The MathFinance Newsletter, Edition 190, October 14 2008.

Previous editions and this edition in html format can be found on http://www.mathfinance.com/Newsletter/.

In this issue:

1. MathFinance Job Exchange
   1. Numerical software development for finance at NAG Ltd / Smith Institute
   2. Credit Suisse invites to a Credit Derivatives Workshop on November 27 2008 in Frankfurt
   3. Financial World Recruitment - a candidate driven recruitment company which vets, interviews and prepares all delegates for the capital market sector
   4. Risikomanagement Financial Risk Solutions, Deloitte, Düsseldorf
   5. Mathematiker (m/w), Naturwissenschaftler (m/w), oder (Wirtschafts-) Informatiker (m/w) bei d-fine GmbH, Deutschland
2. MathFinance Events
   1. Credit Derivatives Modelling by Fitch Solutions, London, 16-17 Oct 2008
      
   2. Monte Carlo Methods in Finance by Dr. Jörg Kienitz, London, 20 - 21 October 2008
      
   3. FX Exotic Options Seminar with Prof. Uwe Wystup, London, 27 - 29 October 2008
      
   4. Latest Developments: Credit Derivatives Pricing, Hedging, Modelling & Trading Techniques: London: 17 - 19 November 2008
      
   5. Latest Developments: Interest Rate Modelling & Interest Rate Exotic & FX Hybrid Products: London: 24 - 25 November 2008
      
   6. Pricing Exotic Interest Rate Derivatives, The LIBOR Market Model in QuantLib, MoneyScience Masterclass with Mark Joshi, London, 25 - 27 February 2009
      
   7. Financial E'trics Conferences, Berlin, March 19-21 2009
      
   8. Frankfurt MathFinance Conference 23-24 March 2009
      
3. MathFinance Resources
1. Steven E. Shreve on Forbes.com: Don't Blame the Quants.
2. Master of Quantitative Finance at Frankfurt School
3. Master's in Financial Engineering Program at UC Berkeley's Haas School of Business

• find quantitative staff
• recommend your book or educational institute
• invite to a workshop
• introduce your research to a wider audience

The MathFinance Newsletter - produced by MathFinance AG

1. MathFinance Job Exchange
   
   

   1. NAG Ltd / Smith Institute - KNOWLEDGE TRANSFER PARTNERSHIP
      
      Numerical software development for finance

      Background

      The Numerical Algorithms Group Ltd (NAG) is a leading provider of numerical software components to a diverse range of industries worldwide. Since its foundation in 1970, and its development of the first numerical software library, it has been at the forefront of research and innovation in the area of mathematical computing. An important market for the company's software is the finance sector and the project outlined here will translate new thinking in numerical algorithms for financial simulation into a viable product for banks and other clients. The Smith Institute connects industry and the science base to create commercial benefit from mathematical modelling. It manages the UK's Knowledge Transfer Network for Industrial Mathematics, which is currently developing new initiatives in the finance industry.

      The Project

      A talented graduate is sought to fill a central role in the development of new software products for the finance industry. The post offers a unique opportunity to apply cutting edge research in numerical algorithms to the requirements of financial markets. It will incorporate active involvement with academic researchers as well as with clients in financial institutions. The objectives are to:

      • take recent research in the area of financial simulation as the basis for an innovative new product;
      • build contacts with financial institutions to further improve product function and design;
      • create an implementation of the chosen algorithms on specific hardware platforms;
      • take the production process through testing and quality assurance to promotion and marketing;
      • evaluate future market potential based on the experience gained.

      The project will last for 2 years. It will be based at NAG in Oxford, and be carried out under joint supervision with the Smith Institute and Prof Mike Giles.

      The Requirement

      The successful candidate will possess a first degree with a strong mathematical content together with higher degree in financial mathematics, preferably in the area of stochastic processes as applied to financial derivatives or risk management. In addition, some familiarity with computer programming languages is needed. It is also important that the candidate has a keen interest in the role that software plays in present day financial markets.

      A flexible approach to working practices and hours is essential, since the role will include visits to clients and interaction with existing company production teams. Strong communication skills are also necessary since an important part of the role is to publicise results through verbal presentations and written reports.

      The salary will be competitive to reflect the successful candidate's qualifications and experience and will be in the range £29,300 - £34,294.

      Candidates should apply in writing to: Gillian Hoyle, Smith Institute, Surrey Technology Centre, Guildford GU2 7GG, or by email to , enclosing a full CV with the names and addresses of two referees, and quoting reference SI/NAG. Further information about NAG may be found at www.nag.co.uk, about the Smith Institute at www.smithinst.co.uk, and about the Knowledge Transfer Network for Industrial Mathematics at www.industrialmaths.net.

      The closing date for applications is Friday 24 October 2008.

