Rational Hedging and Valuation with Utility-Based Preferences Dirk

Total Page:16

File Type:pdf, Size:1020Kb

Rational Hedging and Valuation with Utility-Based Preferences Dirk Rational Hedging and Valuation with Utility-Based Preferences vorgelegt von Diplom-Mathematiker Dirk Becherer aus L¨udenscheid Von der Fakult¨atII - Mathematik und Naturwissenschaften der Technischen Universit¨atBerlin zur Erlangung des akademischen Grades Doktor der Naturwissenschaften { Dr. rer. nat. { genehmigte Dissertation Vorsitzender des Promotionsausschusses: Prof. Dr. Fredi Troltzsch¨ { Technische Universit¨atBerlin Berichter: Prof. Dr. Mark H. A. Davis { Imperial College of Science and Technology, London Prof. Dr. Peter Imkeller { Humboldt-Universit¨atzu Berlin Prof. Dr. Martin Schweizer { Ludwig-Maximilians-Universit¨atM¨unchen Tag der wissenschaftlichen Aussprache: 8. Oktober 2001 Berlin 2001 D 83 Abstract In this thesis, we study stochastic optimization problems in which concave functionals are maximized on spaces of stochastic integrals. Such problems arise in mathematical finance for a risk-averse investor who is faced with valuation, hedging, and optimal investment problems in incomplete financial markets. We are mainly concerned with utility-based methods for the valuation and hedging of non-replicable contingent claims which confront the issuer with some inevitable intrinsic risks. We adopt the perspective of a rational investor who aims to maximize his expected exponential utility. Based on these preferences, the issuer's valuation process and hedging strategy are defined via utility indifference arguments. In a general semimartingale model, the solution to this problem is characterized by a stochastic representation problem. Solving the problem amounts to finding a martingale measure whose density process can be written in a particular form. We then specialize our analysis to two stochastic models which satisfy further structural assumptions. In a semi-complete product model, the valuation and hedging methods are shown to be additive when applied to an aggregate of “sufficiently independent" individual claims. We study the impact of diversification and derive a computation scheme. For a second model, we set up a Markovian system of stochastic differential equations which describes the dynamics of an It^oprocess and an additional finite-state process, and permits for various dependencies between both. In the financial market model, the It^oprocess models the price fluctuations of the risky assets while the second process represents some untradable factors of risk. The solution to the pricing and hedging problem is explicitly described by an interacting system of semi-linear partial differential equations { a so-called reaction-diffusion equation. Using Feynman-Kac results and the Picard-iteration method, we establish existence and uniqueness of a classical solution. In a variation of the basic theme, a similar utility indifference approach is applied to quantify the value of additional investment information. On the mathematical side, this involves a mar- tingale preserving measure transformation and martingale representation results for initially enlarged filtrations. Finally, we show that the so-called numeraire portfolio is related to an- other utility-based valuation method which relies on a marginal rate of substitution argument and can be seen as a limiting case of the utility indifference method. i Zusammenfassung Die vorliegende Arbeit behandelt stochastische Optimierungsprobleme, in denen ein konkaves Funktional ¨uber einem Raum von stochastischen Integralen maximiert wird. In der Finanz- mathematik treten derartige Probleme bei der Behandlung von Bewertungs-, Absicherungs-, und Anlageproblemen in unvollst¨andigenFinanzm¨arktenauf. Wir besch¨aftigenuns vornehm- lich mit nutzenbasierten Methoden zur Bewertung und Absicherung von zufallsbehafteten Finanzpositionen, welche unvermeidbare intrinsische Risiken beinhalten. Wir betrachten das Problem aus der Perspektive eines rationalen Investors, dessen Ziel die Maximierung seines erwarteten exponentiellen Nutzens ist. Ausgehend von diesen Pr¨aferenzen, definieren wir mittels Nutzenindifferenz-Argumenten seinen Bewertungsprozess und eine Ab- sicherungsstrategie. In einem Semimartingalmodell kann die L¨osungdurch ein stochastisches Darstellungsproblem charakterisiert werden. Um das Problem zu l¨osen,gilt es ein Martingal- maß zu finden, dessen Dichteprozess eine bestimmte Form