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2. Asset Pricing : Modeling and Estimation [2004]
 Kellerhals, B. Philipp.
 Second edition.  Berlin, Heidelberg : Springer Berlin Heidelberg, 2004.
 Description
 Book — 1 online resource (xiv, 243 pages) Digital: text file.PDF.
 Summary

 I Asset Pricing Framework. 1 Financial Modeling. 1.1 ContinuousTime Stochastics. 1.1.1 Stochastic Processes and Brownian Motion. 1.1.2 Martingales, Ito Calculus, and Changes of Measure. 1.2 Arbitrage Pricing in Continuous Time. 1.2.1 PDE Approach. 1.2.2 EMM Approach. 2 Estimation Principles. 2.1 State Space Notation. 2.2 Filtering Algorithms. 2.2.1 Filtering Objective. 2.2.2 Optimal Estimator. 2.2.3 Filter Recursions. 2.2.4 Extended Kalman Filtering. 2.3 Parameter Estimation. II Pricing Equities. 3 Introduction and Survey. 3.1 Opening Remarks. 3.2 ClosedEnd Funds: Survey and Hypotheses. 4 Valuation Model. 4.1 Characteristics of ClosedEnd Funds. 4.2 Economic Foundation. 4.3 Pricing ClosedEnd Fund Shares. 5 First Empirical Results. 5.1 Sample Data. 5.2 Implemented Model. 5.3 State Space Form. 5.4 ClosedEnd Fund Analysis. 6 Implications for Investment Strategies. 6.1 Testing the Forecasting Power. 6.1.1 Setup of Forecasting Study. 6.1.2 Evidence on Forecasting Quality. 6.2 Implementing Trading Rules. 6.2.1 Experimental Design. 6.2.2 Test Results on Trading Strategies. 7 Summary and Conclusions. III Pricing FixedIncome Securites. 8 Introduction and Survey. 8.1 Overview. 8.2 Bond Prices and Interest Rates. 8.3 Dynamic Term Structure Models. 9 Term Structure Model. 9.1 Modeling an Incomplete Market. 9.2 Motivation for a Stochastic Risk Premium. 9.3 Economic Model. 10 Initial Characteristic Results. 10.1 Valuing Discount Bonds. 10.2 Term Structures of Interest Rates and Volatilities. 10.2.1 Spot and Forward Rate Curves. 10.2.2 Term Structure of Volatilities. 10.3 Analysis of Limiting Cases. 10.3.1 Reducing to an OrnsteinUhlenbeck Process. 10.3.2 Examining the Asymptotic Behavior. 10.4 Possible Shapes of the Term Structures. 10.4.1 Influences of the State Variables. 10.4.2 Choosing the Model Parameters. 11 Risk Management and Derivatives Pricing. 11.1 Management of Interest Rate Risk. 11.2 Pricing Interest Rate Derivatives. 11.2.1 Bond Options. 11.2.2 Swap Contracts. 11.2.3 Interest Rate Caps and Floors. 12 Calibration to Standard Instruments. 12.1 Estimation Techniques for Term Structure Models. 12.2 Discrete Time Distribution of the State Variables. 12.3 US Treasury Securities. 12.3.1 Data Analysis. 12.3.2 Parameter Estimation. 12.3.3 Analysis of the State Variables. 12.4 Other Liquid Markets. 12.4.1 Appropriate Filtering Algorithm. 12.4.2 Sample Data and Estimation Results. 13 Summary and Conclusions. IV Pricing Electricity Forwards. 14 Introduction and Survey. 14.1 Overview. 14.2 Commodity Futures Markets. 14.3 Pricing Commodity Futures. 14.4 Asset Pricing in Electricity Markets. 15 Electricity Pricing Model. 15.1 Model Assumptions and RiskNeutral Pricing. 15.2 Valuation of Electricity Forwards. 16 Empirical Inference. 16.1 Estimation Model. 16.1.1 Distribution of the State Variables. 16.1.2 State Space Formulation and Kalman Filter Setup. 16.2 Data Analysis and Estimation Results. 17 Summary and Conclusions. List of Symbols and Notation. List of Tables. List of Figures. References.
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 New York ; London : Springer, ©2010.
 Description
 Book — 1 online resource
 Summary

