Practicum Projects

A signature part of the MSFE program at the University of Illinois is the requirement that students complete a corporate-sponsored, semester-long and team-based project applying their skills to a real world project. This should not be confused with typical engineering capstone projects. The Practicum is intensive, involving weekly face-to-face meetings with sponsors, presentation of weekly Progress Reports, a full final report (with annexes documenting data and codes) and finally a condensed presentation describing the project to a panel of technical and non-technical judges in a competitive environment.

In short, it is intended to be a proxy for real world experience, while still at college.

By the time our 10th MSFE class graduates at the end of 2019 the program will have conducted almost 100 different projects with over 40 different sponsors. The scope of project-subjects is eclectic, the range of sponsors is wide and the effect on our program has been immense.

Moreover, each one fits our chosen definition of Financial Engineering "...the application of quantitative techniques to financial markets or financial products..."

Students get invaluable experience, but the program itself benefits from seeing the latest concerns and innovations that engage industry and which indicate where the program may be improved. Industry gets a talented resource to investigate new opportunities or issues - and a look at potential recruits!

 

Projects Conducted by Corporate Sponsors

2020

I.B.M.
Using machine learning for default prediction and underwriting on Lending Tree's loan data

CME Group
Algorithmic futures trading in energy, financial and agricultural markets using machine learning

Morgan Stanley
Factors that drive U.S. population mobility and housing demand across MSAs

RCM-X
Professional sports team valuation, a factor based approach
Forecasting futures volume traded at settlement window

Social Market Analytics
Using textual and sentiment analysis to evaluate 8-K SEC filings

BraveRock
Trading the Bitcoin basis, spot-futures arbitrage in cryptocurrency

Connexin
Using machine learning for default and delinquency prediction on Fannie Mae loan portfolio data

Metrixx
Optimal equity portfolio allocation and performance measuring using technical vs. fundamental analysis

2019

Morgan Stanley
Analysis of event driven investment factors in merger arbitrage

RCM-X
Co-integration strategies for soybean crush futures and spreads, examining data across exchanges

SMA/Hull Trading
Using financial twitter messaging to detect information; designing an allocation strategy for ETF strategy

CME Group
Machine learning for event detection in energy and agricultural futures markets

Bianco Research
Using Natural Language Processing and latent Semantic Analysis to investigate a corpus of Fed minutes and transcripts

Chicago Alpha Modeling
Optimal allocation to a portfolio CTAs for a universe of over 1,500 such entities

CME Group
Continuous - Limit order book analysis; ML for HFT; Designing margins for Clearing House; AI combining NLP and Data

Connexin
Using Machine learning for default prediction on Lending Tree's loan book and FNMA loan portfolio

Professor Dale Rosenthal
Examining financial contract deliveries and their price history for evidence of short squeezes

Professor Woo
Designing "value" portfolios for longer term investment strategies

RCM-X
Multiple - recently examining co-integration strategies for fixed income futures as well as agricultural commodities

2018

AxisRe
Multiple - Optimizing Underwriting portfolios; Predicting default risk on an assumed portfolio of FNMA loans

Bank of Montreal
Multiple - Increasingly sophisticated Machine Learning models for detecting anti-money laundering

CME Group
Continuous - Limit order book analysis; ML for HFT; Designing margins for Clearing House; AI combing NLP and Data

Connexin
Using Machine learning for default prediction on Lending Tree's loan book; and on FNMA loan portfolio

Morgan Stanley
Revising and updating Fama Bliss multi-factor bond signals

Principal Financial
Predicting rating changes using machine learning; up dating an algorithm for trading Chinese equities in Hong Kong

RCM/SMA
Multiple - using financial twitter messages to detect information; designing a trading strategy for cryptocurrency

2017

AxisRe
Multiple - Optimizing Underwriting portfolios; Predicting default risk on an assumed portfolio of FNMA loans

Bank of Montreal
Multiple - Increasingly sophisticated Machine Learning models for detecting anti-money laundering

CME Group
Continuous - Limit order book analysis; ML for HFT; Designing margins for Clearing House; AI combing NLP and Data

Google
Using ML to predict agricultural prices; codifying the persuasive signals in choosing Google Cloud over competitors

MarketAxess
Multiple - Designing liquidity measures for the premia corporate bond platform; Signals from ETF origination

Peak6
Evaluating the early impact of IEX on transaction volume and price of listed equities

Professor Lane
Pricing Cat Bonds or ILS; optimizing ILS portfolio

Social Market Analytics
Multiple - using financial twitter messages to detect information; designing an ETF using SMA sentiment data

SpiderRock Advisors
Multiple - using options overlay strategies to manage liquid portfolios to lessen transaction cost and tax effects

UIUC Treasury Department
Multiple - how to allocate to the delegated managers of the Univ. liquidity portfolio and when/how to reallocate

Wedbush Securities
Multiple - Designing trade execution strategies; allocating to Dark Pools; designing ETFs

