Unified financial analysis the missing links of finance (the wiley finance series)

P1: JYS fm JWBK356-Brammertz February 6, 2009 20:16 Printer: Yet to come Unified Financial Analysis i P1: JYS fm JWBK356-Brammertz February 6, 2009 20:16 Printer: Yet to come For other titles in the Wiley Finance Series please see www.wiley.com/finance ii P1: JYS fm JWBK356-Brammertz February 6, 2009 20:16 Printer: Yet to come Unified Financial Analysis The Missing Links of Finance W Brammertz, I Akkizidis, W Breymann, ă R Entin and M Rustmann iii P1: JYS fm JWBK356-Brammertz C February 6, 2009 20:16 Printer: Yet to come 2009 John Wiley & Sons Ltd Registered office John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com The right of the author to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act 1988 All rights reserved No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher Wiley also publishes its books in a variety of electronic formats Some content that appears in print may not be available in electronic books Designations used by companies to distinguish their products are often claimed as trademarks All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners The publisher is not associated with any product or vendor mentioned in this book This publication is designed to provide accurate and authoritative information in regard to the subject matter covered It is sold on the understanding that the publisher is not engaged in rendering professional services If professional advice or other expert assistance is required, the services of a competent professional should be sought Library of Congress Cataloging-in-Publication Data A catalogue record for this book is available from the Library of Congress A catalogue record for this book is available from the British Library ISBN 978-0-470-69715-3 Set in 10/12pt Times by Aptara Inc., New Delhi, India Printed in Great Britain by Antony Rowe Ltd, Chippenham, Wiltshire iv P1: JYS fm JWBK356-Brammertz February 6, 2009 20:16 Printer: Yet to come Contents List of Figures xv List of Tables xix Acknowledgments xxi Preface PART I xxiii INTRODUCTION 1 The Evolution of Financial Analysis 1.1 Bookkeeping 1.2 Modern finance 1.3 Departments, silos and analysis 1.4 The IT system landscape 1.5 New approach 1.6 Hazards of a single solution 3 10 11 15 17 Finding the Elements 2.1 The notion of elements 2.1.1 Elements and science 2.1.2 Analyzing analysis 2.2 Elements of financial analysis 2.2.1 Liquidity 2.2.2 Value and income 2.2.3 Risk and sensitivity analysis 2.3 Input elements 2.4 Financial events and expected cash flows 2.5 Risk factors and risk categories 2.6 The time dimension 2.6.1 Time and the calendar time 2.6.2 The role of intervals 2.6.3 Double existence of time 19 19 19 21 21 22 22 23 25 26 29 31 31 32 32 v P1: JYS fm JWBK356-Brammertz vi February 6, 2009 20:16 Printer: Yet to come Contents 2.7 Classification of analysis 2.7.1 Liquidation and going-concern view 2.7.2 Analysis types 2.8 Nonfinancial cash flows 2.9 The methodology as an image PART II INPUT ELEMENTS 33 33 35 37 39 41 Financial Contracts 3.1 Modeling of financial contracts 3.2 Standard contract types 3.3 Rules and mechanisms of standard contracts 3.3.1 Principal amortization patterns 3.3.2 Principal draw-down patterns (step-up) 3.3.3 Interest payment patterns 3.3.4 Fixed/variable (rate adjustments) 3.3.5 FX rates 3.3.6 Stock patterns 3.3.7 Commodity patterns 3.3.8 Plain vanilla option patterns 3.3.9 Exotic option patterns 3.3.10 Credit risk 3.3.11 Behavioral patterns 3.4 Examples 3.4.1 Principal at maturity (PAM) 3.4.2 Annuities (ANN) 3.4.3 Regular amortizer (RGM) 3.4.4 Interest rate swap (IRSWP) 3.4.5 Forward rate agreement (FRA) 3.4.6 Bond and interest rate options (IROPT) 3.5 Nonstandard contract types 3.5.1 Input elements and events 3.5.2 Analysis elements Appendix: Practical considerations 3.A.1 Mapping process 3.A.2 Data quality 43 43 46 51 51 53 54 55 57 57 58 58 59 60 61 62 62 63 64 65 66 67 68 69 70 70 71 71 Market Risk Factors 4.1 Expectations 4.1.1 Economic expectations 4.1.2 Arbitrage-free markets and risk-neutral valuation 4.1.3 Absence of arbitrage and economic expectation 4.1.4 Linear and nonlinear effects 4.2 Static modeling 