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!

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

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.

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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

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

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