hat. Im Weiteren untersuchen wir zwei Modelle, welche gewissen strukturellen Bedingungen gen¨ugen.In einem halbvollst¨andigen Produktmodell wird gezeigt, dass die Nutzenindifferenz-Bewertungs- und Absicherungsme- thode additiv ist, wenn sie auf ein Aggregat von \gen¨ugendunabh¨angigen"Positionen ange- wandt wird. Wir untersuchen Diversifikationseffekte und leiten ein Berechnungsschema her. F¨urdas zweite Modell betrachten wir ein Markovsches System stochastischer Differentialgle- ichungen, welches einen It^o-Prozessund einen weiteren Prozess mit endlichem Zustandsraum beschreibt und verschiedene wechselseitige Abh¨angigkeiten zul¨asst. In unserem Marktmod- ell stellt der It^o-Prozessdie Preise der riskanten Anlagen dar w¨ahrendder zweite Prozess irgendwelche nicht handelbaren Risikofaktoren repr¨asentiert. Die L¨osungdes Bewertungs- und Absicherungsproblems wird durch ein wechselwirkenendes System semilinearer partieller Differentialgleichungen, eine so genannte Reaktions-Diffusions Gleichung, beschrieben. Mit- tels Feynman-Kac Resultaten und der Iterationstechnik von Picard zeigen wir Existenz und Eindeutigkeit einer klassischen L¨osung. Erg¨anzendzu unserem Hauptthema nutzen wir ein ¨ahnliches Indifferenzargument um den Wert von zus¨atzlichen Anlage-Informationen zu quantifizieren. Die wesentlichen Mittel sind eine Martingal erhaltende Maßtransformation und Martingal-Darstellungsresultate f¨uranfangsver- gr¨oßerteFiltrationen. Schließlich zeigen wir, dass das so genannte Numeraire-Portfolio mit einer weiteren nutzenbasierten Bewertungsmethode zusammenh¨angt,welche sich auf ein Gren- znutzenargument st¨utztund als Grenzfall der Indifferenz-Methode angesehen werden kann. iii Contents Introduction 1 I RATIONAL PRICING AND HEDGING OF CONTINGENT CLAIMS 13 1 General results for exponential utility 15 1.1 General semimartingale framework . 16 1.2 Duality results on exponential utility optimization . 17 1.3 Utility indifference pricing . 20 1.4 Utility indifference hedging . 24 2 Results in semi-complete product models 29 2.1 The semi-complete model . 30 2.2 The structure of the equivalent martingale measures . 31 2.3 Additivity and diversification . 33 2.4 A computation scheme and explicit bounds . 36 3 PDE-solutions in incomplete SDE-models 41 3.1 The incomplete SDE-model . 41 3.2 Construction of S-dependent intensities . 44 3.3 Some case studies . 45 3.4 Solutions to the utility maximization problem . 46 3.5 Solutions to the rational pricing and hedging problem . 57 4 Applications 61 4.1 The financial market model . 61 4.2 General solution by reaction-diffusion equations . 62 4.3 Equity-linked life insurance contracts . 64 4.4 Default and credit risk . 67 4.5 Stochastic volatility . 70 v 4.6 Weather derivatives . 72 II INITIAL ENLARGEMENT OF FILTRATIONS AND THE VALUE OF INVESTMENT INFORMATION 77 5 The value of initial investment information 79 5.1 General framework and preliminaries . 80 5.2 Strong predictable representation property . 86 5.3 Utility maximization with non-trivial initial information . 89 5.4 Utility indifference value of initial information . 97 5.5 Examples: Terminal information distorted by noise . 100 III ON THE NUMERAIRE PORTFOLIO 105 6 The numeraire portfolio 107 6.1 General framework and preliminaries . 109 6.2 The growth-optimal numeraire . 112 6.3 The numeraire portfolio . 113 6.4 Examples . 119 IV REACTION DIFFUSION EQUATIONS 125 7 Reaction-diffusion equations 127 7.1 General framework . 127 7.2 Fixed points of the Feynman-Kac representation . 128 7.3 Classical solutions to interacting systems of PDEs . 129 Index of Notation 135 vi Introduction In this thesis, we study stochastic optimization problems in which concave functionals are maximized on spaces of stochastic integrals. Such problems arise in mathematical finance for a risk-averse investor who is faced with valuation, hedging, risk management and optimal investment problems in incomplete financial markets. The emphasis of this thesis is on utility- based methods for the valuation and hedging of non-replicable contingent claims which confront the issuer with some inevitable intrinsic risks. If the payoff of a contingent claim is replicable by dynamic trading, the claim can be perfectly hedged by the replicating strategy, and its price is determined as the replication costs. However, such claims are dynamically redundant and have apparently little reason to exist. In incomplete markets, a contingent claim may be not redundant but incorporate