4.2.1 Interest rates 4.2.2 Stocks, exchange rates and commodities 4.2.3 Spreads as risk factors 73 74 74 75 79 80 81 81 84 85 P1: JYS fm JWBK356-Brammertz February 6, 2009 20:16 Printer: Yet to come Contents vii 4.3 Stochastic market models: the arbitrage-free world 4.3.1 Stock price models 4.3.2 Beyond geometric Brownian motion 4.3.3 Interest rates: general considerations 4.3.4 Short rate models 4.3.5 Forward rate models 4.4 Stochastic market models: the real world 4.4.1 Economic scenario generation 4.4.2 Modeling individual products: stocks and commodities 4.4.3 Product rates 4.5 Alternative valuation techniques 4.5.1 Arbitrage-free and complete markets 4.5.2 Arbitrage-free incomplete markets 4.5.3 Discounting with deflators 4.5.4 Arbitrage opportunities and deflators Further reading 87 87 90 91 92 93 96 97 98 100 101 102 103 105 107 108 Counterparty 5.1 Exposure, rating and probabilities of default 5.2 Data determining gross exposure 5.2.1 Counterparty descriptive data 5.2.2 Counterparty hierarchies and group structures 5.2.3 Counterparty and financial contracts 5.3 Credit enhancements 5.3.1 Credit enhancements and financial contracts 5.3.2 Guarantees 5.3.3 Credit derivatives 5.3.4 Collaterals 5.3.5 Close-out netting agreement 5.3.6 Double default 5.4 Credit line and limits 5.4.1 Credit lines 5.4.2 Credit line exposure 5.4.3 Credit limits 5.5 Credit ratings 5.5.1 Measurement of credit rating 5.5.2 Classifying credit ratings 5.5.3 Ratings classes and exposures 5.5.4 Rating techniques Further reading 111 111 113 113 114 115 115 116 118 120 124 125 126 127 127 128 130 131 131 132 132 134 134 Behavior 6.1 Risk sources and behavior 6.2 Market-related behavior 6.2.1 Replication 6.2.2 Prepayment 135 136 138 138 143 P1: JYS c19 JWBK356-Brammertz February 10, 2009 19:45 Printer: Yet to come Towards a Unified Financial Language 419 we need to bring up the point here once more The system does not only define the data input and output but also the algorithm that connects the two via the financial events The centers of the algorithms are the contract types The algorithms know the rules of the contract and how they connect to the other factors discussed next and how to generate the financial events It is the same problem discussed in Section 1.5 19.2.2 Risk factors Risk factor information – especially market risk factors – are already standardized to a great extent today since there are only a very few serious vendors out there, such as Reuters or Bloomberg Risk factors are also more standardized because all banks and insurance companies, academia and even private investors rely on the same or at least very similar concepts Naming conventions are well developed This is unlike the contract world, where every bank tries to distinguish itself through new products and where the same products are sold under many different names just for competition sake 19.2.3 Counterparty information Collateral, guarantees and close-out nettings are financial contracts and therefore subsumed under the subsection above In this section only direct counterparty information is discussed Counterparty systems are like contracts, very specific to every institution Despite this, heterogeneity is much less a problem It has been argued in Chapter that the problem with contracts is the mapping of different logic The differences between different counterparty systems is however much simpler since it is more a difference in convention, such as the description of dates, the naming of the fields, etc There is an agreement concerning the core description of counterparties with name, address and unique ID A unique ID in this system would need to be a globally unique ID, a problem we are discussing later on On top of this minimum information there is widespread agreement concerning credit riskrelated auxiliary information Generally there are a dozen or two dozen significant information attributes such as profit, balance sheet size, etc., which are necessary for the estimation of probability of default We think it would be possible to set up a board where rating agency specialists could define the minimum standard Besides this minimum set, each financial actor could add his own fields