 Markowitz for the Masses: Portfolio Construction Techniques. Markowitz for the Masses: The Risk and Return of Equity and Portfolio Construction Techniques. Markowitz and the Expanding Definition of Risk: Applications of Multifactor Risk Models. Markowitz Applications in the 1990s and the New Century: Data Mining Corrections and the 130/30. Markowitz's MeanVariance Rule and the Talmudic Diversification Recommendation. On the Himalayan Shoulders of Harry Markowitz. Models for Portfolio Revision with Transaction Costs in the MeanVariance Framework. Principles for Lifetime Portfolio Selection: Lessons from Portfolio Theory. Harry Markowitz and the Early History of Quadratic Programming. Ideas in Asset and AssetLiability Management in the Tradition of H.M. Markowitz. Methodologies for Isolating and Assessing the Portfolio Performance Potential of Stock Return Forecast Models with an Illustration. Robust Portfolio Construction. Owitz and the Expanding Definition of Risk: Applications of MultiFactor Risk Models. Applying Markowitz's Critical Line Algorithm. Factor Models in Portfolio and Asset Pricing Theory. Applications of Markowitz Portfolio Theory To Pension Fund Design. Global Equity Risk Modeling. What Matters Most in Portfolio Construction?. Risk Management and Portfolio Optimization for Volatile Markets. Applications of Portfolio Construction, Performance Measurement, and Markowitz Data Mining Corrections Tests. Linking Momentum Strategies with SinglePeriod Portfolio Models. Reflections on Portfolio Insurance, Portfolio Theory, and Market Simulation with Harry Markowitz. Evaluating Hedge Fund Performance: A Stochastic Dominance Approach. Multiportfolio Optimization: A Natural Next Step. Alternative Model to Evaluate Selectivity and Timing Performance of Mutual Fund Managers: Theory and Evidence. Case Closed. StockSelection Modeling and Data Mining Corrections: LongOnly Versus 130/30 Models. Distortion Risk Measures in Portfolio Optimization. A Benefit from the Modern Portfolio Theory for Japanese Pension Investment. Private Valuation of Contingent Claims in a Discrete Time/State Model. Volatility Timing and Portfolio Construction Using Realized Volatility for the S&P500 Futures Index. The Application of Modern Portfolio Theory to Real Estate: A Brief Survey. Erratum.
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4. Tools for computational finance [2002]
 Seydel, R. (Rüdiger), 1947
 Berlin ; New York : Springer, ©2002.
 Description
 Book — 1 online resource (xii, 224 pages) Digital: text file.PDF.
 Summary

 1 Modeling Tools for Financial Options
 2 Generating Random Numbers with Specified Distributions
 3 Numerical Integration of Stochastic Differential Equations
 4 Finite Differences and Standard Options
 5 FiniteElement Methods
 6 Pricing of Exotic Options
 Appendices
 Al Financial Derivatives
 A2 Essentials of Stochastics
 A3 The BlackScholes Equation
 A4 Numerical Methods
 A6 Function Spaces
 A7 Complementary Formula
 References.
5. Portfolio theory and capital markets [1970]
 Sharpe, William F.
 New York : McGrawHill, ©1970.
 Description
 Book — xvi, 316 pages : illustrations ; 24 cm.
 Summary

Part I covers procedures for selecting investments: a set of rules for the intelligent selection of investments under conditions of risk. Part II deals with models of capital markets based on the assumption that investors act in accordance with the principles describ in Part I and Part III.
 Online
Business Library
Business Library  Status 

Archives: Ask at iDesk  
HG173 .S5  Inlibrary use 
 Chen, Ping, 1974
 Boston : Springer, ©2005.
 Description
 Book — 1 online resource (1 volume) Digital: text file.PDF.
 Summary

 Optimal Control Models in Finance. The STV Approach to Financial Optimal Control Models. A Financial Oscillator Model. An Optimal Corporate Financing Model. Further Computational Experiments and Results. Conclusion.
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 Bingham, N. H.
 2nd ed.  London ; New York : Springer, c2004.
 Description
 Book — xviii, 437 p. ; 25 cm.
 Summary