some unavoidable risk. Hence, the issuer's valuation and hedging strategy have to take into account his attitudes and preferences towards risk. We adopt the perspective of a rational investor who aims to maximize his expected utility according to his level of risk aversion. In doing so, the investor balances his two conflicting objectives to maximize return and minimize risk. Based on these preferences, the utility indifference price π of a contingent claim is defined as the amount of money, which makes a potential issuer indifferent { in terms of maximal expected utility { between the opportunity to earn the premium π and take the liability associated with the claim, and the alternative to skip the deal. The hedging strategy for the contingent claim is defined as the adjustment of the investor's optimal
Recommended publications
  • Rational Multi-Curve Models with Counterparty-Risk Valuation Adjustments
    Post-Crisis Interest Rate Markets and Models Rational Multi-Curve Models Rational Bilateral Counterparty Risk Model Conclusion Rational Multi-Curve Models with Counterparty-Risk Valuation Adjustments Stéphane Crépey Université d'Evry Val-d'Essonne, Laboratoire de Mathématiques et Modélisation d'Evry (LaMME) Joint work with A. Macrina, T. M. Nguyen and D. Skovmand 7th General AMaMeF and Swissquote Conference EPFL, 7-10 September 2015 The research presented in these slides beneted from the support of the Chair Markets in Transition under the aegis of Louis Bachelier laboratory, a joint initiative of École polytechnique, Université d'Évry Val d'Essonne and Fédération Bancaire Française 1 / 49 Post-Crisis Interest Rate Markets and Models Rational Multi-Curve Models Rational Bilateral Counterparty Risk Model Conclusion Outline 1 Post-Crisis Interest Rate Markets and Models 2 Rational Multi-Curve Models 3 Rational Bilateral Counterparty Risk Model 4 Conclusion 2 / 49 Post-Crisis Interest Rate Markets and Models Rational Multi-Curve Models Rational Bilateral Counterparty Risk Model Conclusion Libor Most interest-rate derivatives have Libor-indexed cash-ows (Libor xings) What is Libor? Libor stands for London InterBank Oered Rate. It is produced for 10 currencies with 15 maturities quoted for each, ranging from overnight to 12 Months producing 150 rates each business day. Libor is computed as a trimmed average of the interbank borrowing rates assembled from the Libor contributing banks. More precisely, every contributing bank has to submit an
    [Show full text]
  • The Fama and French Three-Factor Model and Leverage: Compatibility with the Modigliani and Miller Propositions”
    “The Fama and French three-factor model and leverage: compatibility with the Modigliani and Miller propositions” AUTHORS Michael Dempsey https://orcid.org/0000-0002-9059-0416 Michael Dempsey (2009). The Fama and French three-factor model and ARTICLE INFO leverage: compatibility with the Modigliani and Miller propositions. Investment Management and Financial Innovations, 6(1) RELEASED ON Monday, 16 March 2009 JOURNAL "Investment Management and Financial Innovations" FOUNDER LLC “Consulting Publishing Company “Business Perspectives” NUMBER OF REFERENCES NUMBER OF FIGURES NUMBER OF TABLES 0 0 0 © The author(s) 2021. This publication is an open access article. businessperspectives.org Investment Management and Financial Innovations, Volume 6, Issue 1, 2009 Michael Dempsey (Australia) The Fama and French three-factor model and leverage: compatibility with the Modigliani and Miller propositions Abstract The issue of whether the Fama and French (FF) three-factor model is consistent with the propositions of Modigliani and Miller (MM) (1958, 1963) has received surprisingly little attention. Yet, unless it is so, the model is at variance with the foundations of finance. Fama and French (FF) (1993, 1995, 1996, 1997) argue that their three-factor asset pricing model is representative of equilibrium pricing models in the spirit of Merton’s (1973) inter-temporal capital asset pricing model (ICAPM) or Ross’s (1976) arbitrage pricing theory (APT) (FF, 1993, 1994, 1995, 1996). Such claims, however, are compromised by the observations of Lally (2004) that the FF (1997) loadings on the risk factors lead to outcomes that are contradictory with rational asset pricing. In response, we outline an approach to adjustment for leverage that leads by construction to compatibility of the FF three-factor model with the Modigliani and Miller propositions of rational pricing.