Financial actors thinking that there are additional significant fields not defined in the minimum set could propose these fields to become standard, which would also guarantee an optimal evolution of the information Despite its technical feasibility concerning counterparty information, resistance to this concept could come from another corner The internationally unique counterparty ID, which is an important part of such a unified system, is especially problematic – it has a seed of big brother watching us The unique ID is not a problem within a single bank but in an international setting, combined with centralized regulation, it takes another dimension A unique ID would allow the regulator to see all transactions of a counterparty and – as experience has shown – it would be not only the regulator that sees this These are serious concerns The system could only work if regulation was to be efficiently regulated itself by a meta regulation The meta regulation would define the rules on how and under which conditions information could be used P1: JYS c19 JWBK356-Brammertz 420 February 10, 2009 19:45 Printer: Yet to come Unified Financial Analysis This is a crucial junction Do we want to know or don’t we want to know Technically speaking it is possible to describe a working system But we want it? Can we make it safe enough? On the other hand, there is need for information How can the central bodies be responsible for the financial sector to the point where they have to bail banks out if they have no clue what is in them? It might boil down to the question of what is worse: bad banks or regulators Who is likely to abuse the system more and at what cost? Is it possible to regulate regulators and how would the meta regulators be regulated? These are questions we can only raise but not answer in this book 19.2.4 Behavior parameters Behavior information – due to its necessarily open structure – is the most difficult part of the puzzle For contracts, risk factors and counterparty information there is a sound technical solution For behavior there are only basic approaches Within behavior it is possible to define any function following any functional form that makes it difficult to standardize A strict standardization would probably deteriorate the quality of internal control The only possibility we see at this point in time is to focus on the most important behavioral parameters For these parameters standard approaches could be defined without discouraging alternative internal approaches Regulation should rely mainly on the internal approach for the capital charge calculation However, for the sake of communication between different financial actors, it would be necessary to have a strictly defined approach known to all actors that is the basis for understanding the instrument The following four items should be standardized: Nonmaturity contracts Nonmaturity contracts are replicated with standard contract types which allows an easy and strict standardization The board should define the mix of contracts to be used for replication A steady research should define the mix to reflect continuously the new risk position implied in such products Prepayment Although there are many ways to express prepayment, there are very few commonly applied ones The main method is by defining the prepayment speed by a matrix having one, two and sometimes more dimensions A board could define the standards and a steady research would guarantee the continued appropriateness of the applied assumptions Mortality/longevity tables Such tables already exist officially A board should just define the actual applicable tables that can be used Migration matrices Migration matrices have already quite a strict format which can be followed generally The numbers within the matrix could again be set, updated and supervised by an official board A strict separation of probability of default, collateral and recovery rates should be adhered to It is possible that in a specific case the board would define more than one answer For example, there could be two or three versions of a mortality/longevity table that are based on different assumptions for one and the same person In this case it is