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Calculating Default Probabilities With Stochastic Volatility
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Book Synopsis Calculating Default Probabilities with Stochastic Volatility by : Sebastian Pflumm
Download or read book Calculating Default Probabilities with Stochastic Volatility written by Sebastian Pflumm and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a structural credit risk model with stochastic volatility and derives a closed-form solution for calculating the corresponding default probabilities. Changes and influences from adding stochastic volatility in the structural setup are thoroughly analyzed along several dimensions in comparison to the popular Merton model. Furthermore, the proposed model is also implemented via the pure proxy approach in order to facilitate the conducted empirical test. Thereby, the effectiveness of the stochastic volatility model in explaining market implied default probabilities before and during the financial crisis is examined. It is shown that, although the traditional Merton model performs better during the crisis, default probabilities with stochastic volatility are the only factor with significant explanatory power in the years leading up to the financial crisis. The study further reaches the conclusion that with the enhanced flexibility and ability to capture stylized facts, calculating default probabilities under consideration of stochastic volatility has the potential to significantly improve upon the shortcomings of existing structural models. However, with default probabilities highly dependent on parametrization, developing an effective method for implementation is a crucial next step in order to ensure successful application of the proposed structural credit risk model.
Book Synopsis Quantitative Finance by : Maria C. Mariani
Download or read book Quantitative Finance written by Maria C. Mariani and published by John Wiley & Sons. This book was released on 2019-11-06 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a multitude of topics relevant to the quantitative finance community by combining the best of the theory with the usefulness of applications Written by accomplished teachers and researchers in the field, this book presents quantitative finance theory through applications to specific practical problems and comes with accompanying coding techniques in R and MATLAB, and some generic pseudo-algorithms to modern finance. It also offers over 300 examples and exercises that are appropriate for the beginning student as well as the practitioner in the field. The Quantitative Finance book is divided into four parts. Part One begins by providing readers with the theoretical backdrop needed from probability and stochastic processes. We also present some useful finance concepts used throughout the book. In part two of the book we present the classical Black-Scholes-Merton model in a uniquely accessible and understandable way. Implied volatility as well as local volatility surfaces are also discussed. Next, solutions to Partial Differential Equations (PDE), wavelets and Fourier transforms are presented. Several methodologies for pricing options namely, tree methods, finite difference method and Monte Carlo simulation methods are also discussed. We conclude this part with a discussion on stochastic differential equations (SDE’s). In the third part of this book, several new and advanced models from current literature such as general Lvy processes, nonlinear PDE's for stochastic volatility models in a transaction fee market, PDE's in a jump-diffusion with stochastic volatility models and factor and copulas models are discussed. In part four of the book, we conclude with a solid presentation of the typical topics in fixed income securities and derivatives. We discuss models for pricing bonds market, marketable securities, credit default swaps (CDS) and securitizations. Classroom-tested over a three-year period with the input of students and experienced practitioners Emphasizes the volatility of financial analyses and interpretations Weaves theory with application throughout the book Utilizes R and MATLAB software programs Presents pseudo-algorithms for readers who do not have access to any particular programming system Supplemented with extensive author-maintained web site that includes helpful teaching hints, data sets, software programs, and additional content Quantitative Finance is an ideal textbook for upper-undergraduate and beginning graduate students in statistics, financial engineering, quantitative finance, and mathematical finance programs. It will also appeal to practitioners in the same fields.
Book Synopsis Pricing Credit Derivatives with Uncertain Default Probabilities by : Vivien Brunel
Download or read book Pricing Credit Derivatives with Uncertain Default Probabilities written by Vivien Brunel and published by . This book was released on 2002 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: One main problem of credit models, as in stochastic volatility models for instance, is that the range of arbitrage prices of risky bonds and credit derivatives is very wide. In this article, we present a model for pricing options on the spread in an environment where the rating transition probabilities are uncertain parameters. The transition intensities are assumed to lie between two bounds which can be easily interpreted in the light of the rating agencies' transition matrices. These bounds are some kind of confidence interval of the future values of the rating transition intensities. We show that the extremal arbitrage prices are solutions of a Black-Scholes-Barenblatt equation. In particular, when using realistic values for the rating transition (default) probabilities, the arbitrage range of credit derivatives prices is narrow.