    [Show full text]
  • On Valuing American Call Options with the Black-Scholes European Formula Author(S): Robert Geske and Richard Roll Source: the Journal of Finance, Vol
    American Finance Association On Valuing American Call Options with the Black-Scholes European Formula Author(s): Robert Geske and Richard Roll Source: The Journal of Finance, Vol. 39, No. 2 (Jun., 1984), pp. 443-455 Published by: Wiley for the American Finance Association Stable URL: http://www.jstor.org/stable/2327870 Accessed: 06-03-2018 17:33 UTC JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at http://about.jstor.org/terms American Finance Association, Wiley are collaborating with JSTOR to digitize, preserve and extend access to The Journal of Finance This content downloaded from 131.179.13.248 on Tue, 06 Mar 2018 17:33:47 UTC All use subject to http://about.jstor.org/terms THE JOURNAL OF FINANCE * VOL. XXXIX, NO. 2 * JUNE 1984 On Valuing American Call Options with the Black-Scholes European Formula ROBERT GESKE and RICHARD ROLL* ABSTRACT Empirical papers on option pricing have uncovered systematic differences between market prices and values produced by the Black-Scholes European formula. Such "biases" have been found related to the exercise price, the time to maturity, and the variance. We argue here that the American option variant of the Black-Scholes formula has the potential to explain the first two biases and may partly explain the third.
    [Show full text]
  • Risk, Uncertainty and Asset Prices
    Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. Risk, Uncertainty and Asset Prices Geert Bekaert, Eric Engstrom, and Yuhang Xing 2005-40 NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. References in publications to the Finance and Economics Discussion Series (other than acknowledgement) should be cleared with the author(s) to protect the tentative character of these papers. Risk, Uncertainty and Asset Prices Geert Bekaert∗ Columbia University and NBER Eric Engstrom Federal Reserve Board of Governors Yuhang Xing Rice University This Draft: 25 July 2005 JEL Classifications G12, G15, E44 Keyphrases Equity Premium, Uncertainty, Stochastic Risk Aversion, Time Variation in Risk and Return, Excess Volatility, External Habit, Term Structure Abstract: We identify the relative importance of changes in the conditional variance of fundamentals (which we call “uncertainty”) and changes in risk aversion (“risk” for short) in the determination of the term structure, equity prices and risk premiums. Theoretically, we introduce persistent time-varying uncertainty about the fundamentals in an external habit model. The model matches the dynamics of dividend and consumption growth, including their volatility dynamics and many salient asset market phenomena. While the variation in dividend yields and the equity risk premium is primarily driven by risk, uncertainty plays a large role in the term structure and is the driver of counter-cyclical volatility of asset returns.
    [Show full text]
  • Formulation of a Rational Option Pricing Model Using Artificial Neural
    Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 17 December 2020 doi:10.20944/preprints202012.0426.v1 Formulation Of A Rational Option Pricing Model using Artificial Neural Networks Kaustubh Yadav School Of Computer Science and Engineering (Vellore Institute Of Technology) Vellore, Tamil Nadu, India [email protected] Abstract—This paper inquires on the options pricing modeling Subsequent approaches in improving on the Black-Scholes using Artificial Neural Networks to price Apple(AAPL) European Model, included modelling volatility as a stochastic process Call Options. Our model is based on the premise that Artificial [2], [4], [5], [6], [3]. Though these modes are an improvement Neural Networks can be used as functional approximators and can be used as an alternative to the numerical methods to some on the Black-Scholes Model in the sense that they use stochas- extent, for a faster and an efficient solution. This paper provides tic volatility to recreate practical conditions, these models a neural network solution for two financial models, the Black- still fail to capture deep out-of-money options. Also with the Scholes-Merton model, and the calibrated-Heston Stochastic introduction of stochastic volatility, there are two stochastic Volatility Model, we evaluate our predictions using the existing processes which increases the computational costs, and these numerical solutions for the same, the analytic solution for the Black-Scholes equation, COS-Model for Heston’s Stochastic models don’t perform exceptionally better than Black-Scholes Volatility Model and Standard Heston-Quasi analytic formula. hence Black-Scholes is still widely used. The research for The aim of this study is to find a viable time-efficient alternative finding a better solution brought non-parametric and semi- to existing quantitative models for option pricing.