necessary to pass this additional information to potential buyers who could then accept the assumptions or make their own judgment At any rate, the assumptions must be clear The four behavior elements are also the most relevant and important items in terms of effects on risk and return This combined with the fact that standardization is relatively easily reached makes it likely that there can be an agreement and the most relevant factors can be captured in P1: JYS c19 JWBK356-Brammertz February 10, 2009 19:45 Printer: Yet to come Towards a Unified Financial Language 421 a structured way Similar to the other input factors, the concepts should be gradually improved and the parameters continually monitored Overall it remains the most difficult part of the system 19.2.5 Contract level information and aggregation Assuming, just for the time being, that it is possible to agree on standards on the four input elements with the corresponding algorithms, the detail level has yet to be discussed In order to overcome the information deficit once and for all, the single contract level is the only choice Coming back to the structured finance problem shown in Figure 19.2, the information on the single mortgage on the left side, including counterparty and collateral information, should remain available throughout the whole chain independent of its length This is a lot of information, which even under modern information technology will be challenging, at least in the near future Although we believe it to be technologically possible even today, a cost–benefit argument here is possible If this argument is valid, aggregation as described in the appendix in Chapter 13 could be applied At the origin, aggregation should not be allowed at all However, as the chain becomes very long, some aggregation could be allowed using predefined or at least controlled mechanisms This means, however, that aggregation would also be part of the regulatory affair Regulation would have to define rules concerning aggregation – under which conditions which methods are to be allowed Technology is progressing fast What is difficult today will be easy, possible and affordable tomorrow Aggregation rules might be a temporary device to overcome technical bottlenecks Once the bottleneck is overcome, aggregation could be reduced or eliminated 19.3 NEW FINANCE, NEW REGULATION The regulatory burden is surely to increase if measured in terms of information that must pass from financial institutions to regulators Whether the burden is going to increase in terms of money and effort depends on the chosen solution If the market continues to follow the old style regulation of today, where each regulatory request triggers new projects inside each bank lasting for many man years, the cost is going to increase drastically and might lead to a collapse of the system in the end Given the proposed solution, however, regulation could become an opportunity, since it would trigger a common unified financial language to be understood by any actor This language would allow not only the communication between the actors and between the actors and the regulatory bodies but even increase internal financial understanding Given that the data and the algorithms exist, regulators could apply their tests themselves Regulators could apply new tests as the need comes up without asking for any new information from the banks or insurance companies Not only could single banks be tested but the entire financial sector as a whole! We have seen above that the system would have an inbuilt mechanism to adapt itself to new realities in a natural way Only in rare cases would the regulator have to ask for additional information such as breakout criteria for additional groupings The cost of regulation could be reduced drastically in the long run – and the quality improved There are only a few occasions where more quality can be had for a lower price; this is one On the side of banks and insurances the new concept would lead to initial investments with limited associated cost This cost would be counterbalanced first by reducing internal cost P1: JYS c19 JWBK356-Brammertz 422 February 10, 2009 19:45 Printer: Yet to come Unified Financial