Book Synopsis Stochastic Filtering With Applications In Finance by : Ramaprasad Bhar
Download or read book Stochastic Filtering With Applications In Finance written by Ramaprasad Bhar and published by World Scientific. This book was released on 2010-08-19 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive account of stochastic filtering as a modeling tool in finance and economics. It aims to present this very important tool with a view to making it more popular among researchers in the disciplines of finance and economics. It is not intended to give a complete mathematical treatment of different stochastic filtering approaches, but rather to describe them in simple terms and illustrate their application with real historical data for problems normally encountered in these disciplines. Beyond laying out the steps to be implemented, the steps are demonstrated in the context of different market segments. Although no prior knowledge in this area is required, the reader is expected to have knowledge of probability theory as well as a general mathematical aptitude.Its simple presentation of complex algorithms required to solve modeling problems in increasingly sophisticated financial markets makes this book particularly valuable as a reference for graduate students and researchers interested in the field. Furthermore, it analyses the model estimation results in the context of the market and contrasts these with contemporary research publications. It is also suitable for use as a text for graduate level courses on stochastic modeling.
Book Synopsis Financial Engineering of the Stochastic Correlation in Credit Risk Models by : Hamidreza Arian
Download or read book Financial Engineering of the Stochastic Correlation in Credit Risk Models written by Hamidreza Arian and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pricing Credit Derivatives by : Keyvan H. Alekasir
Download or read book Pricing Credit Derivatives written by Keyvan H. Alekasir and published by . This book was released on 2007 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations by : Steven R. Dunbar
Download or read book Mathematical Modeling in Economics and Finance: Probability, Stochastic Processes, and Differential Equations written by Steven R. Dunbar and published by American Mathematical Soc.. This book was released on 2019-04-03 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Modeling in Economics and Finance is designed as a textbook for an upper-division course on modeling in the economic sciences. The emphasis throughout is on the modeling process including post-modeling analysis and criticism. It is a textbook on modeling that happens to focus on financial instruments for the management of economic risk. The book combines a study of mathematical modeling with exposure to the tools of probability theory, difference and differential equations, numerical simulation, data analysis, and mathematical analysis. Students taking a course from Mathematical Modeling in Economics and Finance will come to understand some basic stochastic processes and the solutions to stochastic differential equations. They will understand how to use those tools to model the management of financial risk. They will gain a deep appreciation for the modeling process and learn methods of testing and evaluation driven by data. The reader of this book will be successfully positioned for an entry-level position in the financial services industry or for beginning graduate study in finance, economics, or actuarial science. The exposition in Mathematical Modeling in Economics and Finance is crystal clear and very student-friendly. The many exercises are extremely well designed. Steven Dunbar is Professor Emeritus of Mathematics at the University of Nebraska and he has won both university-wide and MAA prizes for extraordinary teaching. Dunbar served as Director of the MAA's American Mathematics Competitions from 2004 until 2015. His ability to communicate mathematics is on full display in this approachable, innovative text.
Book Synopsis Parameter Estimation in Stochastic Volatility Models by : Jaya P. N. Bishwal
Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.
Book Synopsis Credit Risk Modeling by : David Lando
Download or read book Credit Risk Modeling written by David Lando and published by Princeton University Press. This book was released on 2009-12-13 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand, and on a direct modeling of the default probability of issuers on the other. He offers insights that can be drawn from each approach and demonstrates that the distinction between the two approaches is not at all clear-cut. The book strikes a fruitful balance between quickly presenting the basic ideas of the models and offering enough detail so readers can derive and implement the models themselves. The discussion of the models and their limitations and five technical appendixes help readers expand and generalize the models themselves or to understand existing generalizations. The book emphasizes models for pricing as well as statistical techniques for estimating their parameters. Applications include rating-based modeling, modeling of dependent defaults, swap- and corporate-yield curve dynamics, credit default swaps, and collateralized debt obligations.
Book Synopsis Stochastic Analysis with Financial Applications by : Arturo Kohatsu-Higa
Download or read book Stochastic Analysis with Financial Applications written by Arturo Kohatsu-Higa and published by Springer Science & Business Media. This book was released on 2011-07-22 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. The book also covers the areas of backward stochastic differential equations via the (non-linear) G-Brownian motion and the case of jump processes. Concerning the applications to finance, many of the articles deal with the valuation and hedging of credit risk in various forms, and include recent results on markets with transaction costs.
Book Synopsis Probability and Stochastic Processes by : Ionut Florescu
Download or read book Probability and Stochastic Processes written by Ionut Florescu and published by John Wiley & Sons. This book was released on 2014-12-04 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and accessible presentation of probability and stochastic processes with emphasis on key theoretical concepts and real-world applications With a sophisticated approach, Probability and Stochastic Processes successfully balances theory and applications in a pedagogical and accessible format. The book’s primary focus is on key theoretical notions in probability to provide a foundation for understanding concepts and examples related to stochastic processes. Organized into two main sections, the book begins by developing probability theory with topical coverage on probability measure; random variables; integration theory; product spaces, conditional distribution, and conditional expectations; and limit theorems. The second part explores stochastic processes and related concepts including the Poisson process, renewal processes, Markov chains, semi-Markov processes, martingales, and Brownian motion. Featuring a logical combination of traditional and complex theories as well as practices, Probability and Stochastic Processes also includes: Multiple examples from disciplines such as business, mathematical finance, and engineering Chapter-by-chapter exercises and examples to allow readers to test their comprehension of the presented material A rigorous treatment of all probability and stochastic processes concepts An appropriate textbook for probability and stochastic processes courses at the upper-undergraduate and graduate level in mathematics, business, and electrical engineering, Probability and Stochastic Processes is also an ideal reference for researchers and practitioners in the fields of mathematics, engineering, and finance.
