers in the field of financial data science.
Course syllabus
01
First Module: Introduction to Financial Concept and Modeling
In the first module, after a brief introduction to Python, you will be familiar with the following concepts:
- Return
- Correlation
- Covariance
- Risk-Return Relationship
Then, you will start learning how to obtain data using Python APIs. In the last part of this module, you will apply your first financial model, that is, CAPM for asset pricing.
02
Second Module: Time Value of Money, Simulation, and Portfolio Analysis
Time is an important asset and it needs to be included before making a financial decision. Second module covers two essential topics in evaluating time, which are:
- Net Present Value (NPV)
- Internal Rate of Return
First, you will learn the working logic of these approaches and then code them using Python.
03
Third Module: Time Series Analysis
You will start with obtaining time series components, white noise, and random walk. In the subsequence part, you will learn the concept of stationarity and how to detect and handle it.
What comes next is the time series modeling with univariate case. In the final part, you will learn multivariate time series mode
04
Fourth Module: Volatility Modeling
This module will start with extracting data and calculating realized volatility. In what follows, you will practice on the main volatility models such as:
- ARCH
- GARCH
- EGARCH
Then, you will analyze the performance of these models using performance metric and visualization.
05
Fifth Module: Risk Management
This model covers the main pillars of risk management models. These models are:
- Value-at-Risk
- Expected Shortfall
You will learn the theory of this models and apply them using Python.
06
Capstone Project
Capstone project will help you better understand you have learned throughout the course.
You will complete a capstone project that is based on your own idea or I can help you to find one. We will discuss this idea on Saturday, March 18th.
You will submit and present your project in our last class, which is on March 25th.
Course schedule
7-8 hours per week
March 14, 2023 - April 1, 2023
First cohort start on March, 14th and it ends on April, 1st.
3-Hour Live Workshops: Tuesdays & Thursdays (March 14th, 16th, 21st, 23rd)
3:00pm - 6:00pm EST
Learn new topics and practice with me.
Capstone Project Submission and Presentation: April 1st
Saturday 3:00pm - 5:00pm EST
This is a great chance to improve your hands-on skill. Let's discuss your project idea first on Saturday, March 25th. You can either bring your brilliant ideas or I can provide you one.
No worries, you will have time to think thoroughly on your capstone project.
Learning is better with cohorts
Active hands-on learning
This course builds on live workshops and hands-on homeworks and capstone project
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you. You will see that interaction will boost your learning
Frequently Asked Questions
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I work full-time, what is the expected time commitment?
What’s the refund policy?
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Is there any discount for applying as a group?
What if you have further questions?
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