Implementing CCR and CVA in a Primary International Bank


 Posy Cole
 2 years ago
 Views:
Transcription
1 Implementing CCR and CVA in a Primary International Bank
2 Index Introduction 1 Introduction 2 3
3 Index Introduction 1 Introduction 2 3
4 Counterparty Credit Risk and Credit Value Adjustment The main goal of the CCR is determining an adequate EC for actual unexpected counterparty credit losses, the future real distribution of the contracts exposures is needed, so that simulations can be performed with evolution of risk factors whose dynamics is calibrated on historical data, although the revaluation of the deals will be riskneutral in any case. The CCR is not computed to be managed with hedging strategies, but it is based on a reserve approach. This means that sensitivities to risk factors are not needed. The CVA is a risk measure used to adjust the fair value of the derivatives contracts to account for expected losses due to the default of the counterparty. The value of a contract is adjusted at inception, either on a standalone or incremental basis, and then the adjustment is updated in the future accordingly to the NPV of the contract (or netted portfolio of contracts) and to the counterparty s PD.
5 Counterparty Credit Risk and Credit Value Adjustment Implications: The CVA is calculated using market data, Consistency constraints: The future distribution of the netted portfolio of contracts with a given counterparty, being risk neutral, is obtained by a unified framework whereby the both the simulation and the pricing are performed by the same (riskneutral) dynamics for the relevant risk factors. CVA s sensitivities to the risk factors have to be computed so as to allow for a dynamic hedging of its volatility by market instruments. Challenges: the CVA is calculated by numerical schemes (e.g.: Montecarlo): the computational burden is quite heavy if these have to produce also sensitivities, the reliability of the results has to be carefully verified: numerical differentiation is unstable for Montecarlo and many thousands of simulations are needed to achieve acceptable accuracy.
6 Counterparty Credit Risk and Credit Value Adjustment CCR CVA Risk Factor Dynamics Real Risk Neutral Pricing of Contracts Risk Neutral Risk Neutral Sensitivities No Yes Goal EC Fair Value Adjustment & Hedging Table: Differences between CCR and CVA.
7 Index Introduction 1 Introduction 2 3
8 CCR Workflow
9 How Scenarios are Generated 1 The general principle is to take the initial market data and apply to them bumps computed by simulation models. 2 The bumped market data at the moment are Zero curves OIS and fixing (1M, 3M, 6M and 1Y) Libor curves; FX rates; 3 No bumping is applied to volatility surfaces future dates are considered. 5 For each future date, 1000 scenarios are generated.
10 Interest Rates Short rate bumps are generated through the following model: dr t = κ[θ(t) r t]dt +σdw t 4 BUMP EONIA BUMP EONIA This is a single factor short rate model which produces the entire set of discount factors for the basic OIS curve Fixing Libor curves are generated by assuming a constant spread over the OIS curve
11 FX Rates For the path simulation of the FX rate the model used is a Brownian bridge. The FX rate is assumed to be a standard BGM: 1.4 Bumping EUR/USD Bumping EUR/USD 1.2 ds = rsdt +σsdw The Brownian Bridge has the following distribution: W s u = ( (s u) W N, t u ) (t s)(s u) t u
12 Deal Revaluation For each time step and each scenario the FRE (Full Revaluation Engine) reprices every deal. For each deal there is a cube of NPVs over 1000 scenario 40 time steps. The risk control group receives these data and aggregate them according to existing netting and collateral agreements.
13 Facts at the Beginning of the Project CVA was calculated with the approach sketched above with the following IT resources: Hardware: grid of 3,500 Windows 64 bit cores, but only 300 actually exploited; Software: FRE client, a multithread Java application running on Solaris host. FRE server, a Java application developed as a Platform Symphony service (grid service) on Windows host The portfolio comprised about 45,000 OTC contracts. The computation time was 5 days.
14 Facts to Date The CVA project follows two lines of intervention: Overhaul of the FRE client and server, by eliminating bottleneck and allowing the complete usage of the available grid; Rewriting of the pricing function, in C++/Java. Some formulae of the proprietary financial library have been optimised to make them as fast as possible for CVA purposes. For FX products, pricing formulae have been written based on the B&S model with VannaVolga adjustments. The technological stream of the project has achieved a reduction in the calculation time to 3.5 hours. The methodological stream has added a further reduction so that the total computation time is now of 1.5 hours.
15 Future Steps In next future the project will focus on two classes of products to be added to the existing ones: Equity derivatives; Credit derivatives;
16 Index Introduction 1 Introduction 2 3
17 Full Revaluation Engine The core of the CVA calculation is the so called Full Revaluation Engine (FRE), performs the following tasks: loading trade data; loading market data for each scenario; pricing of each trade for each scenario and for each future date; output of data in a cube form (one dimension representing trades, another scenarios and the last one representing dates). A more centralized organization of the calculations is vital to achieve improved performances, which means more accurate results and more information (EPE, PFE, Greeks, etc.).
18 Full Revaluation Engine Scenario Netting Sets Simulation and Collateral Revaluation and Greeks Risk Metrics and CVA Scenarios generated for relevant asset classes: Interest Rates FX Spot Rates Credit Spreads Equity Prices Deals aggregation for: Clients Netting Set Collateral management Deals revaluation in all scenarios Greeks with respect to market risk factors Undrelrying asset(s) Volatility Correlation Expected and potential exposures: EPE PFE Fair Value Adjustment: CVA Figure: Proposed Workflow for the FRE.