2016

Ash Brokerage
Multiple - concerning the appropriateness of annuities in retiree investment strategies

AxisRe
Multiple - Optimizing Underwriting portfolios; Predicting default risk on an assumed portfolio of FNMA loans

Bank of Montreal
Multiple - Increasingly sophisticated Machine Learning models for detecting anti-money laundering

CME Group
Continuous - Limit order book analysis; ML for HFT; Designing margins for Clearing House; AI combing NLP and Data

Geneva/SpiderRock
Multiple - using options overlay strategies to manage liquid portfolios to lessen transaction cost and tax effects

Professor Sowers
Examining signals and returns from pairs trading; measuring the market response function affects of sudden activity

Social Market Analytics
Multiple - using financial twitter messages to detect information; designing an ETF using SMA sentiment data

UIUC Treasury Department
Multiple - how to allocate to the delegated managers of the Univ. liquidity portfolio and when/how to reallocate

Wedbush Securities
Multiple - Designing trade execution strategies; allocating to Dark Pools; designing ETFs

All Prior Years

2015

Ash Brokerage
Multiple - concerning the appropriateness of annuities in retiree investment strategies

Bank of Montreal
Multiple - Increasingly sophisticated Machine Learning models for detecting anti-money laundering

CME Group
Continuous - Limit order book analysis; ML for HFT; Designing margins for Clearing House; AI combing NLP and Data

MarketAxess
Multiple - Designing liquidity measures for the premia corporate bond platform; Signals from ETF origination

PeerEx Investments
Analyzing the Lending Tree loan book for selecting loan acceptance criteria

UIUC Treasury Department
Multiple - how to allocate to the delegated managers of the Univ. liquidity portfolio and when/how to reallocate

Wedbush Securities
Multiple - Designing trade execution strategies; allocating to Dark Pools; designing ETFs

2014

Advocate Asset Management
Multiple - but notably detecting bias in VIX settlements procedures

Bank of Montreal
Multiple - Increasingly sophisticated Machine Learning models for detecting anti-money laundering

Chicago Trading Company
Multiple - predicting exercise of American options

CME Group
Continuous - Limit order book analysis; ML for HFT; Designing margins for Clearing House; AI combing NLP and Data

PeerEx Investments
Analyzing the Lending Tree loan book for selecting loan acceptance criteria

Professor Lane
Pricing Cat Bonds or ILS; optimizing ILS portfolio

Social Market Analytics
Multiple - using financial twitter messages to detect information; designing an ETF using SMA sentiment data

SunGard Financial Systems
Analyzing Spread Variance and predicting the impact of new SEC experiments concerning spread

2013

Advocate Asset Management
Multiple - but notably detecting bias in VIX settlements procedures

Busey Bank
Multiple - evaluating the place of MLPs in portfolios

CME Group
Continuous - Limit order book analysis; ML for HFT; Designing margins for Clearing House; AI combing NLP and Data

Ernst & Young
Using an Economic Scenario Generator to test Insurers Balance Sheet sensitivity to adverse scenarios

Florez
Using graduation, employment and salary data to test viability of investing in "Income Sharing Agreements" [ISA's]

MarketAxess
Multiple - Designing liquidity measures for the premia corporate bond platform; Signals from ETF origination

Nanex
Handling HFT data and considering the limit order book

Professor Lane
Pricing Cat Bonds or ILS; optimizing ILS portfolio

Professor Sowers
Examining signals and returns from pairs trading; measuring the market response function affects of sudden activity

Trade Forecaster Global Markets
High frequency trading and analysis of timing lags

2012

Boston Options Exchange
Evaluating the costs and benefits of enhancing the options platform to allow for combined options execution

Busey Bank
Multiple - evaluating the place of MLPs in portfolios

Fidelity
Using intra day data to test various execution strategies via internal execution group

MarketAxess
Multiple - Designing liquidity measures for the premia corporate bond platform; Signals from ETF origination

Professor Lane
Pricing Cat Bonds or ILS; optimizing ILS portfolio

Professor Sreenivas
Automated trading using Trading Technologies data and platform

Professor Ye
Externalities of high frequency trading; evidence from the Flash Crash using OPRA data

Shostek
Building trading strategies with MARS [Multi-variate Adaptive Regression Splines]

Trade Forecaster Global Markets
High frequency trading and analysis of timing lags

UBS
Multiple - asset allocation and credit spread

2011

Boston Options Exchange
Evaluating the costs and benefits of enhancing the options platform to allow for combined options execution

Chicago Trading Company
Multiple - predicting exercise of American options

Elementum
Using stochastic optimization to design a portfolio of ILS

MarketAxess
Multiple - Designing liquidity measures for the premia corporate bond platform; Signals from ETF origination

UBS
Multiple - asset allocation and credit spread

Wells Fargo Bank
Designing - account mangers incentive systems to enhance productivity, predicting efficiencies