Events

April 7, 2015, 11:00 am-noon, Ford ITW Classroom 1.350
Wasserstrom Family Distinguished Lecture
Prof. Paul Glasserman, Columbia University
Title: Engineering Financial Stability
Abstract: Financial engineering has traditionally addressed problems of portfolio selection, derivatives valuation, and risk measurement. This talk will provide an overview of more recent financial engineering problems that arise in the design and monitoring of the financial system. Several problems in this domain can be viewed as instances of stabilizing or destabilizing feedback. Some problems result from a combination of the two: actions that are stabilizing for individual agents can become destabilizing when agents interact. Other problems draw on traditional tools of the field. I will discuss specific modeling problems in the design of capital requirements, measuring counterparty risk, margin requirements for derivatives, and the effects interconnections between financial institutions, drawing on joint work with several other researchers.

October 2, 2014, 10:00-11:00 am, Tech L324
EECS Departmental Seminar
Prof. Ilya Pollak, Purdue University
Title: Optimal Monitoring and Mitigation of Systemic Risk in Financial Networks
Abstract: We propose a quantitative framework for constructing optimal policies to manage systemic risk in financial networks. Given a one-period borrower-lender network in which all debts are due at the same time and have the same seniority, we address the problem of allocating a fixed amount of cash assistance among the nodes to minimize the weighted sum of unpaid liabilities. Assuming all the loan amounts and asset values are fixed and that there are no bankruptcy costs, we show that this problem is equivalent to a linear program. We show, however, that if the defaulting nodes never pay anything, this problem becomes an NP-hard mixed-integer linear program. Yet we demonstrate through numerical simulations that modern optimization software enables the computation of very accurate solutions to this mixed-integer program on a personal computer in a few seconds for network sizes comparable with the size of the US banking system. We also address the problem of allocating the cash injection amount so as to minimize the number of nodes in default. For this problem, we develop an approximate algorithm which can be viewed as a reweighted iterative linear program and illustrate its effectiveness through numerical simulations. If time allows, we will describe two extensions. The first of these is a distributed version of the optimization procedure for the deterministic problem with no bankruptcy costs. This distributed algorithm is useful for applications where it is desirable to avoid centralized data gathering and computation. Second, since some applications require forecasting and planning for a wide variety of different contingencies, we also consider the problem of minimizing the expectation of the weighted sum of unpaid liabilities under the assumption that the net external asset holdings of all institutions are stochastic.  This is joint work with Zhang Li, Xiaojun Lin, and Borja Peleato-Inarrea.

June 16, 2014, 9:00-11:00 am, Tech A230
Dissertation Proposal
Yutian Nie
Title: Markovian Semimartingales and Financial Modeling
Abstract: Markovian semimartingales are essential in stochastic modeling of financial markets. In this dissertation proposal we discuss two Markovian semimartingales and their applications in financial modeling. The first part studies sticky reflecting Ornstein-Uhlenbeck processes which are solutions to stochastic differential equations with sticky boundary conditions. We construct sample paths of the solution by means of time change, show the joint uniqueness in law, and represent the transition semigroups in terms of spectral expansion. As an application, we propose a Markovian short rate model with zero lower bound based on sticky OU processes under which zero coupon bond and interest rate derivative prices have analytical solutions though eigenfunction expansion. In the second part, we investigate a class of singular continuous stochastic processes called inverse subordinators as a new ingredient in the well-established time change methods in mathematical finance. We study various mathematical characterizations of inverse subordinators, in particular, their semi-Markov property, and show that they can be used to construct a variety of mathematically tractable financial models that incorporate waiting periods and long range dependence.