19 Full Revaluation Engine In the new setting, the FRE performance would benefit from the centralized operations on the deals aggregation and collateral management and on the joint scenario generation and revaluation. This will allow to implement very efficient procedures to: Price deals and netted portfolios; Management of the collateral and of the grace periods after defaults; Greeks calculations (see below).
20 Fast Pricing Function There is a huge scope for improving the performance of the calculation engine. Interest rate swaps (IRS) and caps&floors are best candidates. The guiding principle in optimizing the pricing functions are: Reduce the amount of arithmetic operations required to calculate the cashflows. The idea is to precompute all the cashflows (both for the fixed and for the floating leg) and storing them into an array that is passed into the pricing function that evaluates the flows and do the present value calculation. Simplify the calculations and avoiding many calculations inside the pricing function. This strategy gives a reduction of the computational effort required by the pricing function, speeding up the overall computation time.
21 Fast Pricing Function For ease of comparison we show in table 2 the computation times of the standard Unilib functions and the new optimized functions for a standard swap contract and a cap&floor, both maturing in 5 years. The CPU is an Intel Core2Duo 2.93 GHz, 3.46GB of RAM. N. per 1 sec. IRS µs per 1 contract Standard Functions 200 5,000 Optimized Functions 50, N. per 1 sec. C&F µs per 1 contract Standard Functions 200 5,000 Optimized Functions 10, Table: Number of contracts priced in 1 second and the number of microseconds required to price 1 contract with the standard and optimized functions.
22 Parallel calculus and GPUs The availability of massively parallel hardware, such as GPUs, makes possible the acceleration of the pricing algorithms. To take advantage of this kind of hardware, the libraries have to be overhauled at a code level, by a complete rewriting to make them fit into a SIMD paradigm (single instruction multiple data). Two approaches are possible: 1 fast pricing of complex derivatives: parallel hardware is used to solve partial differential equations with finite elements method (involve linear algebra routines) or with Montecarlo method (simulation on many path in parallel); a single trade is priced in a fast way; 2 parallel pricing of simple products: pricing of plain vanilla trades of a large portfolio (e.g.: swaps) can be decomposed in the pricing of simple components (e.g.: swap cashflows), components can be aggregated (stored in large arrays) and priced in parallel, finally components prices can be summed to get trades prices; many trades are priced simultaneously.
23 Parallel calculus and GPUs We show the calculation times for the optimized functions on the standard CPU described (same as in second row of table 2) and on a GPU Nvidia Tesla M2070Q. N. per 1 sec. IRS µs per 1 contract CPU 50, CPU 1,000,000 1 N. per 1 sec. C&F µs per 1 contract CPU 10, CPU 170, Table: Number of contracts priced in 1 second and the number of microseconds required to price 1 contract.
24 American Montecarlo Method Typically metrics such as EPE or PFE imply a numerical revaluation of netted portfolios via Montecarlo. Montecarlo simulations are used to generate scenarios of risk factors, and when also the deals included in the portfolio need a Montecarlo pricing, the computation burden easily becomes unbearable. The purpose of the American Montecarlo (AM) is to speed up the pricing of exotic trades that requires a Montecarlo method. The brute force approach would be a Montecarlo pricing in each of the (thousands) generated scenarios. The AM optimization consists in the use of the scenarios path to perform evaluation of the exotic trades, avoiding the run of a nested Montecarlo.
25 Greeks Introduction Greeks can be computed brute force by finite difference method: a Montecarlo simulation is launched with tilted starting value of the relevant stochastic factor(s) and/or parameters and the sensitivities are derived from the resulting change in the contract s value. This method is clearly very expensive under a computational point of view and it is worth exploring efficient alternatives whenever they are feasible. We suggest two methods with low computational intensity: 1 Adjoint algorithmic differentiation: It relies on the fact that computer programs are composed of a set of elementary functions; once partial derivative of these elementary function are known, derivatives can be computed using the chain rule. 2 Linear regression:ne tries and approximate by a polynomial the value of a contract. The coefficient of the polynomial are obtained by fitting the chosen function to the terminal valued of the contract simulated by the Montecarlo procedure. The calibrated polynomial is then used to retrieve the value of the contract at any date before the expiry.
26 About Iason Iason is a company created by market practitioners, financial quants and programmers with valuable experience achieved in dealing rooms of financial institutions. Iason offers a unique blend of skills and expertise in the understanding of financial markets, in the pricing of complex financial instruments and in the measuring and the management of banking risks. The company s structure is very flexible and grants a fully bespoke service to our Clients. Iason believes that the ability to develop new quantitative finance approaches through research, and to apply them in practice, is critical to innovation in risk management and pricing. It constantly strives to bring into all the areas of the risk management a new and fresh approach based on the balance between rigour and efficiency which its people aimed at when working in the dealing rooms. Besides tailor made services, Iason develops software applications to calculate and monitor credit VaR and conterparty VaR, fund transfer pricing and loan pricing, liquidityatrisk. c Iason /2011 This is a Iason s creation. The ideas and the model frameworks described in this presentation are the fruit of the intellectual efforts and of the skills of the people working in Iason. You may not reproduce or transmit any part of this document in any form or by any means, electronic or mechanical, including photocopying and recording, for any purpose without the express written permission of Iason ltd.