 ContentsPreface to the Second Edition Preface to the First Edition 1. Derivative Background 1.1 Financial Markets and Instruments 1.1.1 Derivative Instruments 1.1.2 Underlying Securities 1.1.3 Markets 1.1.4 Types of Traders 1.1.5 Modeling Assumptions 1.2 Arbitrage1.3 Arbitrage Relationships 1.3.1 Fundamental Determinants of Option Values 1.3.2 Arbitrage Bounds 1.4 Singleperiod Market Models 1.4.1 A Fundamental Example 1.4.2 A Singleperiod Model 1.4.3 A Few Financialeconomic Considerations Exercises 2. Probability Background 2.1 Measure 2.2 Integral 2.3 Probability 2.4 Equivalent Measures and RadonNikodym Derivatives 2.5 Conditional Expectation2.6 Modes of Convergence 2.7 Convolution and Characteristic Functions 2.8 The Central Limit Theorem 2.9 Asset Return Distributions 2.10 In.nite Divisibility and the L'evyKhintchine Formula 2.11 Elliptically Contoured Distributions2.12 Hyberbolic Distributions Exercises 3. Stochastic Processes in Discrete Time 3.1 Information and Filtrations 3.2 Discreteparameter Stochastic Processes 3.3 De.nition and Basic Properties of Martingales 3.4 Martingale Transforms 3.5 Stopping Times and Optional Stopping3.6 The Snell Envelope and Optimal Stopping 3.7 Spaces of Martingales 3.8 Markov Chains Exercises 4. Mathematical Finance in Discrete Time 4.1 The Model 4.2 Existence of Equivalent Martingale Measures4.2.1 The Noarbitrage Condition 4.2.2 RiskNeutral Pricing 4.3 Complete Markets: Uniqueness of EMMs 4.4 The Fundamental Theorem of Asset Pricing: RiskNeutral Valuation4.5 The CoxRossRubinstein Model 4.5.1 Model Structure4.5.2 Riskneutral Pricing 4.5.3 Hedging 4.6 Binomial Approximations4.6.1 Model Structure4.6.2 The BlackScholes Option Pricing Formula 4.6.3 Further Limiting Models 4.7 American Options 4.7.1 Theory4.7.2 American Options in the CRR Model 4.8 Further Contingent Claim Valuation in Discrete Time 4.8.1 Barrier Options 4.8.2 Lookback Options 4.8.3 A Threeperiod Example 4.9 Multifactor Models 4.9.1 Extended Binomial Model 4.9.2 Multinomial Models Exercises 5. Stochastic Processes in Continuous Time 5.1 Filtrations Finitedimensional Distributions 5.2 Classes of Processes 5.2.1 Martingales 5.2.2 Gaussian Processes 5.2.3 Markov Processes 5.2.4 Diffusions 5.3 Brownian Motion 5.3.1 Definition and Existence 5.3.2 Quadratic Variation of Brownian Motion 5.3.3 Properties of Brownian Motion5.3.4 Brownian Motion in Stochastic Modeling 5.4 Point Processes 5.4.1 Exponential Distribution 5.4.2 The Poisson Process 5.4.3 Compound Poisson Processes 5.4.4 Renewal Processes 5.5 Levy Processes 5.5.1 Distributions 5.5.2 Levy Processes 5.5.3 Levy Processes and the LevyKhintchine Formula5.6 Stochastic Integrals Ito Calculus 5.6.1 Stochastic Integration5.6.2 Ito's Lemma 5.6.3 Geometric Brownian Motion 5.7 Stochastic Calculus for BlackScholes Models5.8 Stochastic Differential Equations 5.9 Likelihood Estimation for Diffusions 5.10 Martingales, Local Martingales and Semimartingales 5.10.1 Definitions 5.10.2 Semimartingale Calculus5.10.3 Stochastic Exponentials 5.10.4 Semimartingale Characteristics 5.11 Weak Convergence of Stochastic Processes 5.11.1 The Spaces Cd and Dd 5.11.2 Definition and Motivation 5.11.3 Basic Theorems of Weak Convergence 5.11.4 Weak Convergence Results for Stochastic IntegralsExercises 6. Mathematical Finance in Continuous Time 6.1 Continuoustime Financial Market Models 6.1.1 The