Time Inhomogeneous L Vy Processes In Interest Rate And Credit Risk Models
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Time Inhomogeneous L Vy Processes In Interest Rate And Credit Risk Models
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Author : Wolfgang Kluge
language : en
Publisher:
Release Date : 2005
Time Inhomogeneous L Vy Processes In Interest Rate And Credit Risk Models written by Wolfgang Kluge and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
L Vy Processes In Credit Risk And Market Models
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Author : Fehmi Özkan
language : en
Publisher:
Release Date : 2002
L Vy Processes In Credit Risk And Market Models written by Fehmi Özkan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
Numerical Lattice Methods For Implementing Interest Rate And Credit Risk Models
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Author : Meng-Lan Yueh
language : en
Publisher:
Release Date : 2002
Numerical Lattice Methods For Implementing Interest Rate And Credit Risk Models written by Meng-Lan Yueh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
Stochastic Processes In Credit Risk Modelling
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Author : Roberto Casarin
language : en
Publisher:
Release Date : 2005
Stochastic Processes In Credit Risk Modelling written by Roberto Casarin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Financial Modelling With Jump Processes
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Author : Peter Tankov
language : en
Publisher: CRC Press
Release Date : 2003-12-30
Financial Modelling With Jump Processes written by Peter Tankov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-30 with Business & Economics categories.
WINNER of a Riskbook.com Best of 2004 Book Award! During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematic
Counterparty Credit Risk Collateral And Funding
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Author : Damiano Brigo
language : en
Publisher: John Wiley & Sons
Release Date : 2013-03-05
Counterparty Credit Risk Collateral And Funding written by Damiano Brigo and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-05 with Business & Economics categories.
The book’s content is focused on rigorous and advanced quantitative methods for the pricing and hedging of counterparty credit and funding risk. The new general theory that is required for this methodology is developed from scratch, leading to a consistent and comprehensive framework for counterparty credit and funding risk, inclusive of collateral, netting rules, possible debit valuation adjustments, re-hypothecation and closeout rules. The book however also looks at quite practical problems, linking particular models to particular ‘concrete’ financial situations across asset classes, including interest rates, FX, commodities, equity, credit itself, and the emerging asset class of longevity. The authors also aim to help quantitative analysts, traders, and anyone else needing to frame and price counterparty credit and funding risk, to develop a ‘feel’ for applying sophisticated mathematics and stochastic calculus to solve practical problems. The main models are illustrated from theoretical formulation to final implementation with calibration to market data, always keeping in mind the concrete questions being dealt with. The authors stress that each model is suited to different situations and products, pointing out that there does not exist a single model which is uniformly better than all the others, although the problems originated by counterparty credit and funding risk point in the direction of global valuation. Finally, proposals for restructuring counterparty credit risk, ranging from contingent credit default swaps to margin lending, are considered.
Optimization Based Models For Measuring And Hedging Risk In Fixed Income Markets
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Author : Johan Hagenbjörk
language : sv
Publisher: Linköping University Electronic Press
Release Date : 2019-12-09
Optimization Based Models For Measuring And Hedging Risk In Fixed Income Markets written by Johan Hagenbjörk and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-09 with categories.