CVA Desk in the Bank
CVA Desk in the Bank Implementation Counterparty Credit Risk represents the risk that the counterparty of an OTC will default before the maturity of the contract and therefore will not make the remaining
More informationARMS Counterparty Credit Risk
ARMS Counterparty Credit Risk PFE  Potential Future Exposure & CVA  Credit Valuation Adjustment An introduction to the ARMS CCR module EXECUTIVE SUMMARY The ARMS CCR Module combines market proven financial
More informationManaging Counterparty Credit Risk through CVA. Karin Bergeron Director, CVA Trading
Managing Counterparty Credit Risk through CVA Karin Bergeron Director, CVA Trading Agenda 1. Background 2. Motivation for CVA desk 3. Organization/Mandate of CVA desk 4. Pretrade/Dealtime pricing of
More informationPotential Future Exposure and Collateral Modelling of the Trading Book Using NVIDIA GPUs
Potential Future Exposure and Collateral Modelling of the Trading Book Using NVIDIA GPUs 19 March 2015 GPU Technology Conference 2015 Grigorios Papamanousakis Quantitative Strategist, Investment Solutions
More informationHigh Performance Counterparty Risk and CVA Calculations in Risk Management
High Performance Counterparty Risk and CVA Calculations in Risk Management Dominique Delarue Azim Siddiqi 20 th March 2013 Title of presentation Overview Counterparty Risk Primer The Problem Scale Scale
More informationCounterparty Credit Risk (CCR) with MATLAB Production Server Brendan Hannigan and Gabo LopezCalva
Counterparty Credit Risk (CCR) with MATLAB Production Server Brendan Hannigan and Gabo LopezCalva 2013 The MathWorks, Inc. 1 Outline Counterparty Credit Risk (CCR) Introduction to MATLAB Production Server
More informationAmerican Monte Carlo for Bermudan CVA. Roland Lichters
American Monte Carlo for Bermudan CVA Roland Lichters IKB QuantLib Workshop, 4 December 2014 Outline Background Problem Way Out Example and Results Appendix 2014 Quaternion Risk Management Ltd. 2 Outline
More informationWHITE PAPER CHALLENGES IN IMPLEMENTING A COUNTERPARTY RISK MANAGEMENT PROCESS. Key data and technology challenges Current trends and best practices
WHITE PAPER CHALLENGES IN IMPLEMENTING A COUNTERPARTY RISK MANAGEMENT PROCESS Authored by David Kelly (Quantifi) Key data and technology challenges Current trends and best practices www.quantifisolutions.com
More informationEDF CEA Inria School Systemic Risk and Quantitative Risk Management
C2 RISK DIVISION EDF CEA Inria School Systemic Risk and Quantitative Risk Management EDF CEA INRIA School Systemic Risk and Quantitative Risk Management Regulatory rules evolutions and internal models
More informationRisk analysis with depth. Software, Services and. XVA Capital IM Limits Adjoint
Risk analysis with depth CompatibL Risk Software, Services and Consultancy XVA Capital IM Limits Adjoint The CompatibL development team has demonstrated extraordinary commitment, skill and flexibility,
More informationBig Data & Analytics. Counterparty Credit Risk Management. Big Data in Risk Analytics
Deniz Kural, Senior Risk Expert BeLux Patrick Billens, Big Data Solutions Leader Big Data & Analytics Counterparty Credit Risk Management Challenges for the Counterparty Credit Risk Manager Regulatory
More informationSwaps Market, evolution, valuation. Julien LORENZI, Adfin Analytics Quant team Manager 27 th March 2014
Swaps Market, evolution, valuation THOMSON REUTERS Julien LORENZI, Adfin Analytics Quant team Manager 27 th March 2014 Agenda for today A brief introduction Swap Market volume trends Swaps Definition and
More informationOpenGamma Quantitative Research Adjoint Algorithmic Differentiation: Calibration and Implicit Function Theorem
OpenGamma Quantitative Research Adjoint Algorithmic Differentiation: Calibration and Implicit Function Theorem Marc Henrard marc@opengamma.com OpenGamma Quantitative Research n. 1 November 2011 Abstract
More informationat ICAP: RESET & ReMATCH
Basis Risk Mitigation services at ICAP: RESET & ReMATCH Guy Rowcliffe CEO RESET and BRM Group July 2012 Definition of basis risk Basis Risk is defined by the Derivative Consulting Group Glossary as: The
More informationMaster of Mathematical Finance: Course Descriptions
Master of Mathematical Finance: Course Descriptions CS 522 Data Mining Computer Science This course provides continued exploration of data mining algorithms. More sophisticated algorithms such as support
More informationAccelerating Market Value at Risk Estimation on GPUs
Accelerating Market Value at Risk Estimation on GPUs NVIDIA Theater, SC'09 Matthew Dixon1 Jike Chong2 1 Department of Computer Science, UC Davis 2 Department of Electrical Engineering and Computer Science,
More informationChallenges in Counterparty Credit Risk Modelling
Risk Netværket I2016 Challenges in Counterparty Credit Risk Modelling Alexander SUBBOTIN Head of Counterparty Credit Risk Models & Measures, Nordea May 26, 2016 Disclaimer This document has been prepared
More informationFinancial derivatives in Risk Management
Financial derivatives in Risk Management A practical introduction for the MSc class of the UvA Business School 1 Contents Risk categories related to financial derivatives Market risk Overview Risk Management
More informationSome Practical Issues in FX and Equity Derivatives
Some Practical Issues in FX and Equity Derivatives Phenomenology of the Volatility Surface The volatility matrix is the map of the implied volatilities quoted by the market for options of different strikes
More informationRisk elearning. Modules Overview.