Financial Market Model 6.1.2 Equivalent Martingale Measures 6.1.3 Riskneutral Pricing 6.1.4 Changes of Numeraire 6.2 The Generalized BlackScholes Model 6.2.1 The Model 6.2.2 Pricing and Hedging Contingent Claims 6.2.3 The Greeks 6.2.4 Volatility 6.3 Further Contingent Claim Valuation 6.3.1 American Options 6.3.2 Asian Options 6.3.3 Barrier Options 6.3.4 Lookback Options 6.3.5 Binary Options 6.4 Discrete versus Continuoustime Market Models 6.4.1 Discrete to ContinuoustimeConvergence Reconsidered 6.4.2 Finite Market Approximations 6.4.3 Examples of Finite Market Approximations 6.4.4 Contiguity6.5 Further Applications of the RiskneutralValuation Principle 6.5.1 Futures Markets6.5.2 Currency Markets Exercises 7. Incomplete Markets 7.1 Pricing in Incomplete Markets 7.1.1 A General OptionPricing Formula 7.1.2 The Esscher Measure 7.2 Hedging in Incomplete Markets 7.2.1 Quadratic Principles 7.2.2 The Financial Market Model 7.2.3 Equivalent Martingale Measures 7.2.4 Hedging Contingent Claims 7.2.5 Meanvariance Hedging and the Minimal ELMM 7.2.6 Explicit Example 7.2.7 Quadratic Principles in Insurance 7.3 Stochastic Volatility Models 7.4 Models Driven by Levy Processes 7.4.1 Introduction 7.4.2 General Levyprocess Based Financial Market Model7.4.3 Existence of Equivalent Martingale Measures 7.4.4 Hyperbolic Models: The Hyperbolic Levy Process 8. Interest Rate Theory 8.1 The Bond Market 8.1.1 The Term Structure of Interest Rates 8.1.2 Mathematical Modelling8.1.3 Bond Pricing, .8.2 Shortrate Models 8.2.1 The Termstructure Equation 8.2.2 Martingale Modelling 8.2.3 Extensions: MultiFactor Models 8.3 HeathJarrowMorton Methodology 8.3.1 The HeathJarrowMorton Model Class 8.3.2 Forward Riskneutral Martingale Measures 8.3.3 Completeness 8.4 Pricing and Hedging Contingent Claims 8.4.1 Shortrate Models 8.4.2 Gaussian HJM Framework8.4.3 Swaps 8.4.4 Caps8.5 Market Models of LIBOR and Swaprates 8.5.1 Description of the Economy 8.5.2 LIBOR Dynamics Under the Forward LIBOR Measure8.5.3 The Spot LIBOR Measure 8.5.4 Valuation of Caplets and Floorlets in the LMM 8.5.5 The Swap Market Model 8.5.6 The Relation Between LIBOR and Swapmarket Models 8.6 Potential Models and the FlesakerHughston Framework8.6.1 Pricing Kernels and Potentials 8.6.2 The FlesakerHughston Framework Exercises 9. Credit Risk 9.1 Aspects of Credit Risk 9.1.1 The Market9.1.2 What Is Credit Risk? 9.1.3 Portfolio Risk Models 9.2 Basic Credit Risk Modeling 9.3 Structural Models 9.3.1 Merton's Model 9.3.2 A Jumpdi.usion Model 9.3.3 Structural Model with Premature Default 9.3.4 Structural Model with Stochastic Interest Rates 9.3.5 Optimal Capital Structure
 Leland's Approach 9.4 Reduced Form Models 9.4.1 Intensitybased Valuation of a Defaultable Claim 9.4.2 Ratingbased Models9.5 Credit Derivatives 9.6 Portfolio Credit Risk Models 9.7 Collateralized Debt Obligations (CDOs) 9.7.1 Introduction 9.7.2 Review of Modelling Methods A. Hilbert Space B. Projections and Conditional Expectations C. The Separating Hyperplane Theorem Bibliograpy Index.
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 Online
Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
HG4515.2 .B56 2004  Unknown 
8. A course in Financial calculus [2002]
 Etheridge, Alison.
 Cambridge, UK ; New York : Cambridge University Press, 2002.
 Description
 Book — 1 online resource (viii, 196 pages) : illustrations
 Summary