The global fixed income market is an enormous financial market whose value by far exceeds that of the public stock markets. The interbank market consists of interest rate derivatives, whose primary purpose is to manage interest rate risk. The credit market primarily consists of the bond market, which links investors to companies, institutions, and governments with borrowing needs. This dissertation takes an optimization perspective upon modeling both these areas of the fixed-income market. Legislators on the national markets require financial actors to value their financial assets in accordance with market prices. Thus, prices of many assets, which are not publicly traded, must be determined mathematically. The financial quantities needed for pricing are not directly observable but must be measured through solving inverse optimization problems. These measurements are based on the available market prices, which are observed with various degrees of measurement noise. For the interbank market, the relevant financial quantities consist of term structures of interest rates, which are curves displaying the market rates for different maturities. For the bond market, credit risk is an additional factor that can be modeled through default intensity curves and term structures of recovery rates in case of default. By formulating suitable optimization models, the different underlying financial quantities can be measured in accordance with observable market prices, while conditions for economic realism are imposed. Measuring and managing risk is closely connected to the measurement of the underlying financial quantities. Through a data-driven method, we can show that six systematic risk factors can be used to explain almost all variance in the interest rate curves. By modeling the dynamics of these six risk factors, possible outcomes can be simulated in the form of term structure scenarios. For short-term simulation horizons, this results in a representation of the portfolio value distribution that is consistent with the realized outcomes from historically observed term structures. This enables more accurate measurements of interest rate risk, where our proposed method exhibits both lower risk and lower pricing errors compared to traditional models. We propose a method for decomposing changes in portfolio values for an arbitrary portfolio into the risk factors that affect the value of each instrument. By demonstrating the method for the six systematic risk factors identified for the interbank market, we show that almost all changes in portfolio value and portfolio variance can be attributed to these risk factors. Additional risk factors and approximation errors are gathered into two terms, which can be studied to ensure the quality of the performance attribution, and possibly improve it. To eliminate undesired risk within trading books, banks use hedging. Traditional methods do not take transaction costs into account. We, therefore, propose a method for managing the risks in the interbank market through a stochastic optimization model that considers transaction costs. This method is based on a scenario approximation of the optimization problem where the six systematic risk factors are simulated, and the portfolio variance is weighted against the transaction costs. This results in a method that is preferred over the traditional methods for all risk-averse investors. For the credit market, we use data from the bond market in combination with the interbank market to make accurate measurements of the financial quantities. We address the notoriously difficult problem of separating default risk from recovery risk. In addition to the previous identified six systematic risk factors for risk-free interests, we identify four risk factors that explain almost all variance in default intensities, while a single risk factor seems sufficient to model the recovery risk. Overall, this is a higher number of risk factors than is usually found in the literature. Through a simple model, we can measure the variance in bond prices in terms of these systematic risk factors, and through performance attribution, we relate these values to the empirically realized variances from the quoted bond prices. De globala ränte- och kreditmarknaderna är enorma finansiella marknader vars sammanlagda värden vida överstiger de publika aktiemarknadernas. Räntemarknaden består av räntederivat vars främsta användningsområde är hantering av ränterisker. Kreditmarknaden utgörs i första hand av obligationsmarknaden som syftar till att förmedla pengar från investerare till företag, institutioner och stater med upplåningsbehov. Denna avhandling fokuserar på att utifrån ett optimeringsperspektiv modellera både ränte- och obligationsmarknaden. Lagstiftarna på de nationella marknaderna kräver att de finansiella aktörerna värderar sina finansiella tillgångar i enlighet med marknadspriser. Därmed måste priserna på många instrument, som inte handlas publikt, beräknas matematiskt. De finansiella storheter som krävs för denna prissättning är inte direkt observerbara, utan måste mätas genom att lösa inversa optimeringsproblem. Dessa mätningar görs utifrån tillgängliga marknadspriser, som observeras med varierande grad av mätbrus. För räntemarknaden utgörs de relevanta finansiella storheterna av räntekurvor som åskådliggör marknadsräntorna för olika löptider. För obligationsmarknaden utgör kreditrisken en ytterligare faktor som modelleras via fallissemangsintensitetskurvor och kurvor kopplade till förväntat återvunnet kapital vid eventuellt fallissemang. Genom att formulera lämpliga