June 6, 2014, 3:00-5:00 pm, Tech C211
Dissertation Proposal
Mingbin Feng
Title: Complementarity Formulations of l_0-norm Optimization Problems, Algorithms for Value-at-Risk Portfolio Optimization Problems, and Green Designs of Simulation Experiments
Abstract: This proposal presents research results for three research projects: minimization of solution sparsity via complementarity formulations, algorithms for Value-at-Risk portfolio optimization problems, and simulation experiment designs that are "green," i.e., designs that exploit preexisting simulation outputs to guide further experiments. l_0-norm minimization problems are non-convex but they process special problem structures. We consider the complementarity formulations of these problems. Our numerical experiments suggest that common nonlinear solvers are able to give good solutions to our reformulations of $\ell_0$-norm problems. Value-at-Risk (VaR) portfolio optimization problems are common in practice and they belong to the class of chance-constrained problems. We customized a decomposition algorithm for general chance-constrained problems for VaR problems. In financial engineering and other areas, simulation experiments are often used to support a particular decision making process, after which simulation outputs are discarded. We think of these preexisting outputs as valuable resources which can be recycled to guide future experiments. We illustrate this idea of green simulation with a risk management example. Our numerical results show that, with a fixed simulation budget, the accuracy of the green simulation estimator improves by an order of magnitude by exploiting preexisting simulation outputs.

June 6, 2014, 10:00 am-noon, Tech C211
Dissertation Proposal
Imry Rosenbaum
Title: Multi-Level Monte Carlo and Database Monte Carlo in Stochastic Simulation Metamodeling

September 27, 2013
Dissertation Proposal
Likuan Qin
Title: Ross Recovery in General Markovian Economies

April 8, 2013, 2:00-3:00 pm, Tech M228
IEMS Departmental Seminar
Prof. Dr. Stefan Weber, Leibniz University Hannover
Title: Liquidity-Adjusted Risk Measures
Abstract: Liquidity risk is an important type of risk, especially during times of crises. As observed by Acerbi and Scandolo (2008), it requires adjustments to classical portfolio valuation and risk measurement. Main drivers are two dimensions of liquidity risk, namely price impact of trades and limited access to financing. The talk discusses a cash-invariant liquidity-adjusted risk measure that can naturally be interpreted as a capital requirement. The difference between our construction and the one of Acerbi and Scandolo (2008) is analyzed in the framework of capital requirements using the notion of eligible assets, as introduced by Artzner, Delbaen, and Koch-Medina (2009). Numerical case studies illustrate how price impact and limited access to financing influence the liquidity-adjusted risk measurements.

November 29, 2012, 4:00-5:00 pm, Tech M228
IEMS Departmental Seminar
Prof. Liming Feng, University of Illinois at Urbana-Champaign
Title: Inverting Analytic Characteristic Functions
Abstract: Analytic characteristic functions naturally arise in financial engineering, as well as many statistical and engineering applications. We explore the analyticity of such characteristic functions and propose highly efficient inversion schemes. The schemes are very easy to implement. One does not need to rely on commercial numerical packages. Despite the simplicity, they are highly accurate, with exponentially decaying errors. Moreover, they admit explicit and computable error estimates that only depend on the given characteristic function. Multiple values of the desired quantity can be computed simultaneously using the fast Fourier transform. We illustrate the effectiveness of the schemes with financial engineering examples, including options valuation, as well as Monte Carlo simulation of Lévy processes with analytic characteristic functions.

October 24, 2012, 3:00-4:30 pm, Tech M228
IEMS Departmental Seminar
Dr. Peter Carr, Morgan Stanley and New York University
Title: Risk, Return, and Ross Recovery
Abstract: The risk return relation is a staple of modern finance. When risk is measured by volatility, it is well known that option prices convey risk. One of the more influential ideas in the last twenty years is that the conditional volatility of an asset price can also be inferred from the market prices of options written on that asset. Under a Markovian restriction, it follows that risk-neutral transition probabilities can also be determined from option prices. Recently, Ross has shown that real-world transition probabilities of a Markovian state variable can be recovered from its risk-neutral transition probabilities along with a restriction on preferences. In this paper, we show how to recover real-world transition probabilities in a bounded diffusion context in a preference-free manner. Our approach is instead based on restricting the form and dynamics of the numeraire portfolio.