    [Show full text]
  • On the Unconditional and Conditional Cross Section of Expected Futures Returns
    On the Unconditional and Conditional Cross Section of Expected Futures Returns A thesis submitted for the degree of Doctor of Philosophy by JoeIle Miffre Department of Economics and Finance, Brunel University 1998 A mes Parents Acknowledgements I would like to thank my parents for their love, encouragement, and generous support over the last twenty seven years. A special thanks to Main for his help during a trip through the south of France. To Professor Tony Antoniou, my supervisor, thanks for his helpful and insightful comments, his encouragement, and his financial support without which this thesis would never have been written. I am looking forward to some fruitful collaboration in the future. I also would like to thank Doctor Richard Priestley for his insightful suggestions and corrections on earlier drafts of the thesis and for his excellent supervision. Thanks to Doctor Andrew Clare for his early contribution to this thesis and to Professor Len Skerratt for his excellent co-ordination of the Ph.D. course in Brunel University. I am also very grateful to the friends and roommates that I have known throughout the years in Brunel. A very special thanks to Aysun, almost my sister, for being such a wonderful person. Thanks to my family and to my French and Greek friends who came to England and visited me over the years. In particular, Sylvie deserves special thanks for her countless trips to Uxbridge, for our endless discussions over the phone, and for being such a wonderful friend over the past seven years. 11 Abstract While most of the literature on asset pricing examines the cross section of stock and bond returns, little attention has been devoted to the analyse of the trade-off between risk and return in futures markets.
    [Show full text]
  • Equity Correlation Swaps: a New Approach for Modelling & Pricing Columbia University — Financial Engineering Practitioners Seminar
    26 February 2007 Equity Correlation Swaps: A New Approach For Modelling & Pricing Columbia University — Financial Engineering Practitioners Seminar Sebastien Bossu Equity Derivatives Structuring — Product Development Equity Correlation Swaps: A New Approach For Modelling & Pricing Disclaimer This document only reflects the views of the author and not necessarily those of Dresdner Kleinwort research, sales or trading departments. This document is for research or educational purposes only and is not intended to promote any financial investment or security. 2 Equity Correlation Swaps: A New Approach For Modelling & Pricing Introduction X The daily life of an Equity Exotic Structurer (1): X Q: ‘Can you price this payoff: ⎡ ⎤ ⎛ ST − S0 ⎞ min⎢20%,max⎜5%, ⎟⎥ ⎣ ⎝ S0 ⎠⎦ ?’ X A: Hedge is a fixed cash flow and a static call spread: 1 1 5% + max[]0, ST −105%× S0 − max[]0, ST −125%× S0 S0 S0 Price: PV(5%) + 1/S0 x (Call Spread 105-125) 3 Equity Correlation Swaps: A New Approach For Modelling & Pricing Introduction X The daily life of an Equity Exotic Structurer (2): X Q: ‘Can you price this payoff: 2 252 ⎛ St ⎞ ∑⎜ln ⎟ t=1 ⎝ St−1 ⎠ ?’ X A: 1-year variance. Hedge is a static portfolio of puts and calls approximating ln(ST/S0), delta-hedged daily. ⎡ 1 1 +∞ 1 ⎤ Price: 2 Put(k)dk + Call(k)dk ⎢ 2 2 ⎥ ⎣∫0 k ∫1 k ⎦ 4 Equity Correlation Swaps: A New Approach For Modelling & Pricing Introduction X The daily life of an Equity Exotic Structurer (3): X Q: ‘Can you price this payoff: 2 ∑ ρi, j N(N −1) i< j where ρi,j is the coefficient of correlation between stocks i and j observed between t = 0 and t = T?’ X A0: ‘Go home’ X A1: ‘Let me program this into our Monte-Carlo engine’ X A2: ‘Let me ask my broker’ 5 Equity Correlation Swaps: A New Approach For Modelling & Pricing Introduction X Pros and cons X A1: Monte-Carlo gives you a price but not a hedge.
