The Quantitative Finance Seminar has been a centerpiece of the Commercial/Industrial 
          program at the Fields Institute since 1995. Its mandate is to arrange 
          talks on current research in quantitative finance that will be of interest 
          to those who work on the border of industry and academia. Wide participation 
          has been the norm with representation from mathematics, statistics, 
          computer science, economics, econometrics, finace and operations research. 
          Topics have included derivatives valuation, credit risk, insurance and 
          portfolio optimization. Talks occur on the last Wednesday of every month 
          throughout the academic year and start at 5 pm. Each seminar is organized 
          around a single theme with two 45-minute talks and a half hour reception. 
          There is no cost to attend these seminars and everyone is welcome. To 
          be informed of speakers and titles for upcoming seminars and financial 
          mathematics activities, please subscribe to the Fields mail 
          list.
          
          Past seminars 2005-06 
        Upcoming Seminars
        
        May 31, 2006
          
          Tom Coleman, Dean, Faculty of Mathematics, University of Waterloo
          Minimizing CVaR and VaR for a Portfolio of Derivatives
          Value at Risk (VaR) and Conditional Value at Risk (CVaR) are frequently 
          used as risk measures in risk management. We analyze the problem of 
          computing the optimal VaR and CVaR portfolios - we illustrate that if 
          the portfolios contain derivatives then the resultant optimization problems 
          are typically ill-posed. We propose corrective measures for this problem 
          and also look at some of the other computing challenges. 
        
         
         
          
          
        
        April 26, 2006
         
          Jean-Pierre Fouque, University of California Santa Barbara
            Perturbation Methods in Default Modeling 
            
            We show that stochastic volatility incorporated in first passage models 
            can create reasonable default probabilities over a wide range of 
            maturities. To achieve that, one has to carefully calibrate the time 
            scales of volatility, and, to make this approach tractable, we show 
            that regular and singular perturbations techniques associated to slow 
            and fast time scales can be used. We then address the multi-name case 
            and we show that default correlations created by stochastic volatility 
            give interesting loss distributions. Perturbation techniques are gain 
            used to compute these distributions and the related tranche prices.
            Joint work with Ronnie Sircar (Princeton), Knut SOLNA (UC Irvine), 
            and Stephen Zhou (PhD student, NC State University).
           and
          Sebastian Jaimungal, Department of Statistics, University 
            of Toronto
            Indifference Pricing for Equity-Linked Insurance and Reinsurance 
            Options
          Insurance companies are increasingly facing heavy exposure to capital 
            market risks, due to the issuance of equity-linked insurance policies. 
            There is now a growing need for coherent valuation and hedging methodologies 
            that take into account the interwoven actuarial and financial risks. 
            In this talk, I will demonstrate how the principle of equivalent utility 
            provides equity-linked insurance premiums, and explain how to value 
            double-trigger reinsurance options consistently; such contracts are 
            crucial risk management vehicles since they provide the insurer with 
            a means to offload unwanted risks. In addition, I will illustrate 
            how utility indifference allows for the simultaneous treatment of 
            counterparty risk. By solving the resulting HJB equations, I determine 
            that both the premiums and prices satisfy Black-Scholes-like PDEs 
            with non-linear and non-local risk-aversion correction terms. Numerical 
            consequences will be explored throughout this talk to clarify the 
            approach and to aid understanding.
        