Analysis by creating a common language between risk management, treasury and even bookkeeping or actuaries and investment officers The continued reinvention of the wheel – algorithms to generate cash flows – could be replaced by a staple commodity almost freeware code The crucial benefit, however, will be the change in focus from solving data problems to making better decisions Instead of fighting with information the original task of managers – making decisions on the best possible information available – would become a reality P1: JYS ind JWBK356-Brammertz February 6, 2009 19:55 Printer: Yet to come Index Note: Page references in italics refer to Figures and Tables 30/360 day count method 3–6–3 rule absence of arbitrage 75–6, 79–80, 101–3, 107 accrual accounts 316 accrual method in FTP 213–15 accrued interest 4, 176–7, 192, 192, 201, 209, 273, 382 acid ratio 402 activity-based costing 38, 159, 161–65, 161 additivity 154 adjusted net asset value (ANAV) 351 advanced measurement approach, statistical basis 280–85 aggregation 305–8 cash flow 306 contract 307–9 ALM see asset and liability management American options 58 amortized cost 198–99 analysis analysis of 21 classification of 33–7 types 35–7 analysis elements 70–2, 383–7 in life insurance 343–344 in non-life insurance 353–54 animal spirit 75, 394, 411 ANN see annuities annuities (ANN) 63–4, 138, 144, 147, 184, 184, 320 with constant maturity 51–2 with constant payment 52 fixed classical 64, 64 variable 64, 64 annuity choice 61 annuity conversion 137, 150–51, 351 arbitrage opportunities and deflators 107–8 arbitrage, absence of, and economic expectations 74–5 arbitrage-free and complete markets 102–3 arbitrage-free incomplete markets 103–5 arbitrage-free markets 75–79 Asian options 59 aspect of yield curves 23 asset and liability management (ALM) 6, 7, 10 asset-or-nothing call 59 asymmetric book valuation method 66 at-the-money options 79 attribute level transformation 71 audience 377 auditing 271 average price options 59 average strike options 59 backtesting 263–71 market risk 264–66 of migration 267 backwardation 87 balance 13 balance sheet 43, 195–97 structure 378–80 balancing 303–7 dynamic 301–4 static 304–5 bankruptcy of SPV 123 banks 309–33 Barings Securities 30 Basel II regulations 5, 132, 229, 264 behavior 31, 133–53, 272, 299–301 credit risk 151–154 expected 36 in life insurance 345 market related 136–46 market risk 135 operational risk 135 423 P1: JYS ind JWBK356-Brammertz 424 February 6, 2009 19:55 Printer: Yet to come Index behavior (Continued) parameters 420–22 risk sources and 134–6 behavioral effects, sequence of 154–5 behavioral elements 25 behavioral events 185–8 in credit risk 187 prepayments 186 behavioral patterns 61–2 behavioral sensitivities 226–31 behavioral shifts 320–22 Bermudan options 58 binary options 59 binomial models 89, 89 binomial trees 89 Black–Scholes model 85, 103–4, 109 Black–Scholes–Merton differential equation bond issues 312–13 bonds 22, 67–8, 67 bonus calculation 345 book value 142 bookkeeping 3–7, 10–11 double entry 3, 9, 22 today 8–10 Bretton Woods system BS see balance sheet structure budgeting 10 bullet 51 choice 62 business disruption 285 calendar time 31–2 call money 53 call option 58 callable bonds 46 CAP curve 268 capital 408–9 available 407 economic 406–7 capital adequacy (CAD) reports 14, 14 capital asset pricing model (CAPM) 48, 57, 78, 98 capital charges for different ratings and concentrations 249, 250 capitalization 55 patterns 206 CAPM see capital asset pricing model capped mortgages 46 cash 371–3 management 186 cash flow 5–6, non-financial 377–79 statement super 15 cash-or-nothing call 59 cash reserve payout pattern 357, 357 certainty equivalent value of liabilities 350 cessation of premium payments 148 chart of accounts 309–11 for life insurance 335–7 for non-life insurance 353–5 claims for non-life insurance 362–3, 368 patterns of 356–8 classical controlling 10 classical fixed bond 63, 63 close-out netting 60, 123–5, 124 collateral 61, 122–3, 151, 229, 255–8 financial 124 haircut 229–30 physical 124 collateralized bond obligation (CBO) 122 collateralized debt obligations (CDO) 121–4, 122, 170 collateralized exposure 111, 129, 