      
      
      

   2. Invitation
      Credit Derivatives Workshop
      Thursday, 27 November 2008
      11:00 – 18:30
      Credit Suisse Offices, Frankfurt

      Looking to leverage your mathematical or algorithmic skills? Enjoy developing effective solutions to challenging problems? Want your work to make an impact in the real world?

      Discover how Credit Suisse models the next generation of financial instruments and apply your technical and interpersonal skills in a credit derivatives workshop.

      Gain an insight into the real world of credit derivatives, and how we as an investment bank trade these products around the globe. Take the opportunity to learn more about our Global Modelling and Analytics Group (GMAG), meet with representatives from Structuring, Research or Trading, and discuss opportunities for quantitative Masters and PhD students at Credit Suisse, London in an informal atmosphere.

      Find out how to apply for quantitative positions in investment banking and meet with representatives from our Graduate Recruitment team. Please note no prior finance knowledge is required.

      We will confirm your participation on Friday, 21 November and provide you with further information.

      To register, email your CV and a cover note by 17:00 on Sunday, 16 November to:

      Flyer in pdf

      Thinking New Perspectives.

      
      
      

   3. Financial World Recruitment

      Financial World Recruitment is a candidate driven recruitment company which vets, interviews and prepares all delegates for the capital market sector. As part of our service you can post either your company jobs or candidate CVs on our website for free. FWR specialises in Quantitative Research, Risk Management, Financial Engineering, Model Validation, Structured Products, Trading & Commodity Derivatives positions. Please see below for a selection of CVs & Jobs or click on our website to view all information.

      Contact Details: Chris King
      Telephone: +44 (0) 1273 201 199
      Email:
      Website: http://www.fwrecruitment.com

      Candidates:

      http://www.fwrecruitment.com/candidates.php
      
      

   4. Risikomanagement Financial Risk Solutions, Deloitte, Düsseldorf

      • Business Analysts, Consultants, Senior Consultants (m/w) - Risikomanagement Financial Risk Solutions
        Job-Nr. H6-CO-BA-DU-157
        Standort: Düsseldorf
        
        

        Es erwartet Sie ein teamorientiertes Arbeitsumfeld mit sehr guten Aufstiegschancen. Das interessante und abwechslungsreiche Aufgabenspektrum bietet Ihnen die Möglichkeit, am Ausbau unserer Service Line Financial Risk Solutions aktiv mitzuwirken. Die Einbindung in das weltweite Netzwerk von Deloitte ermöglicht internationalen Know-how-Transfer und die Mitarbeit an grenzüberschreitenden Projekten.

        
        Ihre Aufgaben
        
        

        Im Spannungsfeld von Mathematik und regulatorischen Anforderungen erarbeiten Sie für unsere Mandanten betriebswirtschaftliche Lösungen unter Einsatz von finanzmathematischen Modellen. Sie verstärken unser Quant-Team, das für quantitative, betriebswirtschaftliche und aufsichtsrechtliche Fragestellungen kompetenter Ansprechpartner für unsere Mandanten ist, zu denen bedeutende Banken, Versicherungen, Finanzdienstleister sowie Energieund Industrieunternehmen geören. Ein Schwerpunkt Ihrer Tätigkeit wird auf Methoden und Verfahren der Steuerung von Kredit-, Marktpreis- und operationellen Risiken liegen.

        
        Ihr Profil
        
        

        Sie haben Ihr Hochschulstudium mit Bezug zu Wirtschaftswissenschaften und quantitativer Ausrichtung überdurchschnittlich erfolgreich abgeschlossen oder erwarten, dies in naher Zukunft zu tun. Bei der Lösung praktischer Problemstellungen fühlen Sie sich sicher im Umgang mit statistischen Verfahren, finanzmathematischen Fragestellungen sowie dem Einsatz und der Bewertung von Derivaten. Vertiefte Kenntnisse der Ökonometrie bzw. schließenden Statistik, der stochastischen Methoden zur Bewertung von Derivaten oder der Versicherungsmathematik bringen Sie idealerweise mit.

        Neben Fragen der mathematischen Modellbildung sind für Sie Projekte mit vorrangig qualitativem Fokus ebenso reizvoll. Dazu zählen beispielsweise Projekte in den Bereichen Treasury, Risikocontrolling, Portfoliomanagement oder zur Internationalen Rechnungslegung von Finanzinstrumenten sowie zur Regulierung von Finanzdienstleistern nach Basel II und den Mindestanforderungen an das Risikomanagement. Idealerweise haben Sie bereits während Ihres Studiums oder in den ersten Berufsjahren praktische Erfahrungen in o. g. Themengebieten sammeln können. Einschlägige Berufserfahrung als "Quant", beispielsweise in der Bewertung von strukturierten Finanzinstrumenten, der Erstellung von Ratingsystemen oder der Modellierung des ALM bei Lebensversicherern, ist für uns besonders wertvoll. Dank Ihrer analytischen Fähigkeiten stellen Sie sich gerne komplexen Herausforderungen, erarbeiten sich neue Themen weitgehend selbständig und präsentieren Ihre Arbeitsergebnisse ohne Schwierigkeiten auch in Englisch. Sie suchen den Kontakt mit Kunden und bauen dabei auf Ihr gesundes Selbstvertrauen.