October 9, 2012, 4:00-5:00 pm, Tech M228
IEMS Departmental Seminar
Prof. Stathis Tompaidis, McCombs School of Business, University of Texas at Austin
Title: Optimal VWAP Trading
Abstract: This work was motivated by a problem that arises in algorithmic trading, of designing a trading strategy to buy or sell a given amount of a stock in a day at an average price that closely matches the volume-weighted-average-price (VWAP) of the stock throughout the day. VWAP is commonly used by institutional investors such as pension funds and mutual funds as a benchmark. VWAP orders are available through most brokerage houses and are seen as a way to reduce execution costs. Recently NASDAQ has filed an application with the Securities and Exchange Commission to introduce their own VWAP order – proceedings regarding the application have been initiated. We study the problem of designing a trading strategy to match VWAP in a model where price and volume dynamics are co-dependent. Using dynamic programming we are able to provide a closed-form formula for the optimal trading strategy in the absence of market impact. We provide empirical evidence for the effectiveness of the strategy for the 30 stocks that form the Dow Jones index. We also study the performance and effectiveness of the proposed strategy in the setting where there trading causes both temporary and permanent price impact.
This paper is joint work with Jedrzej Bialkowski (University of Canterbury) and Daniel Mitchell (McCombs School of Business, University of Texas at Austin).

October 1, 2012, 2:00 pm, Ford ITW Classroom
EECS Distinguished Speaker Series
Prof. Venkat Anantharam, University of California at Berkeley
Title: What Risks Lead to Ruin?
Abstract: Insurance transfers losses from the insured to the insurer for a price, the premium. In the collective risk approach, one abstracts the problem to include just two agents: the insured and the insurer. The pace of modern technology throws up scenarios where it is difficult to have confidence about what the loss distribution is. For instance, how would one insure potential losses incurred by entities operating on the Internet? It is then natural to adopt a nonparametric formulation. Suppose all that the insurer knows is that the loss sequence is a realization from some i.i.d. process with marginal law in some set of probability distributions on the nonnegative integers. The insurer does not know which distribution in this set describes the marginal distribution of the loss sequence. The insurer will go bankrupt if the loss incurred exceeds the built up buffer of reserves from premiums charged so far. Can the insurer set premiums so that the probability of going bankrupt is less than any prescribed threshold irrespective of which distribution from the class is the true loss distribution?  We show that a nonparametric loss model of this type is insurable if it contains no “deceptive" distributions. Here the notion of deceptive distribution is precisely defined in information-theoretic terms. There appear to be close connections between classes of insurable probability distributions and classes of distributions studied in universal data compression. The necessary background from information theory and risk theory will be provided during the talk.

June 21, 2012, 9:00am-11:00 am, Tech C211
Dissertation Defense
Steven Golbeck
Title: Stochastic Modeling in Asset-Backed Financing

April 24, 2012, 4:00-5:00 pm, Tech M228
IEMS Departmental Seminar
Dr. Jon Frye, Federal Reserve Bank of Chicago
Title: Credit Loss and Systematic LGD
Abstract: This paper presents a model of systematic LGD that is simple and effective. It is simple in that it uses only parameters appearing in standard models. It is effective in that it survives statistical testing against more complicated models.

April 18, 2012, 10:00am-noon, Tech C211
Dissertation Defense
Lingfei Li
Title: Stochastic Modeling in Commodity Markets and Optimal Stopping of Symmetric Markov Processes

December 1, 2011, 2:30-3:00 pm, Tech M228
Lingfei Li
Title: Modeling in Commodity Markets and Optimal Stopping of Symmetric Hunt Processes

November 17, 2011, 10:00 am-noon, Tech C211
Dissertation Defense
Yunpeng Sun
Title: Efficient Simulation and Applications in Finance

(The website was not updated during the 2010-2011 academic year when the webmaster was on sabbatical.)

