To help new students prepare for the four core courses in their first fall semester, we offer a Financial Mathematics (FM) Preparation Workshop. The workshop is hosted online only, Monday through Friday, from July 31st to August 18th, 2023. The lectures will be given from 8:30am-3:45pm with breaks. Lectures will be recorded and available online. Each lecture lasts 75 minutes and there will be 10 lectures for each module. The Summer 2023 schedule for the entire three weeks is available for viewing.

This three-week workshop will cover various topics including: mathematics, statistics and R, econometrics, risk management and Python programming. These topics will be customized for the FM program at NC State. Our records indicate that students with a good background in those areas tend to do well in the FM courses. Therefore, the workshop will prepare you for core courses such as ST 501/502, FIM 528, MA 547, FIM 548, and FIM 549, etc.

For those who come from a non-English teaching environment (such as China), this is also a great opportunity to get used to the English teaching environment and prepare for your first semester in the US. Additionally, our workshop is open to professionals in the field of finance as well as any non-NC State student interested in challenging themselves with foundational coursework that will boost their skills in quantitative finance.

Below are the five modules for the Summer 2023 FM Workshop, including the instructors’ information and the topics covered.

Module 2 – Statistics and R Programming by Prof. Sujit Ghosh. Dr. Ghosh is a FM faculty member and a professor of statistics. He will teach ST 501-001 this fall.

Overview

The primary goal of the Statistics module is to provide a quick introduction to basic statistical methods used as tools in finance. Majority of computational illustrations would involve the use of freely available software R which will be introduced as a part of this module. It is advised that the participants download R and get it installed before the workshop begins.

List of Topics

1. General overview and Introduction to R
2. Probability Basics
3. Random Variables and Distributions
4. Illustrations using R Studio
5. Sampling Distributions and Law of Large Numbers
6. Parameter Estimation Based on MoM & MLE
7. R packages for parameter estimation
8. Hypothesis Testing and Confidence Intervals
9. Regression Models: Multiple Linear Models
10. Illustrations of R for stat inference

Module 3 – Econometrics by Prof. Denis Pelletier. Dr. Pelletier is a FM Faculty member and a professor of economics. He has taught MA/FIM 528 before.

Overview

The objective is to give an overview of common models used in econometrics: linear regression, probit and logit. We will discuss the interpretation, estimation and specification of these models. Applications to problems in finance will be discussed.

Upon successful completion of this module, you will be able to:

1. Specify and estimate by OLS  a multiple linear regression model, then interpret the results.
2. Specify and estimate by MLE a logit or probit model, then interpret the results.
3. Use a linear regression model to price options using the Practitioner’s Black-Scholes method.
4. Use a logit or probit model to understand how to do credit scoring.

Module 4 – Risk Management by Prof. Wei Chen, FRM. Dr. Chen is the Director of Global Risk Consulting at SAS Institute and a FM professor of practice at NC State University. He has taught FIM 528, FIM 549 and FIM 590 (Credit Risk Models) in the past.

Overview

This module will give students a brief background on risk management as well as highlight the key strategies for assessing future risk and addressing gaps in risk modeling methods to date.

List of Topics

1. Introduction and Risk Management Overview
2. Financial market and market risk
3. Asset pricing and quantitative methods
4. Financial institutions and credit risk
5. Interest rate risk and ALM
6. Liquidity risk management
7. Operational risk and other risks
8. Introduction to risk modeling
9. Integrated risk management case studies: Financial Crisis 2008 and the bank failures in 2023

Module 5 – Python and Machine Learning by Prof. Andrew Papanicoloau. Dr. Papanicoloau is a FM faculty member who will be teaching FIM 528 this fall.

Overview

Basic Python programming and fundamentals of machine learning will be covered. Learn how to use Python to deal with the financial data analysis problems in practice. 

List of Topics

1. Python Basics
2. Machine Learning
3. Linear Regressions and Multiple Regression
4. Logistic Regression and Decision Trees
5. Neural Networks and Deep Learning

A discounted registration fee of $2295 will be applied to new financial mathematics students who register using the following link. This workshop, however, is optional for our students.

General registration is $2595 and will require registrants to create a Brickyard account. Visit this link to register for the workshop. About creating a Brickyard account.

Registration is now closed.

If you have any questions, including how to register, please send an email to Financial-Mathematics@ncsu.edu.