      • Praktikanten (m/w) - Risikomanagement Financial Risk Solutions, Deloitte
        Job-Nr. H7-CO-PR-DU-010
        Standort: Düsseldorf
        
        

        Es erwartet Sie ein teamorientiertes Arbeitsumfeld mit sehr guten Aufstiegschancen. Das interessante und abwechslungsreiche Aufgabenspektrum bietet Ihnen die Möglichkeit, am Ausbau unserer Service Line Financial Risk Solutions aktiv mitzuwirken. Die Einbindung in das weltweite Netzwerk von Deloitte ermöglicht internationalen Know-how-Transfer und die Mitarbeit an grenzüberschreitenden Projekten.

        Ihre Aufgaben
        
        Sie unterstützen unsere Service Line Financial Risk Solutions bei der Implementierung von Bewertungsmodellen für unterschiedliche Finanzprodukte. Des Weiteren sind Sie in aktuelle Projekte mit quantitativem Schwerpunkt eingebunden. Zu Ihren Aufgaben zählen insbesondere:
        
        
        • Entwicklung und Implementierung von Bewertungsalgorithmen
        • Kalibrierung von Bewertungsmodellen
        • Marktdatenrecherche in Bloomberg
        • Literaturrecherche zu Spezialfragen aus der Finanzmathematik
        • Unterstützung des Quant-Teams im Rahmen der täglichen Projektarbeit
        
        Ihr Profil
        
        

        Sie befinden sich im Hauptstudium eines naturwissenschaftlichen Studienganges mit finanzwirtschaftlichen Schwerpunkten und verfügen über sehr gute Programmier-Kenntnisse in Java und/oder C++. Eine systematische und lösungsorientierte Arbeitsweise sowie kommunikative Kompetenz zeichnen Sie aus. Gute Englischkenntnisse runden Ihr Profil ab.

        Neben Fragen der mathematischen Modellbildung sind für Sie auch Aufgabenstellungen mit vorrangig theoretischem Fokus reizvoll. Idealerweise haben Sie bereits während Ihres Studiums im Rahmen von Praktika (etwa im Front Office einer Bank) Erfahrungen in o. g. Themengebieten sammeln können. Grundkenntnisse im Bereich Finanzmathematik und Derivate setzen wir voraus. Einschlägige Kenntnisse in der Bewertung von strukturierten Finanzinstrumenten und komplexen Produkten sind für uns besonders wertvoll.

        Dank Ihrer analytischen Fähigkeiten stellen Sie sich gerne komplexen Herausforderungen, erarbeiten sich neue Themen weitgehend selbständig und präsentieren Ihre Arbeitsergebnisse ohne Schwierigkeiten auch in Englisch. Zudem sind Sie mindestens 8 Wochen verfügbar.

      Sie sind interessiert?
      
      Dann bewerben Sie sich bitte online unter http://www.deloitte.com/careers oder schicken Sie Ihre aussagekräftigen Unterlagen bitte an Deloitte, Jessica Voß, Schwannstraße 6, 40476 Düsseldorf. Wir freuen uns auf Ihre Bewerbung.
      
      

   5. Mathematiker (m/w), Naturwissenschaftler (m/w), oder (Wirtschafts-) Informatiker (m/w)
      d-fine GmbH, Deutschland

      Sie haben in der Wissenschaft viel bewegt? Dann können Sie auch in der Wirtschaft viel bewegen! Davon sind wir bei d-fine fest überzeugt.

      d-fine ist mit weit über 200 Beratern und Büros in Frankfurt, München, London, Hong Kong und Bratislava eines der größten auf die Finanzwelt spezialisierten Beratungsunternehmen in Europa. Wir fokussieren höchste naturwissenschaftlich-technische Kompetenz auf die anspruchsvollen Herausforderungen unserer Kunden. Wir beraten Banken, Versicherungen, Asset-Manager und Industrieunternehmen zu allen Themen im Bereich Handel und Risikomanagement - von der Strategie-Entwicklung über die fachliche Konzeption der zugehörigen Methoden und Prozesse bis zur professionellen Implementierung, vom finanzmathematischen Modell bis zur real-time Schnittstelle, vom einfachen Kredit bis zum exotischen Derivat, vom Ratingsystem bis zur Portfoliosteuerung, von IAS 39 bis Basel II.