    [Show full text]
  • Stephan Sturm February 2019
    Curriculum Vitae | Stephan Sturm February 2019 Contact Information Stephan Sturm Stratton Hall 202C Worcester Polytechnic Institute phone: (+ 1 ) 508 { 831 { 5921 Department of Mathematical Sciences fax: (+ 1 ) 508 { 831 { 5824 100 Institute Road email: [email protected] MA 01609, Worcester website: users.wpi.edu/~ssturm/ USA Research Interests: Mathematical Finance & Stochastic Analysis Employment Since 07/18 Associate Professor (tenured), Department of Mathematical Sciences, Worcester Polytechnic Institute 07/12 - 06/18 Assistant Professor (tenure track), Department of Mathematical Sciences, Worcester Polytechnic Institute 07/13 - 12/13 Lecturer, Department of Finance, School of Management, Boston University 02/10 - 08/12 RTG Postdoctoral Research Associate & Lecturer, ORFE Department, Princeton University 11/09 - 01/10 Research Fellow, DFG Research Center MATHEON, Berlin 04/04 - 08/09 Teaching Assistant, TU Berlin 07/01 - 08/01 Vienna University Computer Center, University of Vienna 07/00 - 08/00 AVL India Pvt. Ltd., Gurgaon (Haryana), India 08/98 - 09/99 Compulsory Civilian Service, Auschwitz Foundation, Brussels Education 04/04 { 01/10 PhD in Mathematics, TU Berlin Thesis: Small-time large deviations for sample paths of infinite dimensional symmetric Dirichlet processes (Adviser: Alexander Schied) 10/96 { 03/04 BS/MS in Mathematics, University of Vienna Thesis: Calculation of the Greeks by Malliavin Calculus (Advisers: Walter Schachermayer and Josef Teichmann) Administration 2019{21 Associate Editor, SIAM Journal on Financial Mathematics 2019{20 Associate Director, Center for Industrial and Applied Mathematics and Statistics, WPI Since 2018 Steering Committee, Eastern Conference on Mathematical Finance 1 Publications Peer-reviewed Journals 1) Z. Feinstein, W. Pang, B. Rudloff, E. Schaanning, S. Sturm and M.
    [Show full text]
  • Commodity Price Dynamics a Structural Approach
    Commodity Price Dynamics A Structural Approach Craig Pirrong Bauer College of Business University of Houston Contents Preface page vi 1 Introduction 1 1.1 Introduction 1 1.2 A Commodity Taxonomy 4 1.3 Commodity Markets and Data 6 1.4 An Overview of the Remainder of the Book 8 1.4.1 Modeling Storable Commodity Prices 9 1.4.2 A Two Factor Model of a Continuously Produced Commodity 9 1.4.3 The Empirical Performance of the Two Factor Model 9 1.4.4 Commodity Pricing With Stochastic Fundamen- tal Volatility 10 1.4.5 The Pricing of Seasonally Produced Commodities 10 1.4.6 The Pricing of Pollution Credits 11 1.4.7 Non-Storable Commodities Pricing: The Case of Electricity 12 1.5 Where This Book Fits in the Literature 12 2 Storables Modeling Basics 17 2.1 Introduction 17 2.2 Dynamic Programming and the Storage Problem: An Overview 19 2.2.1 Model Overview 19 2.2.2 Competitive Equilibrium 21 2.2.3 The Next Step: Determining the Forward Price 23 2.2.4 Specifying Functional Forms and Shock Dynamics 26 2.3 A More Detailed Look at the Numerical Implementation 29 iv Contents 2.3.1 Solving a PDE Using Finite Differences: The One Dimensional Case 35 2.3.2 Solving the 2D PDE 36 2.3.3 Boundary Conditions 38 2.4 Summary 40 3 Continuously Produced Commodity Price Dynamics 41 3.1 Introduction 41 3.2 The Storage Economy With a Continuously Produced Commodity 44 3.2.1 Introduction 44 3.2.2 Framework and Numerical Solution 44 3.3 Moments and the State Variables 46 3.4 Derivatives Pricing 49 3.5 Extension: Storage Capacity Constraints 56 3.6 speculationspeculation
    [Show full text]
  • Lecture Notes: Topics in Asset Pricing: Part1
    Topics in Asset Pricing Lecture Notes Professor Doron Avramov Background, Objectives, and Pre-requisite The past few decades have been characterized by an extraordinary growth in the use of quantitative methods in the analysis of various asset classes; be it equities, fixed income securities, commodities, currencies, and derivatives. In response, financial economists have routinely been using advanced mathematical, statistical, and econometric techniques to understand asset pricing models, market anomalies, equity premium predictability, asset allocation, security selection, volatility, correlation, and the list goes on. This course attempts to provide a fairly deep understanding of such topical issues. It targets advanced master and PhD level students in finance and economics. Required: prior exposure to matrix algebra, distribution theory, Ordinary Least Squares, as well as kills in computer programing beyond Excel: MATLAB, R, and Python are the most recommended for this course. STATA or SAS are useful. 