        March 29, 2006
         
          Matheus Grasselli, McMaster University
             Rational exercise of employee options.
          At the core of the controversy surrounding the accounting status 
            of employee options lies a lack of agreement on the correct valuation 
            procedure for them. For this, we propose a discrete-time algorithm 
            based on pricing techniques for derivatives in incomplete-markets. 
            The two salient features of the method are that it takes into account 
            the non-linearity inherent to risk preferences, as well as the possibility 
            of partial hedge using a correlated instrument, such as a market index. 
            The immediate effect of non-linearity is that the optimal exercise 
            policy for the employee consists of partial exercise over en extended 
            period of time, as opposed to immediate exercise as soon as the underlying 
            reaches a threshold. The effect of trading on a correlated asset, 
            on the other hand, counter-balances that of risk aversion and can 
            be used to greatly increase the value of the option for the employee, 
            and consequently its cost for the issuing firm.
          and
          Dan Rosen, Fields Institute
            Economic Capital Allocation, Risk Contributions and Diversification 
            in Credit Portfolios 
          Concentration risk is arguably the most important cause of major 
            problems in banks, according to the Basel committee of Banking Supervision. 
            The reverse side of the coin, diversification, is one of the key tools 
            for managing the risk of credit portfolios. A thorough understanding 
            of diversification/concentration risk is vital for allocating optimally 
            economic credit capital. This is required for pricing, profitability 
            assessment and limits, building optimal risk-return portfolios and 
            strategies, performance measurement and risk based compensation. 
          This seminar presents a practical overview of the measurement of 
            diversification and risk capital contributions in credit portfolios 
            and their application to capital allocation. We stress several key 
            points. First, marginal risk contributions provide a useful basis 
            for allocating capital since they are additive and reflect the benefits 
            of diversification within a portfolio. Second, the choice of the risk 
            measure can have a substantial impact on capital allocation. In particular, 
            the quantile level chosen for measuring VaR or expected shortfall 
            (ES) can also have a significant impact on the relative amount of 
            capital allocated to portfolio components. Third, diversification 
            measures and risk contributions can be calculated analytically under 
            certain models. These methods provide fast calculations and can be 
            used to understand capital allocation strategies better, but they 
            may present some practical limitations, as well. Finally, Monte Carlo 
            methods may be required to compute risk contributions in more realistic 
            credit models. Computing VaR and ES contributions is challenging, 
            especially at the extreme quantiles typically used for credit capital 
            definition.
          
        
        February 22, 2006
         
          Hyejin Ku, Department of Math and Statistics, York University
            Liquidity Risk with Coherent Risk Measures
          We consider questions related to the regulation of liquidity risk. 
            Basically, the firm should be able to unwind its current position 
            without too much loss of its wealth if it were required to do so. 
            Liquidity risk is important in deciding whether a firm's position 
            is "acceptable" or not. We develop a method to incorporate 
            liquidity risk into risk measurement. We consider a portfolio to be 
            acceptable if it can (by trading) be turned into an ?acceptable" 
            cash-only position having positive future cash flows at some fixed 
            date, and present an example of modeling liquidity.
          and
          Ajay Subramanian, Assistant Professor of Risk Management and 
            Insurance
            J. Mack Robinson College of Business, Georgia State University
            Asymmetric Beliefs, Agency Conflicts, and Venture Capital Investment 
            
          We develop a dynamic principal-agent model to examine the interplay 
            among risk, imperfect information, agency conflicts, and asymmetric 
            beliefs on the characteristics of venture capital (VC) relationships---the 
            economic value that they generate, the durations of relationships, 
            the structures of long-term contracts between VCs and entrepreneurs 
            (ENs), and the manner in which VC investment is staged over time. 
            We show that the presence of asymmetric beliefs about project quality 
            has a substantial beneficial impact on project value and the expected 
            payoff to the VC implying that VCs have significant incentives to 
            encourage entrepreneur optimism. We analytically characterize the 
            effects of the project's characteristics---its systematic and technical 
            risk, and the degree of asymmetry in beliefs about its quality---on 
            the path of staged investments by the VC and the structure of the 
            long-term contract between the VC and the EN. Consistent with empirical 
            evidence, we predict that varying project characteristics lead to 
            significant heterogeneity in contractual structures and investment 
            schedules. The systematic and technical risks of projects have opposite 
            effects on the durations and economic values of VC relationships. 
            The duration, project value, and the expected payoff to the VC decrease 
            with the project's systematic risk but increase with its technical 
            risk, which leads to the striking implication that the value of the 
            project and the expected payoff to the VC are actually enhanced when 
            there is greater noise in the perception of project quality. Broadly, 
            our study not only demonstrates that the interactions among agency 
            conflicts, imperfect information, and asymmetric beliefs have a major 
            impact on the VC-EN relationship, but also precisely describes the 
            manner in which they affect this relationship.
          
          Authors are Yahel Giat, Steven T. Hackman, and Ajay Subramanian .
        
        January 25, 2006 -- 5:00 pm.
         