      Unsere Kunden schätzen unseren kompromisslos hohen Qualitätsanspruch und vor allem, dass wir diesen Anspruch auch realisieren. Das beginnt schon bei der Auswahl unserer Mitarbeiter (m/w). Wir suchen Sie als Naturwissenschaftler, Mathematiker oder Wirtschaftsinformatiker. Sie besitzen einen exzellenten Hochschulabschluss, sprechen fließend Englisch und Deutsch und haben weit überdurchschnittliche mathematische Fähigkeiten. Sie haben darüber hinaus sehr gute IT-Kenntnisse und sind idealerweise bereits mit Statistik, Numerik und Finanzmathematik vertraut.

      Unbedingt erwarten wir von Ihnen analytisches Denken, ergebnisorientiertes Vorgehen und exzellente Kommunikationsfähigkeiten. Sie sind teamfähig, erfassen auch sehr komplexe Aufgaben schnell und können sich rasch in neue Umgebungen einarbeiten. Sie haben Beratungstalent, hohe Einsatzfreude und sind flexibel und belastbar.

      Selbstverständlich erhalten Sie eine intensive Einführung in Ihr zukünftiges Aufgabenfeld. Wir sind berühmt für unser anspruchsvolles Training auf höchstem Niveau, das wir in Zusammenarbeit mit führenden internationalen Universitäten wie z.B. der University of Oxford, der Frankfurt School of Finance & Management, dem Imperial College, der Warwick Business School und der Université de Lausanne durchführen. Dabei können Sie sogar einen Master of Science (MSc) in Finanzmathematik, einen MBA in Management & Finance oder einen Abschluss als Chartered Financial Analyst (CFA) erwerben.

      Wenn Sie in einem Team hoch begabter und hoch motivierter Kollegen mitarbeiten wollen, große individuelle Freiräume, viel Eigenverantwortung sowie hervorragende Entwicklungsperspektiven suchen, freuen wir uns auf Ihre Bewerbung.

      Und durch unser flexibles Wohnortkonzept können Sie sogar Ihren jetzigen Wohnort beibehalten.

      Willkommen bei d-fine!

      d-fine GmbH
      z. Hd. Frau Sabrina Adam
      Opernplatz 2
      60313 Frankfurt am Main
      Telefon +49-69-90737-555
      
      homepage: http://www.d-fine.de

      
      
      
   
   
   
2. MathFinance Events
   
   

   1. Credit Derivatives Modelling by Fitch Solutions

      This two-day course introduces the concept of credit risk and provides an overview of all the standard market techniques to model credit risk and to price credit derivatives.

      Date: 16-17 October, 2008
      Price: £1,950 + VAT
      Location: London, England
      Visit the website for more information
      Register Now!

      COURSE OBJECTIVES

      This course gives a fairly comprehensive overview of the most widely used credit risk modelling tools and techniques and introduces the credit derivatives literature to the audience. The course provides tools for an efficient implementation of credit derivative pricing models.

      TARGET AUDIENCE

      This course is tailored for quantitative analysts, credit risk traders, credit derivatives researchers, financial analysts, and risk managers at banks, insurance companies and asset managers, who would like to gain a better understanding of the applied tools and techniques that are employed in modelling credit risk and pricing credit derivatives. This is an intermediate to advanced level course with no prerequisites courses (However, the Quant Methods for Fixed Income & Volatility by Fitch Solutions course can be thought to be a companion course). Participants should have working knowledge of algebra and some exposure to stochastic calculus to follow the mathematical discussions.

      For more information visit the course page on our website or call Sarah Butt on +44 20 7201 2770 or E:/

      CONTENT

      CREDIT RISK

      Fundamental instruments: Bond and CDS

      • Risk decomposition in Bond
      • CDS
      • Comparing Bond to CDS.

      RATING

      Rating Transition Matrix

      • Definitions and symbols
      • Generalized Linear Models - Logit
      • Analysing Regression Statistics
      • Transition Matrix and Credit Curves
      • Stochastic Matrices
      • Markov Chain Models
      • Chapman-Kolmogorov Equation
      • Time independent Generators
      • Credit Curves computation

      STRUCTURAL MODELS

      Credit Risk models

      • Structural Credit models
      • Merton Model
      • First passage models
      • Bernoulli mixture models
      • Homogeneous models

      REDUCED FORM MODELS

      Reduced Form Credit Models

      • Default intensity
      • Stopping Time and Hazard Rate
      • Poisson Process
      • Cox Process
      • Affine Intensity

      DEFAULT DEPENDENCE

      Correlation Models

      • Copula Functions
      • Tail Dependence
      • Gaussian Copula
      • Student T copula
      • Copulae Calibration

      CDS IN DETAIL

      Credit Default Swap

      • Credit Events, Monetization of a CDS, Counterparty considerations

      Settlement following a credit Event

      • MtM CDS
      • Pricing a CDS
      • Risky Duration (DV01) and Risky annuity
      • Forward CDS

      SYNTHETIC CDO

      Tranche of protection pricing equations

      • Monte Carlo simulation
      • Valuation by semi-analytic methods
      • One factor - multi factor models
      • Valuation by FFT

      Loss Computation

      • Recursive convolution
      • DFT
      • Loss Interpolation and fractional approaches

      STANDARDIZED CDO'S

      Index Products

      • iTraxx and CDX
      • Base Correlation (spot and term structure)
      • Index Basis
      • Index Spread calculation.