Risk elearning Modules Overview elearning Overview Return vs Risk Optimization Risk Management as a Strategic Asset Risk Appetite Portfolio Aggregation Risk Aggregation Stress Scenario Risk Valuation
More informationCVA on an ipad Mini Part 3: XVA Algorithms
CVA on an ipad Mini Part 3: XVA Algorithms Aarhus Kwant Factory PhD Course January 2014 Jesper Andreasen Danske Markets, Copenhagen kwant.daddy@danskebank.com XVA Calculations The task is to compute T
More informationNVIDIA CUDA Software and GPU Parallel Computing Architecture. David B. Kirk, Chief Scientist
NVIDIA CUDA Software and GPU Parallel Computing Architecture David B. Kirk, Chief Scientist Outline Applications of GPU Computing CUDA Programming Model Overview Programming in CUDA The Basics How to Get
More informationAMF Instruction DOC Calculation of global exposure for authorised UCITS and AIFs
AMF Instruction DOC201115 Calculation of global exposure for authorised UCITS and AIFs Reference texts : Articles 41172 to 41181 and 42251 to 42260 1 of the AMF General Regulation 1. General provisions...
More informationCHAPTER 6. Different Types of Swaps 1
CHAPTER 6 Different Types of Swaps 1 In the previous chapter, we introduced two simple kinds of generic swaps: interest rate and currency swaps. These are usually known as plain vanilla deals because the
More informationCALYPSO ENTERPRISE RISK SYSTEM
1 CALYPSO ENTERPRISE RISK SYSTEM Dr Philip Symes Introduction 2 Calypso's Enterprise Risk Service (ERS) is part of their FronttoBack software system. Calypso ERS provides the Middle Office risk function.
More informationA Guide to Modelling Counterparty Credit Risk
A Guide to Modelling Counterparty Credit Risk What are the steps involved in calculating credit exposure? What are the differences between counterparty and contractlevel exposure? How can margin agreements
More informationBasis Risk Mitigation in the New Regulatory Framework Washington, May 2011
MEMORANDUM TO: File No. S70811; S70611 FROM: Andrew Blake Division of Trading and Markets RE: Meeting with Representatives from ICAP DATE: May 17, 2011 On May 17, 2011, representatives from the Securities
More information(Part.1) FOUNDATIONS OF RISK MANAGEMENT
(Part.1) FOUNDATIONS OF RISK MANAGEMENT 1 : Risk Taking: A Corporate Governance Perspective Delineating Efficient Portfolios 2: The Standard Capital Asset Pricing Model 1 : Risk : A Helicopter View 2:
More informationContents. List of Figures. List of Tables. Acknowledgments PART I INTRODUCTION 1
List of Figures List of Tables Acknowledgments Preface xv xix xxi xxiii PART I INTRODUCTION 1 1 The Evolution of Financial Analysis 3 1.1 Bookkeeping 3 1.2 Modern finance 8 1.3 Departments, silos and analysis
More informationWith the derivative markets having changed dramatically since the 2008 financial crisis,
Avoiding Collateral Surprises: Managing MultiCurrency CSAs Anna Barbashova, Numerix  24 Jan 2013 This article explores multicurrency credit support annexes (CSAs) in the derivatives area and their potential
More informationBetter Risk Management for Improved Business Decision Making
WHITE PAPER Better Risk Management for Improved Business Decision Making SAS Risk Management for Banking Table of Contents Introduction...1 SAS Risk Management for Banking...2 Infrastructure...2 Risk Data
More informationLIBOR vs. OIS: The Derivatives Discounting Dilemma
LIBOR vs. OIS: The Derivatives Discounting Dilemma John Hull PRMIA May 2012 1 Agenda OIS and LIBOR CVA and DVA The Main Result Potential Sources of Confusion FVA and DVA See John Hull and Alan White: LIBOR
More informationCounterparty Risk. Gabor Fath Morgan Stanley
Counterparty Risk Gabor Fath Morgan Stanley Counterparty credit risk  definition Counterparty credit risk (CP risk) is the risk that the counterparty to a financial contract will default prior to the
More informationINSTITUTE AND FACULTY OF ACTUARIES EXAMINATION
INSTITUTE AND FACULTY OF ACTUARIES EXAMINATION 14 April 2016 (pm) Subject ST6 Finance and Investment Specialist Technical B Time allowed: Three hours 1. Enter all the candidate and examination details
More informationWebinar #2. Introduction to IAS39 hedge accounting with Fairmat. Fairmat Srl 18/07/2013
Webinar #2 Introduction to IAS39 hedge accounting with Fairmat Fairmat Srl 18/07/2013 Agenda Brief notes on IAS39 hedge accounting 1 Brief notes on IAS39 hedge accounting 2 3 Introduction Prospective
More informationBasel Committee on Banking Supervision. Basel III counterparty credit risk  Frequently asked questions
Basel Committee on Banking Supervision Basel III counterparty credit risk  Frequently asked questions November 2011 Copies of publications are available from: Bank for International Settlements Communications
More informationFor the purposes of this Annex the following definitions shall apply:
XIV. COUNTERPARTY CREDIT RISK 1. Definitions ANNEX III: THE TREATMENT OF COUNTERPARTY CREDIT RISK OF DERIVATIVE INSTRUMENTS, REPURCHASE TRANSACTIONS, SECURITIES OR COMMODITIES LENDING OR BORROWING TRANSACTIONS,
More informationStress Testing Trading Desks
Stress Testing Trading Desks Michael Sullivan Office of the Comptroller of the Currency Paper presented at the Expert Forum on Advanced Techniques on Stress Testing: Applications for Supervisors Hosted
More informationHedging Illiquid FX Options: An Empirical Analysis of Alternative Hedging Strategies
Hedging Illiquid FX Options: An Empirical Analysis of Alternative Hedging Strategies Drazen Pesjak Supervised by A.A. Tsvetkov 1, D. Posthuma 2 and S.A. Borovkova 3 MSc. Thesis Finance HONOURS TRACK Quantitative
More informationThe properties of interest rate swaps An investigation of the price setting of illiquid interest rates swaps and the perfect hedging portfolios.