259 collateralized loan obligation (CLO) 122 collateralized mortgage obligation (CMO) 122 combination of risks 369 commodities 48–9 modelling 100 patterns 58 completeness 310 compound options 60 compounding 55 consistency 411–12 constant principal payment 52 contango 84 contract aggregation 307–8 contract level and performance 305–6 contract type 44 mapping 72–3 contracts 25, 35–6, 43–74 characteristics 296–7 compound 49–50 construction of non-standard 69–70 credit-related 49 examples 62–8 fixed income maturity 46–8 fixed income non-maturity 48 grouping criteria 160–61, 161 for life insurance 49, 337–44 modeling 43–6 new production 294–99, 297 for nonlife insurance 49, 355–9 in the nonfinancial world 373–4 nonmaturity 61 nonstandard 68–72 pricing 299–300 for reinsurance 359–60 standard 46–51 in unified financial language 418–9 variety 45 with drawing patterns 56 P1: JYS ind JWBK356-Brammertz February 6, 2009 19:55 Printer: Yet to come Index contribution margin (CM) 159–60, 160 CM I 159,160, 162 CM II 159, 163, 164 controlling 10 convenience yield 84 convexity 178, 185, 221, 223, 234–5, 273, 328, 328 corporate valuation, practical example 396 correlations between risks 252 between defaulters 150 market conditions 150 of sub-items of life risk 252 cost 274, 302–3 amortized 198–9 direct 157 historical 22 indirect 157 variable 168, 170 see also costs cost accounting 157–64 activity based 161–2 standard 159–61 cost object 159 cost of capital (CoC) 351 cost-of-carry model 84 costs 157–73 allocation to financial contracts 162–7 allocation, examples 165–7 categories 171 contracts and counterparties 162–4 life insurance 340–1, 348 acquisition 340–1 funds management 340 risk 340 saving 340 servicing 340 in different temporal modes 169–70 as a financial event 167–9 fixed and variable 158–9 integration into general framework 167–71 in non-life insurance 366 patterns 164–5 risk and 170–1 counterbalancing 142, 322 capacity 323–4, 324 counterparty 25, 109–32, 299–300, 320–2 credit exposure 237, 237 data 272 descriptive data 113–14 and financial contracts 113, 113 as guarantor 116 hierarchies and group structures 112–14, 112 risk 30 in unified financial language 419–20 coupon rates 85 425 Cox, Ingersol and Ross (CIR) model 92 credit default sensitivities 226–30 credit default swap 118–9, 119 credit derivatives 51, 118–22 collateralized debt obligations (CDO) 121–4, 124, credit default swap 120–1, 121 credit enhancements 111, 115–27 asset based 124 collaterals 124–5 counterparty based 117 and financial contracts 116–18 main types 117, 117 credit exposure 11, 113–4, 120, 126, 129, 130, 227, 229, 236–7, 280, 370 covering 111 report 239 credit facility 128, 146 credit limits 130 credit line exposure 128–30, 129 credit lines 54, 61, 127–8, 128, 153–4 drawing 137, 263 exposure 128–30, 129 credit loss 136 credit margin 213 credit ratings 131–4 classification 132, 133 classification for Basel II 132 measurement of 131–2 rating techniques 134 ratings classes and exposures 132–3 credit-related contracts 49 credit related impairments204 credit risk 4, 11, 29, 60–1, 88, 256–60, 263, 384 behavior 135, 149–52 rating backtesting 266–9 CreditMetrics 246, 254 CreditRisk+ 246–50, 255 loss distribution 248, 248 cross currency swaps 50 cross-overs 138 current accounts 313–14 current principal 13 data mapping 71 missing 71 reduction 274–6 wrong 71–2 data determining gross exposure 113–15 data entry 285, 304 data quality 71–2, 305 data warehouses 12, 13 limitations 12–15 debt to equity ratio 404 decision support 273 P1: JYS ind JWBK356-Brammertz 426 February 6, 2009 19:55 Printer: Yet to come Index default remoteness of SPV 122n defaulters, correlation with 150 degree of dependency 114 degree of limits 130 departmentalism 9–10 deposits 313–4 direct costs 157 disability 251 discount paper 62 discounting with deflators 105–7 disruption, business 285 distribution of NPV 330 dollar convexity 235 duration 234–5 double-barrier option 60 double default 126–7 double default credit risk 127 double existence of time 32–3 draw-down 146–8 amount 147 dates 147 drawing 137 patterns 61 drawn at default 128 duration 234–5 dynamic analysis 33, 34, 82, 384–6 importance of 289 new contract