 Preface
 1. Single period models
 2. Binomial trees and discrete parameter martingales
 3. Brownian motion
 4. Stochastic calculus
 5. The BlackScholes model
 6. Different payoffs
 7. Bigger models
 Bibliography and further reading
 Notation
 Index.
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 Scherer, Bernd Michael.
 New York : Springer, 2005.
 Description
 Book — 1 online resource (xxi, 405 pages) : illustrations Digital: text file; PDF.
 Summary

 Linear and Quadratic Programming; General Optimization With Simple; Advanced Issues in MeanVariance Optimization; Resampling and Portfolio Choice; Scenario Optimization: Addressing Nonnormality; Robust Statistical Methods for Portfolio Construction; Bayes Methods.
 Rebonato, Riccardo. Author
 Princeton, New Jersey : Princeton University Press, 2012.
 Description
 Book — 1 online resource (XVII, 467 pages) : illustrations
 Summary

 Introduction xi Acknowledgements xvii I. The Structure of the LIBOR Market Model 1 1. Putting the Modern Pricing Approach in Perspective 3 1.1. Historical Developments 3 1.2. Some Important Remarks 21 2. The Mathematical and Financial Setup 25 2.1. The Modelling Framework 25 2.2. Definition and Valuation of the Underlying PlainVanilla Instruments 28 2.3. The Mathematical and Financial Description of the Securities Market 40 3. Describing the Dynamics of Forward Rates 57 3.1. A Working Framework for the Modern Pricing Approach 57 3.2. Equivalent Descriptions of the Dynamics of Forward Rates 65 3.3. Generalization of the Approach 79 3.4. The SwapRateBased LIBOR Market Model 83 4. Characterizing and Valuing Complex LIBOR Products 85 4.1. The Types of Product That Can be Handled Using the LIBOR Market Model 85 4.2. Case Study: Pricing in a ThreeForwardRate, TwoFactor World 96 4.3. Overview of the Results So Far 107 5. Determining the NoArbitrage Drifts of Forward Rates 111 5.1. General Derivation of the Drift Terms 112 5.2. Expressing the NoArbitrage Conditions in Terms of MarketRelated Quantities 118 5.3. Approximations of the Drift Terms 123 5.4. Conclusions 131 II. The Inputs to the General Framework 133 6. Instantaneous Volatilities 135 6.1. Introduction and Motivation 135 6.2. Instantaneous Volatility Functions: General Results 141 6.3. Functional Forms for the Instantaneous Volatility Function  Financial Implications 153 6.4. Analysis of Specific Functional Forms for the Instantaneous Volatility Functions 167 6.5. Appendix I  Why Specification (6.11c) Fails to Satisfy Joint Conditions 171 6.6. Appendix II  Indefinite Integral of the Instantaneous Covariance 171 7. Specifying the Instantaneous Correlation Function 173 7.1. General Considerations 173 7.2. Empirical Data and Financial Plausibility 180 7.3. Intrinsic Limitations of LowDimensionality Approaches 185 7.4. Proposed Functional Forms for the Instantaneous Correlation Function 189 7.5. Conditions for the Occurrence of Exponential Correlation Surfaces 196 7.6. A SemiParametric Specification of the Correlation Surface 204 III Calibration of the LIBOR Market Model 209 8. Fitting the Instantaneous Volatility Functions 211 8.1. General Calibration Philosophy and Plan of Part III 211 8.2. A First Approach to Fitting the Caplet Market: Imposing TimeHomogeneity 214 8.3. A Second Approach to Fitting the Caplet Market: Using Information from the Swaption Matrix 218 8.4. A Third Approach to Fitting the Caplet Market: Assigning a Future Term Structure of Volatilities 226 8.5. Results 231 8.6. Conclusions 248 9. Simultaneous Calibration to Market Caplet Prices and to an Exogenous Correlation Matrix 249 9.1. Introduction and Motivation 249 9.2. An Optimal Procedure to Recover an Exogenous Target Correlation Matrix 254 9.3. Results and Discussion 260 9.4. Conclusions 274 10 Calibrating a ForwardRateBased LIBOR Market Model to Swaption Prices 276 10.1. The General Context 276 10.2. The Need for a Joint Description of the Forwardand SwapRate Dynamics 280 10.3. Approximating the SwapRate Instantaneous Volatility 294 10.4. Computational Results on European Swaptions 306 10.5. Calibration to CoTerminal European Swaption Prices 312 10.6. An Application: Using an FRABased LIBOR Market Model for Bermudan Swaptions 318 10.7. Quality of the Numerical Approximation in Realistic Market Cases 326 IV. Beyond the Standard Approach: Accounting for Smiles 331 11. Extending the Standard Approach  I: CEV and Displaced Diffusion 333 11.1. Practical and Conceptual Implications of NonFlat Volatility Smiles 333 11.2. Calculating Deltas and Other Risk Derivatives in the Presence of Smiles 342 11.3. Accounting for Monotonically Decreasing Smiles 349 11.4. TimeHomogeneity in the Context of Displaced Diffusions 363 12. Extending the Standard Approach  II: Stochastic Instantaneous Volatilities 367 12.1. Introduction and Motivation 367 12.2. The Modelling Framework 372 12.3. Numerical Techniques 382 12.4. Numerical Results 397 12.5. Conclusions and Suggestions for Future Work 413 13. A Joint Empirical and Theoretical Analysis of the StochasticVolatility LIBOR Market Model 415 13.1. Motivation and Plan of the
 Chapter 415 13.2. The Empirical Analysis 420 13.3. The Computer Experiments 437 13.4. Conclusions and Suggestions for Future Work 442 Bibliography 445 Index 453.
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 Maringer, Dietmar.
 Dordrecht : Springer, ©2005.
 Description
 Book — 1 online resource (xiv, 222 pages) : illustrations Digital: text file.PDF.
 Summary