      Register Now

      For more information visit the course page on our website or call Sarah Butt on +44 20 7201 2770 or E:/
      
      

   2. Monte Carlo Methods in Finance by Dr. Jörg Kienitz
      London: 20th & 21st October 2008

      The aim of the seminar is to illustrate the applications of Monte Carlo methods in financial applications. We cover a variety of methods and examples from different areas of finance like Derivatives Pricing, Asset Allocation and Value at Risk calculation. After introducing the basic theory and some easy to understand examples we dig into more complicated financial applications from various markets. Finally, in the advanced sections we cover some of the most recent methods in this field, for example the efficient simulation of the Heston process, likelihood ratio and proxy schemes or simulating Lévy processes only to mention a few. Since we always focus on real financial problems the seminar puts advanced mathematical theory to work. Not to loose grip on the used methods we provide Excel Sheets for illustration. These sheets can later be used for your own individual studies or as a starting point for a Monte Carlo implementation.

      Day 1:

      Applications of Monte Carlo Methods in Finance and Mathematical Background

      • Derivatives Pricing
      • Value-at-Risk and Expected Shortfall Calculation
      • Scenario based Optimization and Asset Allocation
      • Basic Probability Theory (Laws of Large Numbers, Central Limit Theorem)
      • Stochastic Processes with Examples
      • Stochastic Differential Equation and basic Stochastic Calculus
      • Applications and Examples

      Random Number Generation

      • Pseudo Random Numbers
      • Congruential Generators
      • Mersenne Twister
      • Quasirandom Numbers
      • Halton Sequences
      • Sobol Sequences
      • Generating Variates Due to Distributions
      • Normal Distribution, Gamma Distribution, Chi Squared Distribution, Inverse Gaussian Distribution
      • Applications and Examples

      Path Generation - One-Dimensional Cases

      • (Geometric) Brownian Motion
      • Jump Extensions
      • NIG Processes and Variance Gamma Processes
      • Poisson Processes
      • Applications (Stochastic Processes appearing in Equity, Credit, Interest Rates)

      Path Generation - Multi-Dimensional Cases

      • Multi-Dimensional Brownian Motion (Cholesky-, Spectral Decomposition)
      • Beyond Brownian Motions
      • Copulas
      • Applications (Dependency, Credit, Interest Rates, Hybrids)

      Day 2:

      • Stochastic Volatility Models

      • The Heston and the Bates stochastic volatility model
      • Monte Carlo Simulation Techniques - Comparison of numerical schemes
      • The Quadratic Exponential (QE) Scheme
      • Applications (Equity)

      Variance Reduction Methods

      • Controlling the Error
      • Antithetic Variables
      • Control Variates
      • Importance Sampling
      • Stratified Sampling
      • Weighted Monte Carlo
      • Applications and Examples

      Advanced Monte Carlo I - Calculation of Sensitivities

      • Finite Difference Methods
      • Pathwise Methods
      • Likelihood Ratio Methods
      • Proxy Schemes
      • Applications and Examples (Greeks for Discontinuous Payoffs)

      Advanced Monte Carlo II - Early Exercise Features

      • The Longstaff Schwarz Method
      • Regression Now or Regression Later
      • Dual Methods
      • Applications and Examples (Regression Methods)

      Day schedule: 09:00 - 17:30
      Break: 10:30 - 10:45
      Lunch: 12:30 - 13:30
      Break: 15:15 - 15:30

      Contact: Neil Fowler
      T: +44(0) 1273 201352 F: +44(0) 1273 201360
      Website: http://www.wbstraining.com
      Event page: http://www.wbstraining.com/php/events/showevent.php?id=147

      
      
      

   3. FX Exotic Options Seminar with Prof. Uwe Wystup
      London, 27 - 29 October 2008

      For detailed information please visit http://www.londonfs.com/programmes/fxex_outline.htm.