          Roger Stein, Moodys
             Better Predictions of Income Volatility Using a Structural Default 
            Model
            We propose a novel approach to predicting future volatility of company 
            earnings, in this case EBITDA. Our approach combines predictions of 
            a firms probability of default with insights from a structural 
            model of default. The source of the probabilities of default can be 
            econometric, structural, reduced-form or other models or agency ratings, 
            provided the source has high predictive power. We use these probabilities 
            to imply EBITDA volatility using a stylized, liquidity-based model 
            of firm default similar in some ways to that originally proposed by 
            Wilcox (1971). The method does not require market information and 
            our out-of-sample testing suggests that our approach is more accurate 
            in estimating future volatility than the historical volatility of 
            EBIDTA. Importantly, the method also produced reasonable estimates 
            of volatility when historical data is quite limited, for instance 
            when no historical financial data are available for the firm. In addition 
            in comparison with historical volatility estimates the implied volatility 
            estimates appear provide incremental information useful in identifying 
            those firms that are more likely to experience EBITDA. Beyond implied 
            volatility, we explore extensions of the approach for estimating implied 
            liquidity requirements and target growth rates for firms, given a 
            starting capital structure and variable cash flow stream.
          and
          David Lando, Copenhagen Business School
            Decomposing Swap Spreads
            We analyze a six-factor model for Treasury bonds, corporate bonds, 
            and swap rates and decompose swap spreads into three components: A 
            convenience yield from holding Treasuries, a credit risk element from 
            the underlying LIBOR rate, and a factor specific to the swap market. 
            In the later part of our sample, the swap-specific factor is strongly 
            correlated with hedging activity in the MBS market. The model further 
            sheds light on the relationship between AA hazard rates and the spread 
            between LIBOR rates and GC repo rates and on the level of the riskless 
            rate compared to swap and Treasury rates.
            (Joint work with Peter Feldhütter) 
        
        November 23, 2005 -- 5:00 p.m.
         
          Steven Kou, Columbia University
            Credit Spreads, Optimal Capital Structure, and Implied Volatility 
            with Endogenous Default and Jump Risk
            
          We propose a two-sided jump model for credit risk by extending the 
            Leland-Toft endogenous default model based on the geometric Brownian 
            motion. The model shows that jump risk and endogenous default can 
            have significant impacts on credit spreads, optimal capital structure, 
            and implied volatility of equity options: (1) The jump and endogenous 
            default can produce a variety of non-zero credit spreads, including 
            upward, humped, and downward shapes; interesting enough, the model 
            can even produce, consistent with empirical findings, upward credit 
            spreads for speculative grade bonds. (2) The jump risk leads to much 
            lower optimal debt/equity ratio; in fact, with jump risk, highly risky 
            firms tend to have very little debt. (3) The two-sided jumps lead 
            to a variety of shapes for the implied volatility of equity options, 
            even for long maturity options; and although in general credit spreads 
            and implied volatility tend to move in the same direction under exogenous 
            default models, but this may not be true in presence of endogenous 
            default and jumps. In terms of mathematical contribution, we give 
            a proof of a version of the ``smooth fitting'' principle for the jump 
            model, justifying a conjecture first suggested by Leland and Toft 
            under the Brownian model.
          and
          Mary Hardy, University of Waterloo
             Stock Return Models for Long Term Embedded Options'
          Insurance companies in Canada and the USA have found that adding 
            out-of-the-money guarantees to mutual fund type investments creates 
            a product which is highly popular. The risk management of these contracts 
            is challenging. A crucial part of the problem is finding a real world 
            model for the mutual fund returns that adequately captures the tails.
          In this talk I will briefly describe how actuaries approach the risk 
            management of these contracts, and then will present some of the many 
            models proposed for equity returns. It emerges that very small tweaks 
            in the equity model can make a significant difference to the resulting 
            regulatory capital. Using (and abusing) a bootstrap approach we show 
            how to determine which of these models can be justified using the 
            historic data.
          
        
        October 26, 2005 -- 5:00 p.m.
         