optimeringsmodeller kan de olika underliggande finansiella storheterna mätas i enlighet med observerbara marknadspriser samtidigt som ekonomisk realism eftersträvas. Mätning och hantering av risker är nära kopplat till mätningen av de underliggande finansiella storheterna. Genom en datadriven metod kan vi visa att sex systematiska riskfaktorer kan användas för att förklara nästan all varians i räntekurvorna. Genom att modellera dynamiken i dessa sex riskfaktorer kan tänkbara utfall för räntekurvor simuleras. För kortsiktiga simuleringshorisonter resulterar detta i en representation av fördelningen av portföljvärden som väl överensstämmer med de realiserade utfallen från historiskt observerade räntekurvor. Detta möjliggör noggrannare mätningar av ränterisk där vår föreslagna metod uppvisar såväl lägre risk som mindre prissättningsfel jämfört med traditionella modeller. Vi föreslår en metod för att dekomponera portföljutvecklingen för en godtycklig portfölj till de riskfaktorer som påverkar värdet för respektive instrument. Genom att demonstrera metoden för de sex systematiska riskfaktorerna som identifierats för räntemarknaden visar vi att nästan all portföljutveckling och portföljvarians kan härledas till dessa riskfaktorer. Övriga riskfaktorer och approximationsfel samlas i två termer, vilka kan användas för att säkerställa och eventuellt förbättra kvaliteten i prestationshärledningen. För att eliminera oönskad risk i sina tradingböcker använder banker sig av hedging. Traditionella metoder tar ingen hänsyn till transaktionskostnader. Vi föreslår därför en metod för att hantera riskerna på räntemarknaden genom en stokastisk optimeringsmodell som också tar hänsyn till transaktionskostnader. Denna metod bygger på en scenarioapproximation av optimeringsproblemet där de sex systematiska riskfaktorerna simuleras och portföljvariansen vägs mot transaktionskostnaderna. Detta resulterar i en metod som, för alla riskaverta investerare, är att föredra framför de traditionella metoderna. På kreditmarknaden använder vi data från obligationsmarknaden i kombination räntemarknaden för att göra noggranna mätningar av de finansiella storheterna. Vi angriper det erkänt svåra problemet att separera fallissemangsrisk från återvinningsrisk. Förutom de tidigare sex systematiska riskfaktorerna för riskfri ränta, identifierar vi fyra riskfaktorer som förklarar nästan all varians i fallissemangsintensiteter, medan en enda riskfaktor tycks räcka för att modellera återvinningsrisken. Sammanlagt är detta ett större antal riskfaktorer än vad som brukar användas i litteraturen. Via en enkel modell kan vi mäta variansen i obligationspriser i termer av dessa systematiska riskfaktorer och genom prestationshärledningen relatera dessa värden till de empiriskt realiserade varianserna från kvoterade obligationspriser.
Financial Asset Pricing Theory
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Author : Claus Munk
language : en
Publisher: Oxford University Press, USA
Release Date : 2013-04-18
Financial Asset Pricing Theory written by Claus Munk and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-18 with Business & Economics categories.
The book presents models for the pricing of financial assets such as stocks, bonds, and options. The models are formulated and analyzed using concepts and techniques from mathematics and probability theory. It presents important classic models and some recent 'state-of-the-art' models that outperform the classics.
Credit Risk Modeling Valuation And Hedging
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Author : Tomasz R. Bielecki
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Credit Risk Modeling Valuation And Hedging written by Tomasz R. Bielecki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Business & Economics categories.
The motivation for the mathematical modeling studied in this text on developments in credit risk research is the bridging of the gap between mathematical theory of credit risk and the financial practice. Mathematical developments are covered thoroughly and give the structural and reduced-form approaches to credit risk modeling. Included is a detailed study of various arbitrage-free models of default term structures with several rating grades.
Measuring And Managing Liquidity Risk
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Author : Antonio Castagna
language : en
Publisher: John Wiley & Sons
Release Date : 2013-09-03
Measuring And Managing Liquidity Risk written by Antonio Castagna and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-03 with Business & Economics categories.
A fully up-to-date, cutting-edge guide to the measurement and management of liquidity risk Written for front and middle office risk management and quantitative practitioners, this book provides the ground-level knowledge, tools, and techniques for effective liquidity risk management. Highly practical, though thoroughly grounded in theory, the book begins with the basics of liquidity risks and, using examples pulled from the recent financial crisis, how they manifest themselves in financial institutions. The book then goes on to look at tools which can be used to measure liquidity risk, discussing risk monitoring and the different models used, notably financial variables models, credit variables models, and behavioural variables models, and then at managing these risks. As well as looking at the tools necessary for effective measurement and management, the book also looks at and discusses current regulation and the implication of new Basel regulations on management procedures and tools.