Financial Mathematics Modeling Workshop

Winter 2020 Workshop: January 9-18, 2020

Description: The School of Mathematics at the University of Minnesota holds a 10-day workshop on Financial Mathematics Modeling every winter between fall and spring Semesters. 

Below are the details for the winter 2020 Modeling Workshop

Format: Students will work in teams of up to 5 students under the guidance of a mentor from the field of quantitative finance. The mentor will help guide the students in the modeling process, analysis and computational work associated with a real-world quantitative finance modeling problem. A progress report from each team will be scheduled during the period. In addition, each team will be expected to make a final oral presentation and submit a written report at the end of the 10-day period.

Projects and Industry Mentors : 

Team 1 - Industry Mentor - Matt Abroe: Dr. Abroe is a portfolio manager focused on interest rates in developed economies, specializing in inflation linked securities and derivatives.  Prior to working as a portfolio manager, he was as a quantitative analyst at Black River Asset Management.  He holds a PhD in physics from the University of Minnesota

Project - Inflation Rate Curve Modeling: Inflation linked debt comprises a significant portion of the bond issuance program for most developed economies.  Valuing these securities is complicated by the fact that the future cash flows are uncertain in nominal terms.  Additionally, the well behaved seasonal pattern of inflation indices must also be incorporated into any valuation framework.  In this module we will learn how to use inflation derivatives to determine the market implied path of forward inflation.  We then utilize this information to build valuation tools used to analyze inflation linked debt.
 

Team 2 - Industry Mentor - Dr. Chris Bemis: Dr. Bemis is Head of Quantitative Analysis and Research for Whitebox Advisors, focusing on cross-asset alpha drivers for a variety of asset classes. He is an active researcher for the Whitebox quantitative group, where he works on varied problems in the context of equity, derivative, and fixed income strategies; of particular interest is the interpretation of constraints in an optimal portfolio setting in a Bayesian context. Dr. Bemis earned his PhD in applied mathematics from the University of Minnesota, where his work involved both modeling and optimization for portfolios of risky assets.

Project - Machine Learning in Equity Classification: In this module, we will work with various machine learning classification models with the goal of classifying equities via well-known quantitative factors such as Value and Momentum.  The classification will be supervised, utilizing a novel ETF dataset which we will supplement extensively.  Participants will not be required to have extensive background in Python, although that will be the language we use; especially the Scikit Learn module. 

 
Team 3 - Industry Mentor - He Lu: Mr. Lu has a strong background in quantitative analysis and risk management. He currently serves as a Managing Director at BlueWater Financial Technologies, leading analytics, portfolio management, product development, and data science initiatives. Prior to joining Blue Water, He Lu worked as a portfolio manager at Incenter, responsible for MSR modeling, risk analysis, and MSR hedging. Earlier in his career, He served as an MSR modeler and risk manager at U.S. Bank, responsible for their OAS valuation framework development and risk management. He earned a Master Degree in Financial Mathematics from the University of Minnesota and a BA in Computer Science from Yanshan University.  
 
Project - Modeling Mortgage Prepayment and Delinquency Rates: Prepayment and delinquency rate modeling is critical in pricing mortgage-related financial products ( i.e. whole loan, mortgage-backed securities, mortgage servicing rights, etc.).  Working with a large loan-level dataset, participants will gain hands-on experiences ranging from building a data pipeline and database, conducting data analysis and visualization, to exploring and applying various statistical and machine learning modeling techniques. All exercises will be completed using Python.

 
Team 4 - Industry Mentor - Perry Li: Mr. Li, CFA, FRM, is a portfolio manager responsible for trading and assisting with day-to-day management of Parametric’s options-based Volatility Risk Premium strategies, including Defensive Equity and other proprietary strategies. Prior to joining Parametric in 2014, Perry worked for CHS Inc., where he managed commodity futures and options portfolios and conducted research on macro economy and derivative strategies. He earned a B.S. in Statistics from the Sun Yat-Sen University and a M.S. in Financial Mathematics from the University of Minnesota Twin Cities. He is a Certified FRM®, as well as a CFA® charterholder and a member of the CFA Society of Minnesota.
 
Project - Alternative Risk Premium in Commodity and Currency: What amount of money is expected to earn from on a risky asset to induce investors to hold rather than the risk-free asset? Ever since the first stocks and bonds were issued by the Dutch East India Company (VOC), investors have tried to understand what drives returns.

Beyond “Smart Beta” strategies, which seek to offer the potential for better-than-market (beta) returns with better-defined risks, Alternative Risk Premium strategies (ARP) utilize rule-based, long/short positions to achieve uncorrelated, complementary returns while reducing costs such as liquidity constraints and management fees.

The goal of this project is to give the participants live back-test and portfolio construction experience, to build a multi-asset investment portfolio that traditionally defined as “alpha”, by using different factors like carry, value, momentum. The project will include practices of data gathering (Bloomberg) and process, creating back-test models, and exploring variation of ARP combinations for optimal portfolio construction.

 

Tentative Schedule 

Team break-out rooms are available from 8 am to 4 pm, rooms are the same for all workshop days (* except Saturday, January 11 and Sunday, January 12):

Team 1 Breakout Room - Vincent Hall 206
Team 2 Breakout Room - Vincent Hall 209
Team 3 Breakout Room - Vincent Hall 207
Team 4 Breakout Room  - Vincent Hall 213

Thursday, January 9 - Vincent Hall 16: All Day Workshop Outline:

Posing of workshop projects by the industry mentors through half-hour introductory talks in the morning followed by a welcoming lunch. In the afternoon, the teams work with the mentors. The goal at the end of the day is for students to start working on the projects.

9:00am-9:30am - Check In & Coffee (120 Vincent Hall)
9:30am-9:40am - Welcome — Dr. Chris Bemis (University of Minnesota)
9:40am-10:00am - Mentor 1
10:00am-10:20am - Mentor 2
10:20am-10:40am - Mentor 3
10:40am-11:00am - Mentor 4
12:00pm - Lunch (120 Vincent Hall)
1:30pm-4:30pm - Afternoon - start work on projects

Friday, January 10 to Sunday, January 12: All Day Students work on the projects. Mentors will be available by phone, email, evening meetings, to guide their groups through the modeling process, leading discussion sessions, suggesting references, and assigning work.

Monday, January 13 - Vincent Hall 16

9:00am-9:30am - Coffee (120 Vincent Hall)
9:30am-9:50am - Team 1 progress report
9:50am-10:10am - Team 2 progress report
10:10am-10:30am - Team 3 progress report
10:30am - 10:50am - Team 4 progress report
12:00pm-1:30pm Lunch (on your own)
2:00pm-5:00pm - Remainder of the day students work on projects in breakout rooms. Mentors available for consultation.

Tuesday, January 14 to Friday, January 17: All Day Students work on the projects in their breakout rooms. Mentors available for consultation.

Saturday, January 18 - Vincent Hall 16

9:00am-9:30am - Coffee (120 Vincent Hall)
9:30am - Team 1 Final Report
10:00am - Team 2 Final Report
10:30am -Team 3 Final Report
11:00am - Team 4 Final Report
12:30pm-2:00pm - Lunch (120 Vincent Hall)