      
      
      

   4. Latest Developments:
      Credit Derivatives Pricing, Hedging, Modelling & Trading Techniques:
      London: 17th - 19th November 2008

      Topics:

      Day 1: Credit Derivatives: Pricing, Hedging, Modelling & Trading Techniques

      • Pricing and Hedging of Credit Derivatives: Information-Based Models
      • New Tools for Credit Index Volatility
      • Application: Index options are NOT vanilla
      • New developments in dynamic credit modelling and applications to pathdependent credit exotics
      • Applications: Pricing TARNs, forward-starting tranches
      • Stochastic Optimal Control: an application to CPDOs
      • Optimal leverage function for CPDOs via stochastic control techniques

      Presenters:

      Dorje C. Brody: Royal Society University Research Fellow, Imperial College London
      Youssef Elouerkhaoui: Managing Director, Head of Credit Derivatives Quantitative Research, Citigroup
      Giuseppe Di Graziano: Deutsche Bank AG
      Lane P. Hughston: Professor of Financial Mathematics, King's College London
      Laurent Luciani: Head of Credit Volatility Modelling, Société Générale

      Day 2: Credit Derivatives: Pricing, Hedging, Modelling & Trading Techniques

      • Subprime Shock on Credit Markets
      • New product developments in the aftermath of subprime
      • One-factor models for Credit Derivatives - From iTraxx to TABX
      • Dynamic Spread Modelling for Credit CPPI and CPDO
      • Pricing TABX: adapting standard one factor market models
      • Dynamic Portfolio Loss Modelling
      • LCDX and Synthetic CLO structures
      • LevX and LCDX Indeces: Impact on market liquidity and future developments

      Presenters:

      Salah Amraoui: Structured Credit Trading, BNP Paribas
      Matthias Arnsdorf: Quantitative Research, JP Morgan
      Joao Garcia: Head of Credit Modelling, Dexia Bank
      Philip Gisdakis: Head of Credit Strategy & Structured Credit, UniCredit Market & Investment Banking
      Serge Goossens: Senior Quantitative Analyst, Dexia Bank

      Day 3: "After The Storm: The Future of Structured Credit"

      • Lessons to be learned
      • The correlation crisis of 2005
      • The subprime meltdown of 2007
      • Coping with CDO pricing
      • Super senior pricing
      • Prepayment risk (LCDX and ABS CDOs)
      • Proper risk management of CDOs
      • Idiosyncratic vs systemic risk
      • Correlation risk
      • Other leverage structures
      • LSS and CDPCs
      • Rating agency approaches

      Presenter:

      Jon Gregory: Global Head of Credit Derivatives Research, Barclays Capital

      Contact: Neil Fowler
      T: +44(0) 1273 201352 F: +44(0) 1273 201360
      Website: http://www.wbstraining.com
      Event page: http://www.wbstraining.com/php/events/showevent.php?id=146
      
      Fees: £999 per day + UK VAT
      Register to ANY ONE day TWO days or all THREE days of the workshop
      Register to ANY TWO days of the workshop and receive £200 discount
      Register to ALL THREE workshop days and receive £300 discount

      
      
      

   5. Latest Developments:
      Interest Rate Modelling & Interest Rate Exotic & FX Hybrid Products::
      London: 24th - 25th November 2008

      Topics:

      Day 1: Rate Modelling: Pricing, Hedging & Calibration Techniques

      • Managing Smile Risk
      • The SABR model, vanna, volga and managing smile risk
      • Levy based models
      • Managing Exotic Interest Rate Products
      • Calibration/pricing/hedging cycle
      • Models for exotics
      • Practical Pricing of Exotics
      • Auto-calibration/global calibration
      • Extension to other callable exotics
      • Pricing Callable Range Notes
      • Adjusters and risk migration
      • Callable range notes

      Presenter:

      Pat Hagan: Head Quantitative Analytics, Chief Investment Office, JP Morgan

      Day 2: Interest Rate Modelling

      • Mathematical Theory of Interest Rate Term Structure Dynamics and Calibration
      • Markov Functional models (including multi-currency, multi-factor and forward smile)
      • 1-factor Markov Functional Models: the Hunt-Kennedy-Pelsser calibration method
      • Markov Functional models and forward smile
      • CMS & CMS spread options
      • Pricing & modelling of correlation copula models Markovian projection
      • Swaptions arbitrage

      Presenters:

      Dorje C. Brody: Royal Society University Research Fellow, Imperial College London
      Luca Capriotti: Vice President, Global Modelling and Analytics Group, Credit Suisse Investment Banking Division
      Lane P. Hughston: Professor of Financial Mathematics, King's College London
      Simon Johnson: Co-head of Credit and Interest Rate Financial Engineering, Commerzbank
      Julien Turc: Quantitative Strategy, Société Générale

      Day 3: Interest Rate Exotic & FX Hybrid Products

      • Cross Currency Models
      • History of FX model for long dated structures
      • Long Dated FX Hybrids
      • PRDC and FX Tarn payoffs
      • Exotic Interest Rate Pricing with Trees
      • Gaussian Model and Extensions
      • Wavelet Option Pricing
      • General Pricing using the Green functions