The properties of interest rate swaps An investigation of the price setting of illiquid interest rates swaps and the perfect hedging portfolios. Max Lindquist 12/23/211 Abstract The main purpose of this
More informationAPT Integrated risk management for the buyside
APT Integrated risk management for the buyside SUNGARD S APT: INTEGRATED RISK MANAGEMENT FOR THE BUYSIDE SunGard APT helps your business to effectively monitor and manage its investment risks. Whatever
More informationUsing least squares Monte Carlo for capital calculation 21 November 2011
Life Conference and Exhibition 2011 Adam Koursaris, Peter Murphy Using least squares Monte Carlo for capital calculation 21 November 2011 Agenda SCR calculation Nested stochastic problem Limitations of
More informationCITIGROUP INC. BASEL II.5 MARKET RISK DISCLOSURES AS OF AND FOR THE PERIOD ENDED MARCH 31, 2013
CITIGROUP INC. BASEL II.5 MARKET RISK DISCLOSURES AS OF AND FOR THE PERIOD ENDED MARCH 31, 2013 DATED AS OF MAY 15, 2013 Table of Contents Qualitative Disclosures Basis of Preparation and Review... 3 Risk
More informationInterest Rate Swaps and Fixed Income Portfolio Analysis
White Paper Interest Rate Swaps and Fixed Income Portfolio Analysis Copyright 2014 FactSet Research Systems Inc. All rights reserved. Interest Rate Swaps and Fixed Income Portfolio Analysis Contents Introduction...
More informationHARDWARE ACCELERATION IN FINANCIAL MARKETS. A step change in speed
HARDWARE ACCELERATION IN FINANCIAL MARKETS A step change in speed NAME OF REPORT SECTION 3 HARDWARE ACCELERATION IN FINANCIAL MARKETS A step change in speed Faster is more profitable in the front office
More informationPricing complex options using a simple Monte Carlo Simulation
A subsidiary of Sumitomo Mitsui Banking Corporation Pricing complex options using a simple Monte Carlo Simulation Peter Fink Among the different numerical procedures for valuing options, the Monte Carlo
More informationINITIAL MARGIN AND GUARANTEE FUND CALCULATIONS
INITIAL MARGIN AND GUARANTEE FUND CALCULATIONS Initial Margin Calculation: Initial margin is the guarantee amount requested in advance to compensate for the risks exposed to from the date of the default
More informationSoftware that writes Software Stochastic, Evolutionary, MultiRun Strategy AutoGeneration. TRADING SYSTEM LAB Product Description Version 1.
Software that writes Software Stochastic, Evolutionary, MultiRun Strategy AutoGeneration TRADING SYSTEM LAB Product Description Version 1.1 08/08/10 Trading System Lab (TSL) will automatically generate
More informationINTEREST RATES AND FX MODELS
INTEREST RATES AND FX MODELS 8. Portfolio greeks Andrew Lesniewski Courant Institute of Mathematical Sciences New York University New York March 27, 2013 2 Interest Rates & FX Models Contents 1 Introduction
More informationApplication of Interest Rate Swaps in Indian Insurance Industry Amruth Krishnan Rohit Ajgaonkar Guide: G.LN.Sarma
Institute of Actuaries of India Application of Interest Rate Swaps in Indian Insurance Industry Amruth Krishnan Rohit Ajgaonkar Guide: G.LN.Sarma 21 st IFS Seminar Indian Actuarial Profession Serving the
More informationContents. Bibliografische Informationen http://dnb.info/996662502. digitalisiert durch
Part I Methodology 1 Introduction 3 1.1 Basic Concepts. 3 1.2 Preliminary Examples 4 1.2.1 Vanilla InterestRate Swap 4 1.2.2 Cancellable Swap.. 5 1.2.3 Managing Credit Risk Collateral, Credit Default
More information4. ANNEXURE 3 : PART 3  FOREIGN EXCHANGE POSITION RISK
Annexure 3 (PRR)  Part 3, Clause 18  Foreign Exchange Position Risk Amount 4 ANNEXURE 3 : PART 3  FOREIGN EXCHANGE POSITION RISK (a) CLAUSE 18  FOREIGN EXCHANGE POSITION RISK AMOUNT (i) Rule PART 3
More informationSizing ASAP FOR BW ACCELERATOR SAP BUSINESS INFORMATION WAREHOUSE. How to size of a BW system SIZING AND PERFORMANCE. Version 3.
