Overview What You Will Learn Curriculum Instructor

Course Overview

Artificial intelligence (AI) is leading the front of the digital transformation strategy in finance today. AI can practically be employed in everything present in the digital world.

We will begin the course by learning about the time value of money and get introduced to many terminologies like NPV, IRR, payback rule, and payback period. All of these play a very crucial role in TVM. We will also discover about PV Calculation of Annuity from Perpetual. We will proceed further and get to know some interesting Numerical Methods for Pricing Options. There, we will explore the Binomial Trees, European Pricing Options, and the Black-Scholes-Merton option model. Finally, we will dive into the world of Time Series Data and get to know many things like Normality, ARIMA/SARIMA Model, Amihud’s Illiquidity, and Fama-Macbeth Regression.

At the end of the course, you will be able to master the art of applying Python-based programming to different paradigms in the financial industry and perform effective and efficient data analysis.

“Disclaimer: The opinion expressed in this course/contents are those of the speaker/author and they do not reflect the opinion or views of his current and former employers.”

What You Will Learn

  • Introduction to TVM along with very interesting and detailed hands-on sessions!
  • Get to know about the numerical methods for pricing options which include American and European pricing options
  • Explore Statistical Analysis of time series data along with many interesting examples

Program Curriculum

  • Time Value of Money – Theory Session
  • Time Value of Money – Practical Session
  • NPV and NPV Rule, IRR, and IRR Rule – Theory Session
  • NPV and NPV Rule, IRR, and IRR Rule – Practical Session
  • Payback Period and Payback Period Rule – Theory Session
  • Payback Period and Payback Period Rule – Practical Session
  • PV Calculation of Annuity from Perpetuality
  • Practical Examples – Time Value of Money
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Options, Binomial Trees in Option Pricing, Pricing European Options
  • Futures, Payoff and Profit/Loss Functions for Call and Put Options
  • Black-Scholes-Merton Option Model on Non-dividend Paying Stocks
  • Binomial Tree (CRR) Method for Europe and American Options
  • Hedging Strategies
  • Chapter 2 Quiz

  • Introduction to Time Series Data
  • Test for Normality, High and Low Trading Values
  • Time Series Data, Forecasting with ARIMA/SARIMA Models
  • Estimating Roll’s Spread, Amihud’s Illiquidity, Fama-MacBeth Regression
  • Python for Very High Frequency Data
  • Introduction to CRSP
  • Applications of RNN, RNN-LSTM for Time Series Data
  • Chapter 3 Quiz

Instructor

Shovon Sengupta

Shovon Sengupta is an experienced data scientist with over 12 years of experience in advanced predictive analytics, machine learning, deep learning, and reinforcement learning. He has worked extensively in designing award-winning solutions for various organizations, for different business problems in the realm of Finance. Currently, he is Director - Data Science @AI CoE in one of the leading NBFCs in the USA. He has a USA patent(United States Patent - Sengupta et al. : Automated Predictive Call Routing Using Reinforcement Learning) for designing a reinforcement learning-based solution to his credit.

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