      Presenters:

      Messaoud Chibane: Senior Quantitative Analyst, Bank of America
      Antonio Cosma: Université du Luxembourg
      Dherminder Kainth: QuARC, Royal Bank of Scotland
      Michael Roehl: Senior Quant, Interest Rate Modelling/Hybrids, Morgan Stanley

      Contact: Neil Fowler
      T: +44(0) 1273 201352 F: +44(0) 1273 201360
      Website: http://www.wbstraining.com
      Event page: http://www.wbstraining.com/php/events/showevent.php?id=143
      
      Fees: £999 per day + UK VAT
      Register to ANY ONE day TWO days or all THREE days of the workshop
      Register to ANY TWO days of the workshop and receive £200 discount
      Register to ALL THREE workshop days and receive £300 discount

      
      
      

   6. Pricing Exotic Interest Rate Derivatives
      The LIBOR Market Model in QuantLib
      MoneyScience Masterclass with Mark Joshi
      25 - 27 February 2009
      The Institute of Physics, London, UK

      Further Information and Course Outline at http://www.moneyscience.com/Events_Noticeboard/article558

      Book before September 30th to Receive a 20% 'Early Bird' Discount and before November 30th to receive a 10% Discount.

      This three-day course will be led by an international expert who played a large role in the coding of the LIBOR market model in the QuantLib C++ open-source project. He will examine the practical problems that arise when implementing the LIBOR market model to price exotic interest rate derivatives. Each issue will be discussed at theoretical, practical and coding levels. The solution of these using QuantLib classes will be the focus of the course.

      We will see how QuantLib provides a free easily-extendible implementation that achieves rapid pricing and sensitivity computation, and stable calibration to the market; whilst being able to cope with path-dependence, discontinuous pay-offs and early exercise features.

      • "Great Interactivity"
      • "Relevant and timely coverage of recent developments"
      • "Very Practical"
      • "Relaxed, Broad coverage"

      Mark Joshi obtained a B.A. in mathematics from the University of Oxford in 1990, and a Ph.D. in pure mathematics from the Massachusetts Institute of Technology in 1994. He was an Assistant Lecturer in the department of pure mathematics and mathematical statistics at Cambridge University from 1994 to 1999. Following which he worked for the Royal Bank of Scotland from 1999 to 2005 as a quantitative analyst at a variety of levels, finishing as the Head of Quantitative Research for Group Risk Management. He joined Melbourne University in November 2005 as an Associate Professor.

      
      
      

   7. Financial E'trics Conferences 2009 in Berlin

      March 19, 2009: CASE-QPL Distinguished Lecture Series

      Tim Bollerslev and Torben Andersen: "Recent Developments in Measuring and Modeling Financial Market Volatility"

      Torben G. Andersen and Tim Bollerslev are leading experts in the area of financial econometrics and are particularly well recognized for their contributions to the measuring and forecasting financial market volatility. The quantification of an asset's or a market's volatility is a central aspect in financial practice. It is of enormous importance for asset pricing, portfolio allocation and risk management. The lecture series deals with recent developments in the areas of implied and realized volatility modelling. Besides implications for forecasting, newest insights into the relations between both volatility concepts will be discussed. For further information please see on http://www.case.hu-berlin.de/events/events/Archive/DLS2009/

      March 20/21, 2009: Humboldt-Copenhagen Conference 2009:
      "Recent Developments in Financial Econometrics"

      Keynote speakers: Neil Shephard and Joel Hasbrouck

      The Humboldt-Copenhagen Conference 2009 aims to present and discuss recent topics in Financial Econometrics such as

      :
      • Volatility and Correlation
      • Dynamic (Latent) Factor Models
      • High-Frequency Finance and Market Microstructure Analysis
      • Risk Management and Asset Pricing

      You are cordially invited to submit papers in all areas of financial econometrics/statistics and quantitative finance. Submission Deadline is October 24, 2008. For further information please see on http://www.hu-ku-conference.de/.

      Electronic submissions to:

      Location:

      Humboldt-Universität zu Berlin
      School of Business and Economics
      Spandauer Straße 1
      10178 Berlin

      Contacts:

      Prof. Dr. Nikolaus Hautsch
      Phone: +49 - 30 - 2093 5711
      E-mail:
      
      Oliver Blaskowitz
      Phone: +49 - 30 - 2093 5705
      E-mail:

      
      
      

   8. Frankfurt MathFinance Conference
      Changed Date to: March 23-24 2009

      http://conference.mathfinance.com

      
      
      
3. MathFinance Resources
   
   

   1. Don't Blame The Quants
      by Steven Shreve 10.08.08, 12:01 AM ET, on Forbes.com

      http://www.forbes.com/opinions/2008/10/07/securities-quants-models-oped-cx_ss_1008shreve.html

      Financial markets are a mess, and the excesses of the finance industry are dragging down the whole economy. In recent years, safe investments delivered unusually low returns, and hordes of investors seeking to be above average (as Garrison Keillor would say) bought extremely complicated instruments.