June 3, 2010, 9:00-11:00 am, Tech M228
Dissertation Proposal
Luis Chavez-Bedoya
Title: Topics in Asset Allocation

April 22, 2010, 4:00-5:00 pm, Pancoe Auditorium
IEMS Departmental Seminar
Dr. Alan J. King, IBM, Yorktown Heights, N.Y.
Title: On Safeguarding the Financial System slides
Abstract: In this talk, I consider what is going to be needed, in the way of methodology and technology, to examine the causes of and develop solutions to the recent global failure of financial regulation. Embedded in the Senate's current financial reform legislation, are provisions to set up a new Office of Financial Research to collect data and perform research and analysis on risks to the financial system. We will discuss the nature in which the financial system is a network of supply chains, and develop an overview of the challenges and opportunities in developing an effective program of research and analysis to safeguard the financial system from future crises.

April 14, 2010, 4:00-5:00 pm, Tech M416
Financial Engineering Practitioner Seminar Series
Dr. Lisa Goldberg, MSCI Barra, Berkeley
Title: How Well Can We Forecast the Risk of Financial Extremes?
Abstract: We discuss the structure and accuracy of a practical, broadly applicable, factor-based model that forecasts and analyzes extreme risk. This model began as an intern project in the summer of 2006, and with some help from the financial crisis, it has received intense interest from diverse segments of the financial services community.

April 14, 2010, 10:00 am-12:00 pm, Tech C211
Dissertation Defense
Ming Liu
Title: Efficient Simulation in Financial Risk Management

March 4, 2010, 4:00-5:00 pm, Tech M416
Financial Engineering Practitioner Seminar Series
Sheldon Natenberg, Chicago Trading Company
Title: Option Market-Making, Pricing, and Risk Management
Abstract: The presentation will focus on the trading of options from the perspective of a professional market-making firm, including a discussion of how professional traders use theoretical pricing models to price options and manage risk, and the practical problems of adapting theory to the real world of the marketplace.

February 25, 2010, 4:00-5:00 pm, Tech M228
IEMS Departmental Seminar
Prof. Liuren Wu, City University of New York
Title: A Multifrequency Theory of the Interest Rate Term Structure
Abstract: We develop a class of no-arbitrage dynamic term structure models that are extremely parsimonious. The model employs a cascade structure to provide a natural ranking of the factors in terms of their frequencies, with merely five parameters to describe the interest rate time series and term structure behavior regardless of the dimension of the state vector. The dimension-invariance feature allows us to estimate low and high-dimensional models with equal ease and accuracy. With 15 LIBOR and swap rate series, we estimate 15 models with the dimension going from one to 15. The extensive estimation exercise shows that the 15-factor model significantly outperforms the other lower-dimensional specifications. The model generates mean absolute pricing errors less than one basis point, and overcomes several known limitation of traditional low-dimensional specifications. Authors: Laurent E. Calvet, Adlai J. Fisher, and Liuren Wu.

December 3, 2009, 4:00-5:00 pm, Tech M345
Financial Engineering Practitioner Seminar Series
Dr. Alexander Eydeland, Morgan Stanley, New York
Title: Commodity Models: from Ags to Zinc
Abstract: We will discuss various issues and challenges facing commodity quants and suggest a number of modeling methodologies designed to address these issues. We will also give a brief introduction of standard commodity structures as well as new products and recent developments in commodity markets.

December 3, 2009, 9:30-11:00 am, Tech C211
Dissertation Proposal
Lingfei Li
Title: Commodity Derivative Models with Mean-Reverting Jumps and Stochastic Volatility: A Spectral Expansion Approach

November 10, 2009, 4:00-5:00 pm, Tech M228
IEMS Departmental Seminar
Prof. Thaleia Zariphopoulou, Oxford University
Title: A New Approach for Investment Performance Measurement
Abstract: A new method for measuring the performance of investment policies will be introduced. Optimality of investment strategies will be associated with a stochastic partial differential equation (SPDE). The novel concept of performance volatility, as the driver to this SPDE, will be presented. Examples of performance volatility processes, modeling different numeraires, benchmarks and market views, will be presented.