Sizing ASAP FOR BW ACCELERATOR SAP BUSINESS INFORMATION WAREHOUSE How to size of a BW system Version 3.1 December 2004 2004 SAP AG 1 Table of Contents ASAP for BW Accelerator... 1 1 INTRODUCTION... 1 2
More informationCREDIT VALUE ADJUSTMENT AND THE CHANGING ENVIRONMENT FOR PRICING AND MANAGING COUNTERPARTY RISK
Executive Summary The market volatility experienced during the financial crisis has driven many firms to review their methods of accounting for counterparty credit risk. The traditional approach of controlling
More informationCVA, Hedging and Best Practices Denny Yu, CFA
CVA, Hedging and Best Practices Denny Yu, CFA February 28, 2012 Agenda CVA and the trading desk Hedging of CVA risk Best practices in CVA solutions CVA Impact on the Trading Desk Definitions Potential
More informationMarket Risk Analysis. Quantitative Methods in Finance. Volume I. The Wiley Finance Series
Brochure More information from http://www.researchandmarkets.com/reports/2220051/ Market Risk Analysis. Quantitative Methods in Finance. Volume I. The Wiley Finance Series Description: Written by leading
More informationThe Regulatory Capital Treatment of Credit Exposures Arising From Derivative Transactions
The Regulatory Capital Treatment of Credit Exposures Arising From Derivative Transactions Prepared By: Algorithmics Incorporated Date: May 30, 2001 1. Background Algorithmics was founded in 1989 in response
More informationOVERVIEW OF THE USE OF CROSS CURRENCY SWAPS
OVERVIEW OF THE USE OF CROSS CURRENCY SWAPS PRACTICAL CONSIDERATIONS IVAN LARIN CAPITAL MARKETS DEPARTMENT FABDM Webinar for Debt Managers Washington, D.C. 20 th January, 2016 AGENDA 1. BASICS 2. PreTRADE
More informationEnterprise Risk Management
Enterprise Risk Management Enterprise Risk Management Understand and manage your enterprise risk to strike the optimal dynamic balance between minimizing exposures and maximizing opportunities. Today s
More informationDACT autumn diner workshop. Risk management, valuation and accounting
DACT autumn diner workshop Risk management, valuation and accounting Agenda 1. Risk management  mitigate risk Cost of hedging Risk mitigants Risk management policy 2. Valuation & accounting  mitigate
More informationPricing and calibration in local volatility models via fast quantization
Pricing and calibration in local volatility models via fast quantization Parma, 29 th January 2015. Joint work with Giorgia Callegaro and Martino Grasselli Quantization: a brief history Birth: back to
More informationOTC Derivative Portfolio Pricing Options for the BuySide
OTC Derivative Portfolio Pricing Options for the BuySide OTC Derivatives Operations in Fund Management 02Nov2011, 09:30 session Miroslav Vanous Head of EMEA OTC Valuations (A Tullett Prebon Company)
More informationEstimation of Credit Exposures. RegressionBased MonteCarlo Simulation
On the Using RegressionBased MonteCarlo Simulation UBS AG October 16, 2009 at Department of Statistics and Mathematics WU Wien Disclaimer Introduction The opinions expressed in this presentation are
More informationASSET LIABILITY MANAGEMENT Significance and Basic Methods. Dr Philip Symes. Philip Symes, 2006
1 ASSET LIABILITY MANAGEMENT Significance and Basic Methods Dr Philip Symes Introduction 2 Asset liability management (ALM) is the management of financial assets by a company to make returns. ALM is necessary
More informationLightning Fast FRTB SATB, SACVA, and SIMM using Adjoints: Can We Use Them, and What are the Benefits
Lightning Fast FRTB SATB, SACVA, and SIMM using Adjoints: Can We Use Them, and What are the Benefits Alexander Sokol Head of Quant Research, CompatibL WBS FRTB Conference, Frankfurt June 3, 2016 Alexander
More informationFacilitating OnDemand Risk and Actuarial Analysis in MATLAB. Timo Salminen, CFA, FRM Model IT
Facilitating OnDemand Risk and Actuarial Analysis in MATLAB Timo Salminen, CFA, FRM Model IT Introduction It is common that insurance companies can valuate their liabilities only quarterly Sufficient
More informationFAST SENSITIVITY COMPUTATIONS FOR MONTE CARLO VALUATION OF PENSION FUNDS
FAST SENSITIVITY COMPUTATIONS FOR MONTE CARLO VALUATION OF PENSION FUNDS MARK JOSHI AND DAVID PITT Abstract. Sensitivity analysis, or socalled stresstesting, has long been part of the actuarial contribution
More informationWHS FX options guide. Getting started with FX options. Predict the trend in currency markets or hedge your positions with FX options.