2 Topics to be covered From CAPM to market anomalies Credit risk implications for the cross section of asset returns Rational versus behavioural attributes of stylized cross-sectional effects Are market anomalies pervasive? Conditional CAPM Conditional versus unconditional portfolio efficiency Multi-factor models Interpreting factor models Panel regressions with fixed effects and their association with market-timing and cross-section investment strategies Machine learning methods: Lasso, Ridge, elastic net, group Lasso,
    [Show full text]
  • CHAPTER 5 REAL OPTION VALUATION the Essence of Real
    1 CHAPTER 5 REAL OPTION VALUATION The approaches that we have described in the last three chapters for assessing the value of an asset, for the most part, are focused on the negative effects of risk. Put another way, they are all focused on the downside of risk and they miss the opportunity component that provides the upside. The real options approach is the only one that gives prominence to the upside potential for risk, based on the argument that uncertainty can sometimes be a source of additional value, especially to those who are poised to take advantage of it. We begin this chapter by describing in very general terms the argument behind the real options approach, noting its foundations in two elements – the capacity of individuals or entities to learn from what is happening around them and their willingness and the ability to modify behavior based upon that learning. We then describe the various forms that real options can take in practice and how they can affect the way we assess the value of investments and our behavior. In the last section, we consider some of the potential pitfalls in using the real options argument and how it can be best incorporated into a portfolio of risk assessment tools. The Essence of Real Options To understand the basis of the real options argument and the reasons for its allure, it is easiest to go back to risk assessment tool that we unveiled in chapter 6 – decision trees. Consider a very simple example of a decision tree in figure 5.1: Figure 5.1: Simple Decision Tree p =1/2 $ 100 -$120 1-p =1/2 Given the equal probabilities of up and down movements, and the larger potential loss, the expected value for this investment is negative.
    [Show full text]
  • Rational Multi-Curve Models with Counterparty-Risk Valuation Adjustments
    Rational Multi-Curve Models with Counterparty-Risk Valuation Adjustments St´ephaneCr´epey 1; Andrea Macrina 2;3, Tuyet Mai Nguyen1, David Skovmand 4 1 Laboratoire de Math´ematiqueset Mod´elisationd'Evry,´ France 2 Department of Mathematics, University College London, United Kingdom 3 Department of Actuarial Science, University of Cape Town, South Africa 4 Department of Finance, Copenhagen Business School, Denmark February 27, 2015 Abstract We develop a multi-curve term structure setup in which the modelling ingredients are expressed by rational functionals of Markov processes. We calibrate to LIBOR swaptions data and show that a rational two-factor lognormal multi-curve model is suf- ficient to match market data with accuracy. We elucidate the relationship between the models developed and calibrated under a risk-neutral measure Q and their consistent equivalence class under the real-world probability measure P. The consistent P-pricing models are applied to compute the risk exposures which may be required to comply with regulatory obligations. In order to compute counterparty-risk valuation adjustments, such as CVA, we show how positive default intensity processes with rational form can be derived. We flesh out our study by applying the results to a basis swap contract. Keywords: Multi-curve interest rate term structure, forward LIBOR process, rational asset pricing models, calibration, counterparty-risk, risk management, Markov func- tionals, basis swap. 1 Introduction arXiv:1502.07397v1 [q-fin.MF] 25 Feb 2015 In this work we endeavour to develop multi-curve interest rate models which extend to counterparty risk models in a consistent fashion. The aim is the pricing and risk manage- ment of financial instruments with price models capable of discounting at multiple rates (e.g.
    [Show full text]