 Portfolio Management. Heuristic Optimization. Transaction Costs and Integer Constraints. Diversification in Small Portfolios. Cardinality Constraints for Markowitz Efficient Lines. The Hidden Risk of Value at Risk. Finding Relevant Risk Factors in Asset Pricing. Concluding Remarks.
 (source: Nielsen Book Data)
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12. Stochastic volatility : selected readings [2005]
 Oxford ; New York : Oxford University Press, 2005.
 Description
 Book — 1 online resource (viii, 525 pages) : illustrations Digital: data file.
 Summary

 General Introduction
 PART I: MODEL BUILDING
 1. A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices
 2. Financial Returns Modelled by the Product of Two Stochastic Processes: A Study of Daily Sugar Prices, 196179
 3. The Behavior of Random Variables with Nonstationary Variance and the Distribution of Security Prices
 4. The Pricing of Options on Assets with Stochastic Volatilities
 5. The Dynamics of Exchange Rate Volatility: A Multivariate Latent Factor ARCH Model
 6. Multivariate Stochastic Variance Models
 7. Stochastic Autoregressive Volatility: A Framework for Volatility Modeling
 8. Long Memory in Continuoustime Stochastic Volatility Models
 PART II: INFERENCE
 9. Bayesian Analysis of Stochastic Volatility Models
 10. Stochastic Volatility: Likelihood Inference and Comparison with ARCH models
 11. Estimation of Stochastic Volatility Models with Diagnostics
 PART III: OPTION PRICING
 12. Pricing Foreign Currency Options with Stochastic Volatility
 13. A ClosedForm Solution for Options with Stochastic Volatility, with Applications to Bond and Currency Options
 14. A Study Towards a Unified Approach to the Joint Estimation of Objective and Risk Neutral Measures for the Purpose of Options Valuation
 PART IV: REALISED VARIATION
 15. The Distribution of Exchange Rate Volatility
 16. Econometric Analysis of Realized Volatility and its use in Estimating Stochastic Volatility Models
 Index.
 (source: Nielsen Book Data)
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13. Stochastic volatility : selected readings [2005]
 Oxford ; New York : Oxford University Press, 2005.
 Description
 Book — 1 online resource (viii, 525 pages) : illustrations Digital: data file.
 Summary

 General Introduction
 PART I: MODEL BUILDING
 1. A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices
 2. Financial Returns Modelled by the Product of Two Stochastic Processes: A Study of Daily Sugar Prices, 196179
 3. The Behavior of Random Variables with Nonstationary Variance and the Distribution of Security Prices
 4. The Pricing of Options on Assets with Stochastic Volatilities
 5. The Dynamics of Exchange Rate Volatility: A Multivariate Latent Factor ARCH Model
 6. Multivariate Stochastic Variance Models
 7. Stochastic Autoregressive Volatility: A Framework for Volatility Modeling
 8. Long Memory in Continuoustime Stochastic Volatility Models
 PART II: INFERENCE
 9. Bayesian Analysis of Stochastic Volatility Models
 10. Stochastic Volatility: Likelihood Inference and Comparison with ARCH models
 11. Estimation of Stochastic Volatility Models with Diagnostics
 PART III: OPTION PRICING
 12. Pricing Foreign Currency Options with Stochastic Volatility
 13. A ClosedForm Solution for Options with Stochastic Volatility, with Applications to Bond and Currency Options
 14. A Study Towards a Unified Approach to the Joint Estimation of Objective and Risk Neutral Measures for the Purpose of Options Valuation
 PART IV: REALISED VARIATION
 15. The Distribution of Exchange Rate Volatility
 16. Econometric Analysis of Realized Volatility and its use in Estimating Stochastic Volatility Models
 Index.
 (source: Nielsen Book Data)
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14. Risk and asset allocation [2005]
 Meucci, Attilio.
 Berlin ; New York : Springer, 2005.
 Description
 Book — xxvi, 532 p. : 141 fig. ; 25 cm.
 Summary