October 2, 2009, 3:00-4:00 pm Tech M152
Guest Lecture, IEMS 326
Dr. John Charnes, Bank of America, Charlotte
Title: Commercial Credit Portfolio Management

June 11, 2009, 3:00-4:00 pm Tech M228
Lingfei Li
Title: Commodity and Energy Derivatives Models with Mean Reverting Jumps and Stochastic Volatility: A Spectral Expansion Approach

June 8, 2009, 10:00 am-12:00 pm
Dissertation Defense
Hai Lan
Title: Two-Level Simulation of Expected Shortfall: Confidence Intervals, Efficient Simulation Procedures, and High-Performance Computing

June 2, 2009, 10:00 am-12:00 pm Tech C211
Dissertation Proposal
Ming Liu
Title: Efficient Simulation in Financial Risk Management

May 28, 2009, 7:30-9:30 am Cohen Commons, Technological Institute
Mornings at McCormick
Prof. Jeremy Staum
Title: Systemic Risk: The Next Frontier in Risk Management and Regulation
Abstract: The current paradigm of risk management and regulation addresses the risk of each firm in isolation. How can government regulators measure or reduce the risk of the financial system as a whole? How might this affect the practice of risk management within financial firms? Can regulation provide incentives for firms to make decisions that reduce systemic risk? We will discuss some basic concepts and insights of the emerging field of systemic risk management and consider their implications for engineering a more stable financial system.

May 26, 2009, 4:00-5:00 pm Tech M228
IEMS Departmental Seminar
Dr. Michael B. Gordy, Federal Reserve Board, Washington D.C.
Title: Constant Proportion Debt Obligations: A Post-Mortem Analysis of Rating Models
Abstract: In its complexity and its vulnerability to market volatility, the CPDO might be viewed as the poster child for the excesses of financial engineering in the credit market. This paper examines the CPDO as a case study in model risk in the rating of complex structured products. We explain how a CPDO transaction works and review events in this market to date. We demonstrate that the models used by S&P and Moodys would have assigned (at best) low probability to the spread levels realized in the investment grade corporate credit default swap market in late 2007. The spread levels realized in the first quarter of 2008 would have been assigned negligibly small probabilities. Had the models put non-negligible likelihood on attaining these high spread levels, the CPDO notes could never have achieved investment grade status.
(Joint work with Soren Willemann.)

May 12, 2009, 9:00-11:00 am Ford Building, ITW Classroom
Technical Seminar
The MathWorks
Title: Computational Finance with MATLAB
Abstract: We will demonstrate how to use MATLAB as an analytics platform and an application development environment to import, analyze, and visualize data, measure risk, and develop optimization strategies. Application examples will be presented highlighting capabilities for GARCH modeling/forecasting, option pricing, and portfolio optimization among others.

May 5, 2009, 2:00-4:00 pm Tech C211
Dissertation Defense
Rafael Mendoza
Title: Unified Credit-Equity Modeling

April 14, 2009, 4:00-5:00 pm Tech M228
IEMS Departmental Seminar
Prof. Paul Zipkin, Duke University
Title: Quality Snags in the Mortgage-Finance Supply Chain
Abstract: This essay views the current financial crisis through the lens of quality management. The crisis represents a failure of quality, and solving it will require, among other things, careful management of quality in financial institutions and across financial supply chains. This will be difficult for several reasons, but not impossible. I offer several recommendations, partly inspired by successful quality practices in industry.