          Nizar Touzi, University Paris I-Pantheon-Sorbonne
            Modelling continuous-time financial markets with capital gains 
            taxes
            We formulate a model of continuous time financial market consisting 
            of a bank account with constant interest rate and one risky asset 
            subject to transaction costs and capital gains taxes. The taxation 
            rule is linear so that it allows for tax credits when capital losses 
            are experienced. We consider the problem of maximizing expected utility 
            from future consumption in infinite horizon. We first derive lower 
            and upper bounds on the value function in erms of the corresponding 
            value function in the tax free and frictionless model. In particular, 
            these bounds allow to obtain an explicit first order expansion of 
            our value function for small interest rate and tax rate coefficients. 
            We next provide a characterization of the value function in terms 
            of the associated dynamic programming equation, and we suggest a numerical 
            approximation scheme based on finite differences and the Howard 
            algorithm. The numerical results show that the first order Taylor 
            expansion is very accurate for reasonable market data.
            
            and
            
            Marco Frittelli, Università degli Studi di Firenze
            A Unifying Framework for Utility Maximization Problems with Unbounded 
            SemimartingalesDuring the past twenty years, the theory of expected 
            utility maximization in continuous-time stochastic incomplete markets 
            has 
            constantly improved, but a case has been left apart: exactly the situation 
            examined in this talk where the semi-martingale X, describing the 
            price evolution of a finite number of assets, can be possibly unbounded. 
            This is a non-trivial extension, from a mathematical but also from 
            a financial point of view.
            
            In fact, in highly risky markets (i.e. with unbounded losses in the 
            trading: think of X as a Compound Poisson process on a finite horizon, 
            with unbounded jumps) the traditional approach to the problem leads 
            to trivial maximization: the optimal choice for the agent would be 
            investing the initial endowment entirely in the risk free asset. However, 
            it could happen that some of the investors are willing to take a greater 
            risk: mathematically speaking, they accept trading strategies that 
            may lead to unbounded losses. This risk-taking attitude gives them 
            the concrete possibility of increasing their expected utility from 
            terminal wealth.
          
          In a unified framework, we consider the utility maximization problem 
            for utility functions that can be finite valued on the whole real 
            line or only on the positive semi axes and we select a generalized 
            class of trading strategies which allows for unbounded stochastic 
            integrals. By duality methods we prove existence of the optimal solution 
            to both the dual and the primal problems.
            As it is widely known, the utility maximization problem is linked 
            to derivative pricing through the so-called indifference pricing technique. 
            Such a technique is far from being a theoretical speculation, since 
            it is currently used by financial institutions to price new and/or 
            illiquid derivatives. The results here presented allow tackling this 
            problem in the general case of a non-necessarily locally bounded semi-martingale 
            price process.
          
        
        September 28, 2005 -- 5:00 p.m.
         
          Dmitry Kramkov, Carnegie Mellon
            Sensitivity analysis of utility based prices and risk-tolerance 
            wealth processes
            In the general framework of a semimartingale financial model and 
            a utility function U defined on the positive real line we compute 
            the first order expansion of marginal utility based prices with respect 
            to a ``small'' number of random endowments. We show that this linear 
            approximation has some important qualitative properties if and only 
            if there is a risk-tolerance wealth process. In particular, they hold 
            true in the following polar cases:
            (i) for any utility function U if and only if the set of state price 
            densities has a greatest element from the point of view of second 
            order stochastic dominance 
            (ii) for any financial model if and only if U is a power utility function 
            (U is an exponential utility function if it is defined on the whole 
            real line).
            The presentation is based on a joint paper with Mihai Sirbu.
          
          and
          Mark Reesor, University of Western Ontario
            A Debt Strategy Simulation Framework and Interest-rate Model Risk
            Debt strategy is the manner in which governments (or agencies 
            and corporations) issue bonds to cover their funding requirements. 
            The issuer has some control over the relative amounts of bond issuance 
            across the maturity spectrum, making this problem analogous to the 
            typical portfolio selection problem. Furthermore, there are additional 
            constraints that are unique to the problem of managing a large portfolio 
            of public debt. We discuss how this bond issuance problem can be formulated 
            as a (constrained) stochastic optimal control problem, along with 
            a simulation framework that allows for its analysis. Clearly a model 
            for interest rates is one of the main components of such a framework. 
            Using a simple example, we investigate the issue of model risk in 
            the debt strategy analysis.
            This is joint work with Shudan Liu, a PhD student in the Dept of Applied 
            Math, UWO.
        
         
           
             
               
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