Getting started with FX options WHS FX options guide Predict the trend in currency markets or hedge your positions with FX options. Refine your trading style and your market outlook. Learn how FX options
More informationMarket Risk: FROM VALUE AT RISK TO STRESS TESTING. Agenda. Agenda (Cont.) Traditional Measures of Market Risk
Market Risk: FROM VALUE AT RISK TO STRESS TESTING Agenda The Notional Amount Approach Price Sensitivity Measure for Derivatives Weakness of the Greek Measure Define Value at Risk 1 Day to VaR to 10 Day
More informationReplicating Life Insurance Liabilities
Replicating Life Insurance Liabilities O. Khomenko Jena, 23 March 2011 1 Solvency II New Regulation for Insurance Industry Solvency II is a new regulation for European insurance industry. It is expected
More informationKI Finans Manual 1 Last update: 2015/03/10 Finance active
KI Finans Manual 1 Last update: 2015/03/10 Finance active Table of Contents Overview... 1 Getting started... 6 Create a New Fixed Rate Loan... 8 Create a New Floating Rate Loan... 9 Create a New Vanilla
More informationMANAGE RISK WITH CONFIDENCE
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> ENTERPRISE RISK Bloomberg Trading Solutions MANAGE RISK WITH CONFIDENCE >>>>> SHARPEN YOUR VIEW Managing risk is more critical than ever. And more
More informationA Practical Guide to Fair Value and Regulatory CVA. Alexander Sokol, Numerix/CompatibL PRMIA Global Risk Conference 2012, NYC
A Practical Guide to Fair Value and Regulatory CVA Alexander Sokol, Numerix/CompatibL PRMIA Global Risk Conference 2012, NYC Training Scope Introduction to CVA Rationale and challenges Fair value vs. regulatory
More informationSolving Systems of Linear Equations Using Matrices
Solving Systems of Linear Equations Using Matrices What is a Matrix? A matrix is a compact grid or array of numbers. It can be created from a system of equations and used to solve the system of equations.
More informationGCSE Revision Notes Mathematics Quadratic Formula
GCSE Revision Notes Mathematics Quadratic Formula irevise.com 2014. All revision notes have been produced by mockness ltd for irevise.com. Email: info@irevise.com Copyrighted material. All rights reserved;
More informationInternational Financial Reporting for Insurers. August 1921, Hong Kong. Session 32: Cash Flow Modeling. Simon Walpole
International Financial Reporting for Insurers August 191, 01 Hong Kong Session : Cash Flow Modeling Simon Walpole Cash Flow Modelling Insurance IFRS Seminar Hong Kong, August 0, 01 Simon Walpole Session
More informationMargin Calculation Methodology and Derivatives and Repo Valuation Methodology
Margin Calculation Methodology and Derivatives and Repo Valuation Methodology 1 Overview This document presents the valuation formulas for interest rate derivatives and repo transactions implemented in
More informationModeling VaR of Swaps. Dr Nitin Singh IIM Indore (India)
Modeling VaR of Swaps Dr Nitin Singh IIM Indore (India) nsingh@iimidr.ac.in Modeling VaR of Swaps @Risk application Palisade Corporation Overview of Presentation Swaps Interest Rate Swap Structure and
More informationIntroduction to Eris Exchange Interest Rate Swap Futures
Introduction to Eris Exchange Interest Rate Swap Futures Overview Eris Exchange interest rate swap futures ( Eris contracts ) have been designed to replicate the net cash flows associated with plainvanilla,
More informationALIGNE Credit Risk Management
ALIGNE Credit Risk Management ALIGNE CREDIT RISK EFFECTIVELY MANAGE CREDIT MONITORING, ANALYSIS AND REPORTING Counterparty credit worthiness, as well as internal credit monitoring, are becoming increasingly
More informationYou can find the Report on the SaxoTrader under the Account tab. On the SaxoWebTrader, it is located under the Account tab, on the Reports menu.