March 31, 2009, 1:00-2:00 pm Tech M426
Information Session
Morgan Stanley
Title: Morgan Stanley Quantitative Finance Program
Abstract: Morgan Stanley Innovative Data, Environments, Analytics & Systems (IDEAS), is an integrated quantitative and technology organization formed to create a sustainable, commercial advantage for Morgan Stanley by reshaping the Firm's businesses around innovative people, processes and systems. IDEAS includes revenue-generating, business unit-embedded desk strategist teams, and platform and technology teams with a broad range of expertise across those data sources, applications, systems and technologies used by the Firm's sales and trading, banking and investment management businesses.

October 21, 2008, 4:00-5:00 pm Tech M228
IEMS Departmental Seminar
Prof. Garud Iyengar, Columbia University
Title: Robust Portfolio Selection
Abstract: Parameters in a portfolio section problem are typically estimated from a finite amount of data -- consequently, the parameter estimates are always erroneous. Moreover, optimal solutions to the portfolio selection models tend to amplify these parameter errors several fold, resulting in "error-maximized and investment irrelevant" portfolios! Robust optimization has recently emerged as a particularly useful methodology for optimizing performance in the presence of data errors. In this talk we will survey some of our recent work on robust formulations for portfolio selection. In particular, we will discuss a robust version of the mean-variance and the mean-CVaR portfolio selection problem. We will illustrate these methods on examples from equity portfolio management, pension-fund management, and credit portfolio management.
(Parts of this talk are joint work with Donald Goldfarb, Emre Erdogan, and Ka Chun (Alfred) Ma.)

September 26, 2008, 4:00-5:00 pm Tech L251
Alexander Lipton, Merrill Lynch, London
Title: Jump-diffusions and credit modelling (Theoretical models and practical implications)
Abstract: In this talk we discuss qualitative and quantitative approaches to modelling credit risk and credit events.  In particular, we present a view from the trenches of the developing credit crisis.

September 23, 2008 4:00-5:00 pm Tech M228
IEMS Departmental Seminar
Michael Sotiropoulos, Banc of America Securities, New York
Title: Volatility Trading and Timer Options
Abstract: Trading financial derivatives is a risky activity, even in the presence of frequent Delta hedging. This talk briefly reviews some industry-standard approaches for dealing with the volatility risk in option positions. The problems associated with managing volatility risk are pointed out and a novel structure, the timer option, is presented. The pricing of timer options is shown to be robust under volatility and stochastic model misspecification.

September 23, 2008 11:30-1:00 pm Tech C211
Dissertation Defense
Evren Baysal
Title: Advances in Risk Management Simulation

May 21, 2008, 12:00-1:00
Joint Kellogg-McCormick Operations Seminar
Prof. Vadim Linetsky
Title: A Modeling Framework for Heavy Equipment Financing and Leasing with the Risk of Default: The Case of Aircraft Manufacturing
Abstract: Sales of heavy equipment, such as aircraft, ships, rail stock, factory and construction equipment, require long term financing, such as loans or leases. In this work we focus on the aircraft sector as a representative industry. If the customer defaults on its loan or lease, the aircraft will be repossessed and sold or leased in the used aircraft market. The financier is thus exposed to the risk of declining prices for used equipment, as well as credit risk (the risk of default on the financing contract). We study the problem of valuing and assessing the risk of a range of aircraft financing contracts. In particular, we propose a framework to model market prices of depreciating equipment.

March 6, 2008
Information Session
Chicago Trading Company
Title: Financial engineering research in an options market marking firm

October 23, 2007, 4:00-5:00 Tech M228
IEMS Departmental Seminar
Prof. Kay Giesecke, Stanford University
Title: The correlation-neutral measure for portfolio credit
Abstract: Using a complex-valued measure change, we derive a formula for a Fourier transform of a counting process that describes the arrival of totally inaccessible events, and we show how this transform facilitates an analytical treatment of a range of valuation, hedging and risk management problems that arise in single name and portfolio credit risk. Example applications include reduced form pricing of credit sensitive securities referenced on single or multiple issuers, hedging of constituent risks, model estimation, and credit portfolio risk measures.



Please send announcements of financial engineering events in the Chicago area to the webmaster.