 Preface. Onedimensional Random Variables. Multidimensional Random Variables. Modelling the Market. Estimating the Invariants Distribution. Evaluating Allocations. Optimizing Allocations. Estimation and Optimization together. Appendices: Linear Algebra. Functional Analysis. References. Index.
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Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
HG4529.5 .M48 2005  Unknown 
 Voit, Johannes, 1957
 Berlin ; New York : Springer, [2001]
 Description
 Book — 1 online resource (xii, 220 pages) : illustrations Digital: text file.PDF.
 Summary

 1. Introduction
 2. Basic Information on Capital Markets
 3. Random Walks in Finance and Physics
 4. The BlackScholes Theory of Option Prices
 5. Scaling in Financial Data and in Physics
 6. Turbulence and Foreign Exchange Markets
 7. Risk Control and Derivative Pricing in NonGaussian Markets
 8. Microscopic Market Models
 9. Theory of Stock Exchange Crashes.
 Bingham, N. H., author.
 Second edition.  London : Springer, [2004]
 Description
 Book — 1 online resource (xviii, 437 pages) Digital: text file.PDF.
 Summary

 Contents Preface to the Second Edition Preface to the First Edition 1. Derivative Background 1.1 Financial Markets and Instruments 1.1.1 Derivative Instruments 1.1.2 Underlying Securities 1.1.3 Markets 1.1.4 Types of Traders 1.1.5 Modeling Assumptions 1.2 Arbitrage 1.3 Arbitrage Relationships 1.3.1 Fundamental Determinants of Option Values 1.3.2 Arbitrage Bounds 1.4 Singleperiod Market Models 1.4.1 A Fundamental Example 1.4.2 A Singleperiod Model 1.4.3 A Few Financialeconomic Considerations Exercises 2. Probability Background 2.1 Measure 2.2 Integral 2.3 Probability 2.4 Equivalent Measures and RadonNikodym Derivatives 2.5 Conditional Expectation 2.6 Modes of Convergence 2.7 Convolution and Characteristic Functions 2.8 The Central Limit Theorem 2.9 Asset Return Distributions 2.10 In.nite Divisibility and the L'evyKhintchine Formula 2.11 Elliptically Contoured Distributions 2.12 Hyberbolic Distributions Exercises 3. Stochastic Processes in Discrete Time 3.1 Information and Filtrations 3.2 Discreteparameter Stochastic Processes 3.3 De.nition and Basic Properties of Martingales 3.4 Martingale Transforms 3.5 Stopping Times and Optional Stopping 3.6 The Snell Envelope and Optimal Stopping 3.7 Spaces of Martingales 3.8 Markov Chains Exercises 4. Mathematical Finance in Discrete Time 4.1 The Model 4.2 Existence of Equivalent Martingale Measures 4.2.1 The Noarbitrage Condition 4.2.2 RiskNeutral Pricing 4.3 Complete Markets: Uniqueness of EMMs 4.4 The Fundamental Theorem of Asset Pricing: RiskNeutral Valuation 4.5 The CoxRossRubinstein Model 4.5.1 Model Structure 4.5.2 Riskneutral Pricing 4.5.3 Hedging 4.6 Binomial Approximations 4.6.1 Model Structure 4.6.2 The BlackScholes Option Pricing Formula 4.6.3 Further Limiting Models 4.7 American Options 4.7.1 Theory 4.7.2 American Options in the CRR Model 4.8 Further Contingent Claim Valuation in Discrete Time 4.8.1 Barrier Options 4.8.2 Lookback Options 4.8.3 A Threeperiod Example 4.9 Multifactor Models 4.9.1 Extended Binomial Model 4.9.2 Multinomial Models Exercises 5. Stochastic Processes in Continuous Time 5.1 Filtrations
 Finitedimensional Distributions 5.2 Classes of Processes 5.2.1 Martingales 5.2.2 Gaussian Processes 5.2.3 Markov Processes 5.2.4 Diffusions 5.3 Brownian Motion 5.3.1 Definition and Existence 5.3.2 Quadratic Variation of Brownian Motion 5.3.3 Properties of Brownian Motion 5.3.4 Brownian Motion in Stochastic Modeling 5.4 Point Processes 5.4.1 Exponential Distribution 5.4.2 The Poisson Process 5.4.3 Compound Poisson Processes 5.4.4 Renewal Processes 5.5 Levy Processes 5.5.1 Distributions 5.5.2 Levy Processes 5.5.3 Levy Processes and the LevyKhintchine Formula 5.6 Stochastic Integrals
 Ito Calculus 5.6.1 Stochastic Integration 5.6.2 Ito's Lemma 5.6.3 Geometric Brownian Motion 5.7 Stochastic Calculus for BlackScholes Models 5.8 Stochastic Differential Equations 5.9 Likelihood Estimation for Diffusions 5.10 Martingales, Local Martingales and Semimartingales 5.10.1 Definitions 5.10.2 Semimartingale Calculus 5.10.3 Stochastic Exponentials 5.10.4 Semimartingale Characteristics 5.11 Weak Convergence of Stochastic Processes 5.11.1 The Spaces Cd and Dd 5.11.2 Definition and Motivation 5.11.3 Basic Theorems of Weak Convergence 5.11.4 Weak Convergence Results for Stochastic Integrals Exercises 6. Mathematical Finance in Continuous Time 6.1 Continuoustime Financial Market Models 6.1.1 The Financial Market Model 6.1.2 Equivalent Martingale Measures 6.1.3 Riskneutral Pricing 6.1.4 Changes of Numeraire.
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 Carmona, R. (René)
 Berlin ; New York : Springer, c2006.
 Description
 Book — xiv, 235 p. : ill. ; 24 cm.
 Summary