The FX Options Report What is the FX Options Report? The FX Options Report gives you a detailed analysis of your FX and FX Options positions across multiple currency pairs, enabling you to manage your
More informationBASICS OF CREDIT VALUE ADJUSTMENTS AND IMPLICATIONS FOR THE ASSESSMENT OF HEDGE EFFECTIVENESS
BASICS OF CREDIT VALUE ADJUSTMENTS AND IMPLICATIONS FOR THE ASSESSMENT OF HEDGE EFFECTIVENESS This is the third paper in an ongoing series that outlines the principles of hedge accounting under current
More informationAnalysis of GPU Parallel Computing based on Matlab
Analysis of GPU Parallel Computing based on Matlab Mingzhe Wang, Bo Wang, Qiu He, Xiuxiu Liu, Kunshuai Zhu (School of Computer and Control Engineering, University of Chinese Academy of Sciences, Huairou,
More informationThe new ACI Diploma. Unit 2 Fixed Income & Money Markets. Effective October 2014
The new ACI Diploma Unit 2 Fixed Income & Money Markets Effective October 2014 8 Rue du Mail, 75002 Paris  France T: +33 1 42975115  F: +33 1 42975116  www.aciforex.org The new ACI Diploma Objective
More informationUnderstanding Cross Currency Swaps. A Guide for Microfinance Practitioners
Understanding Cross Currency Swaps A Guide for Microfinance Practitioners Cross Currency Swaps Use: A Currency Swap is the best way to fully hedge a loan transaction as the terms can be structured to exactly
More informationRISK MANAGEMENT PRACTICES RISK FRAMEWORKS MARKET RISK OPERATIONAL RISK CREDIT RISK LIQUIDITY RISK, ALM & FTP
T H E P RO F E SS I O N A L R I S K M A N AG E R ( P R M ) D E S I G N AT I O N P RO G R A M PRM TM SELF STUDY GUIDE EXAM III RISK MANAGEMENT PRACTICES RISK FRAMEWORKS MARKET RISK OPERATIONAL RISK CREDIT
More informationProgram for Energy Trading, Derivatives and Risk Management by Kyos Energy Consulting, dr Cyriel de Jong Case studies
Program for Energy Trading, Derivatives and Risk Management by Kyos Energy Consulting, dr Cyriel de Jong Case studies We use cases throughout its course in various forms. The cases support the application
More informationHedging Variable Annuity Guarantees
p. 1/4 Hedging Variable Annuity Guarantees Actuarial Society of Hong Kong Hong Kong, July 30 Phelim P Boyle Wilfrid Laurier University Thanks to Yan Liu and Adam Kolkiewicz for useful discussions. p. 2/4
More informationFixed Income Portfolio Management. Interest rate sensitivity, duration, and convexity
Fixed Income ortfolio Management Interest rate sensitivity, duration, and convexity assive bond portfolio management Active bond portfolio management Interest rate swaps 1 Interest rate sensitivity, duration,
More informationCounterparty Credit Risk Measurement Under Basel II. A presentation by ISDA Asia 2007
Counterparty Credit Risk Measurement Under Basel II A presentation by ISDA Asia 2007 1 Outline 1 Definition of counterparty credit risk (CCR) 2 Basel I treatment 3 Basel II treatment : Regulatory approved
More informationRevoScaleR Speed and Scalability
EXECUTIVE WHITE PAPER RevoScaleR Speed and Scalability By Lee Edlefsen Ph.D., Chief Scientist, Revolution Analytics Abstract RevoScaleR, the Big Data predictive analytics library included with Revolution
More informationCase Study. Implementing IAS 39 with Fairmat
Case Study Implementing IAS 39 with Fairmat Revision #3 In this tutorial we will show how international accounting standard 39 principles, which regulate how financial instruments must be accounted for
More informationFrom CFD to computational finance (and back again?)
computational finance p. 1/17 From CFD to computational finance (and back again?) Mike Giles mike.giles@maths.ox.ac.uk Oxford University Mathematical Institute OxfordMan Institute of Quantitative Finance
More informationNEW DIRECTION FOR MARKET RISK: ISSUES AND CHALLENGES
NEW DIRECTION FOR MARKET RISK: ISSUES AND CHALLENGES 3 rd Annual RISK AMERICAS, May 1213, Marriott Downtown, New York City Presenter: Anshuman Prasad, Director, Risk and Analytics May 1213, 2014 Agenda
More informationRegulations for Calculating the Fund s Global Exposure and Risk Exposure to a Counterparty
K U N G U I E L Ā 1 LV 1 0 5 0 R Ī G Ā T Ā L R U N I S + 3 7 1 6 7 7 7 4 8 0 0 F A K S S + 3 7 1 6 7 2 2 5 7 5 5 (Unofficial translation) Riga, 11 November 2011 Regulations No. 242 (Minutes No. 43 of
More informationSpreadSheet Inside. Xenomorph White Paper. Spreadsheet flexibility, database consistency
SpreadSheet Inside Spreadsheet flexibility, database consistency This paper illustrates how the TimeScape SpreadSheet Inside can bring unstructured spreadsheet data and complex calculations within a centralised
More informationKondor+ 3.3 What s New Enterprise trade and risk management for the new world of finance
Enterprise trade and risk management for the new world of finance SERVICE GATEWAY BUSINESS PROCESS CATALOGUE ASSET CLASS BUNDLES INDIVIDUAL ASSET CLASSES FINANCIAL REPORTS CASH FLOW REPORTS KONDOR UX NEW
More informationRisk Based Capital Guidelines; Market Risk. The Bank of New York Mellon Corporation Market Risk Disclosures. As of December 31, 2013
Risk Based Capital Guidelines; Market Risk The Bank of New York Mellon Corporation Market Risk Disclosures As of December 31, 2013 1 Basel II.5 Market Risk Annual Disclosure Introduction Since January
More informationModeling Counterparty Credit Exposure
Modeling Counterparty Credit Exposure Michael Pykhtin Federal Reserve Board PRMIA Global Risk Seminar Counterparty Credit Risk New York, NY May 14, 2012 The opinions expressed here are my own, and do not
More informationApplications to Computational Financial and GPU Computing. May 16th. Dr. Daniel Egloff +41 44 520 01 17 +41 79 430 03 61
F# Applications to Computational Financial and GPU Computing May 16th Dr. Daniel Egloff +41 44 520 01 17 +41 79 430 03 61 Today! Why care about F#? Just another fashion?! Three success stories! How Alea.cuBase
More information