Book Synopsis Monte Carlo and Quasi-Monte Carlo Methods 2010 by : Leszek Plaskota
Download or read book Monte Carlo and Quasi-Monte Carlo Methods 2010 written by Leszek Plaskota and published by Springer Science & Business Media. This book was released on 2012-08-23 with total page 721 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book represents the refereed proceedings of the Ninth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Warsaw (Poland) in August 2010. These biennial conferences are major events for Monte Carlo and the premiere event for quasi-Monte Carlo research. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. The reader will be provided with information on latest developments in these very active areas. The book is an excellent reference for theoreticians and practitioners interested in solving high-dimensional computational problems arising, in particular, in finance and statistics.
Book Synopsis Estimation of Default Probabilities Part 3 by : Uwe Wehrspohn
Download or read book Estimation of Default Probabilities Part 3 written by Uwe Wehrspohn and published by . This book was released on 2003 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: The article provides a detailed analysis of the approach to estimate firms' default probabilities as it is proposed in the Credit Risk+ portfolio model. It is shown that systematic estimation errors occur in the methodology that also carry over to credit portfolio risk management.
Book Synopsis Introduction to Stochastic Calculus Applied to Finance by : Damien Lamberton
Download or read book Introduction to Stochastic Calculus Applied to Finance written by Damien Lamberton and published by CRC Press. This book was released on 2011-12-14 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition of this book, the area of mathematical finance has grown rapidly, with financial analysts using more sophisticated mathematical concepts, such as stochastic integration, to describe the behavior of markets and to derive computing methods. Maintaining the lucid style of its popular predecessor, this concise and accessible introduction covers the probabilistic techniques required to understand the most widely used financial models. Along with additional exercises, this edition presents fully updated material on stochastic volatility models and option pricing as well as a new chapter on credit risk modeling. It contains many numerical experiments and real-world examples taken from the authors' own experiences. The book also provides all of the necessary stochastic calculus theory and implements some of the algorithms using SciLab. Key topics covered include martingales, arbitrage, option pricing, and the Black-Scholes model.
Book Synopsis Stochastic Modeling, Prediction and Pricing Ofdefault Risk by : Huaming Zhai
Download or read book Stochastic Modeling, Prediction and Pricing Ofdefault Risk written by Huaming Zhai and published by . This book was released on 1995 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Seminar on Stochastic Analysis, Random Fields and Applications IV by : Robert Dalang
Download or read book Seminar on Stochastic Analysis, Random Fields and Applications IV written by Robert Dalang and published by Birkhäuser. This book was released on 2012-12-06 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains twenty refereed papers presented at the 4th Seminar on Stochastic Processes, Random Fields and Applications, which took place in Ascona, Switzerland, from May 2002. The seminar focused mainly on stochastic partial differential equations, stochastic models in mathematical physics, and financial engineering. The book will be a valuable resource for researchers in stochastic analysis and professionals interested in stochastic methods in finance and insurance.
Book Synopsis Assessing Default Probabilities from Structural Credit Risk Models by : Wei Wang
Download or read book Assessing Default Probabilities from Structural Credit Risk Models written by Wei Wang and published by . This book was released on 2008 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we study the empirical performance of structural credit risk models by examining the default probabilities calculated from these models with different time horizons. The parameters of the models are estimated from firm's bond and equity prices. The models studied include Merton (1974), Merton model with stochastic interest rate, Longstaff and Schwartz (1995), Leland and Toft (1996) and Collin-Dufresne and Goldstein (2001). The sample firms chosen are those that have only one bond outstanding when bond prices are observed. We first find that when the Maximum Likelihood estimation, introduced in Duan (1994), is used to estimate the Merton model from bond prices, the estimated volatility is unreasonable high and the estimation process does not converge for most of the firms in our sample. This shows that the Merton (1974) is not able to generate high yields to match the empirical observations. On the other hand, when equity prices are used as input we find that the default probabilities predicted for investment-grade firms by Merton (1974) are all close to zero. When stochastic interest rates are assumed in Merton model, the model performance is improved. The models of Longstaff and Schwartz (1995) with constant interest rate as well as the Leland and Toft (1996) provide quite reasonable predictions on real default probabilities when compared with those reported by Moody's and Samp;P. However, Collin-Dufresnce and Goldstein (2001) predict unreasonably high default probabilities for longer time horizons.