 The Term Structure of Interest Rates. Data and Instruments of the Term Structure of Interest Rates. Term Structure Factor Models. Infinite Dimensional Stochastic Analysis. Infinite Dimensional Integration Theory. Stochastic Analysis in Infinite Dimensions. The Malliavin Calculus. Generalized Models for the Term Structure of Interest Rates. General Models. Specific Models.
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SAL3 (offcampus storage)
SAL3 (offcampus storage)  Status 

Stacks  Request (opens in new tab) 
HG4651 .C32 2006  Available 
 Roman, Steven.
 New York : Springer, [2004]
 Description
 Book — 1 online resource (xiv, 354 pages) : illustrations Digital: text file.PDF.
 Summary

 Notation key and Greek alphabet
 1. Probability I : an introduction to discrete probability
 2. Portfolio management and the capital asset pricing model
 3. Background on options
 4. An aperitif on arbitrage
 5. Probability II : more discrete probability
 6. Discretetime pricing models
 7. The CoxRossRubinstein model
 8. Probability III : continuous probability
 9. The BlackScholes option pricing formula
 10. Optimal stopping and American options
 App. A. Pricing nonattainable alternatives in an incomplete market
 App. B. Convexity and the separation theorem.
(source: Nielsen Book Data)
 Voit, Johannes, 1957
 3rd ed.  Berlin ; New York : Springer, ©2005.
 Description
 Book — 1 online resource (xv, 378 pages) : illustrations Digital: text file.PDF.
 Summary

 Basic Information on Capital Markets
 Random Walks in Finance and Physics
 The BlackScholes Theory of Option Prices
 Scaling in Financial Data and in Physics
 Turbulence and Foreign Exchange Markets
 Derivative Pricing Beyond BlackScholes
 Microscopic Market Models
 Theory of Stock Exchange Crashes
 Risk Management
 Economic and Regulatory Capital for Financial Institutions.
 Roman, Steven.
 New York : Springer, ©2004.
 Description
 Book — xiv, 354 pages : illustrations ; 25 cm.
 Summary

 Notation key and Greek alphabet
 1. Probability I : an introduction to discrete probability
 2. Portfolio management and the capital asset pricing model
 3. Background on options
 4. An aperitif on arbitrage
 5. Probability II : more discrete probability
 6. Discretetime pricing models
 7. The CoxRossRubinstein model
 8. Probability III : continuous probability
 9. The BlackScholes option pricing formula
 10. Optimal stopping and American options
 App. A. Pricing nonattainable alternatives in an incomplete market
 App. B. Convexity and the separation theorem.
(source: Nielsen Book Data)
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Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

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HG4515.3 .R66 2004  Unknown 
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