      The investment banks created such instruments, so-called mortgage-backed securities, with payoffs that depend on the performance of hundreds or even thousands of mortgages. Many of these securities received investment-grade ratings, and their returns were significantly greater than investing in a comparably rated bond. The law that higher risk means higher expected return seemed to have been repealed. The practice of "ratings arbitrage," getting a better-than-merited rating and selling securities based on that rating, was born.

      It is easy under these circumstances to point an accusing finger at the "quants" on Wall Street, that cadre of mathematics and physics Ph.D.s who crunch numbers in esoteric models. Without the quants, the complicated mortgage-backed securities that fueled the housing bubble and led to the freezing of credit might not have been created. The models used by the quants determine the prices of those securities and steer the traders who make markets in them. Without this guidance, the banks might not have touched them in the first place. To prevent a recurrence of financial crises, some call for a return to a simpler time, before derivative securities and the quants who analyze them--a time when investors bought stocks and bonds and little else.

      Such complaints miss the point. When a bridge collapses, no one demands the abolition of civil engineering. One first determines if faulty engineering or shoddy construction caused the collapse. If engineering is to blame, the solution is better--not less--engineering. Furthermore, it would be preposterous to replace the bridge with a slower, less efficient ferry rather than to rebuild the bridge and overcome the obstacle.

      There are very good reasons for the existence of derivative securities--and even mortgage-backed securities, the root of our present problems. Potential homeowners need investors to fund their mortgages. So how can the two come together? The Savings and Loan system was a major provider of mortgages until its spectacular collapse in the 1980s, causing the Federal Deposit Insurance Corporation to require $120 billion from the U.S. Treasury to make depositors whole again.

      Today, foreign institutions have the big money--and they would not make deposits in U.S. Savings and Loans even if such institutions were available. Energy trading did not disappear with the demise of Enron, and neither will mortgage-backed securities after this fiasco. Put simply, the bridge between lenders and borrowers will be rebuilt, because we need it. It should, however, be built with better engineering and greater simplicity than before.

      Before the collapse, Carnegie Mellon's alumni in the industry were telling me that the level of complexity in the mortgage-backed securities market had exceeded the limitations of their models. The bridge was cantilevered out way too far, and the quants knew it. But in most banks, the quants are not the decision-makers. When they issue warnings that stand in the way of profits, they are quickly brushed aside. Furthermore, in addition to better engineering, the bridge must not be built this time with the shoddy construction material of no-documentation mortgage applications and a network of unscrupulous mortgage originators.

      Regardless of what some may wish, we will not revert to a simpler time before derivative securities; that simpler time never existed. Options have been traded since the 17th century--and even before that, in ancient times, by some accounts.

      These instruments serve an economic purpose. Southwest Airlines recently reported its 69th consecutive quarterly profit, weathering two spikes in the price of jet fuel since 1991, because it used derivative securities to hedge against price increases. International firms use derivative securities to hedge currency risk. Insurance firms sell annuities that guarantee a lifetime income and must use derivative securities to hedge against increases in longevity. The quants did not create derivative securities. The quants help us understand them, price them, trade them and manage the risk associated with them.

      The quants know better than anyone how their models can fail. For banks, the only way to avoid a repetition of the current crisis is to measure and control all their risks, including the risk that their models give incorrect results. On the other hand, the surest way to repeat this disaster is to trust the models blindly while taking large-scale advantage of situations where they seem to provide trading strategies that would yield results too good to be true. Because this bridge will be rebuilt, the way out of our present dilemma is not to blame the quants. We must instead hire good ones--and listen to them.

      Steven Shreve is the Orion Hoch professor of mathematical sciences at Carnegie Mellon University and one of the founders of Carnegie Mellon's bachelor's, master's and Ph.D. programs in quantitative finance.

      
      
      

   2. Master of Quantitative Finance at Frankfurt School

      Study Quantitative Finance in 11 block weeks tought by industry practioners in English

      Detailed information is at
      http://www.frankfurt-school.de/content/en/education_programmes/academic_programmes/master_science/mqf

      
      
      

   3. Master's in Financial Engineering Program
      UC Berkeley's Haas School of Business

      Applications for the 2009-2010 term are now open The Master's in Financial Engineering Program provides students with a one-year graduate degree from UC Berkeley's Haas School of Business. Instruction is led by world-renowned faculty from the academic community and by current financial practitioners.

      Detailed information can be found at

      http://mfe.haas.berkeley.edu/.