production 289–90, 290 dynamic balancing 301–4 dynamic FTP margins 332 dynamic FTP reports 331, 331 dynamic market 36 dynamic market models 89 dynamic stimulation 46, 290 EAD see exposure at default earnings at risk (EaR) 24, 29, 258 earnings before income tax (EBIT) 402 earnings before interest , taxes, depreciation and amortization (EBITDA) 385 earnings before interest and taxes (EBIT) 385 economic expectations 76–7, 80–1 economic risk capital 403 economic risk reports 405–8 economic scenario generation 97 economic scenario generator 105 economic scenarios 97–98 based on historical models 97 based on Monte-Carlo scenarios 97 based on what-if scenarios 97 economic value added 404 economic value in life insurance 349–1 effective yield 22 EI see exposure indicator, for operational risk elements of financial analysis 21–4 elements, notion of 19–21 analyzing analysis 21 science and 19–21 employment practices 285 endowment 345 endowment period 148 equity note tranches 121 equity ratios European economic value 351 European options 58 EVA see economic value added event based analysis 15–16, 16 event generation 291 event types 285 evolution of financial analysis 3–17 income ex-ante hedge testing using what-if simulation 209, 209 with a correlation coefficient 209, 210 exchange rates 84–5 execution, delivery and process management 285 exotic options 51 patterns 59–60 expectations 76–83 expected behavior 36 expected cash flows 26–9 mortality 147 expected defaults in Solvency II 249, 249 expected liquidity cash flows 28 expected loss (EL) 62, 111 expected market 36 expected shortfall 259–60 expense 405–6 exposure 11, 280 adjust 229 at maturity 228, 228 collateralized 109, 127, 257 credit 236–7 FX 235 gross 109–11, 126, 128, 227, 257 net 110, 246 outrights 50 potential 228, 229 rates 57, 294 remaining 109 swap 228 total 249 uncollateralized 109 exposure at default (EAD) 110, 226–7, 256, 267 potential 227–29 exposure indicator, for operational risk 279 External Credit Assessment Institutions (ECAIs) 130 external fraud 285 extreme dependency 98 P1: JYS ind JWBK356-Brammertz February 6, 2009 19:55 Printer: Yet to come Index facilities see credit lines facility use 128 fair value 22, 105 fair value valuation 200 FASB 5, fee 144, 147 filtered historical simulation 98 financial analysis 21 financial contracts see contracts financial corporates 371–6 financial elements 19–39 financial events 26–9, 176 examples 180–5 on fixed rate instruments 178–80 on forward rate agreements 183 liquidity and 175–90 processing 175–8 on swaps contracts 182 on variable ANN contracts 181 on variable PAM contracts 181 on variable rate instruments 180–2 financial laboratory 401–22 financial language 413–22 finding the elements 19–39 fixed income maturity 48 nonmaturity 46–8 fixed rate bond 26 fixed rate instruments 178–80 fixed/variable conditions 55–7 fixing days 55 forecast reporting 326 forward rate agreement (FRA) 26, 66–7, 67, 183 forward rate models 93–6 forward rates 85 forwards 50 FRA see forward rate agreements frequency and severity distribution, for operational risk 284 FTP see Funds Transfer Pricing Funds Transfer Pricing (FTP) 6, 157, 191, 210–8, 330–2 accrual method 213–15 boni/mali 213 credit margin 213 dynamic margins 534 income 331–2 income split 214, 214, 332 institution specific margin 213 liquidity margin 213 for nonmaturity contracts 216–8 NPV method 215–16 profit center 217 reports 14, 14 Treasury 217 427 Treasury margin 213 value split 215 futures 50, 66–7 gap analysis 5, gap results 325 GARCH filter 98 generally accepted accounting principles (GAAPs) 195 geometric Brownian motion 78, 80, 89, 90–1, 90, 103 going concern valuation 387–9 going-concern view 33–5, 35 goods 371–3 government 375–6 granularity 273–4 gross domestic product (GDP) 375–6 gross exposure 109–11, 126, 128, 227, 257 grouping and summing hypothesis 14 growth optimal po45 guarantees 61, 116–8, 117 guarantor 116 Heath–Jarrow–Morton (HJM) model 76, 95–6 hedge accounting 208, 208 de-designation 208 designation 208 Heston model 91 hierarchical level 112 historic valuation 199, 200 historical cost 22 historical models 97 historical simulation 253 historization 271–5 HJM see Heath-Jarrow-Morton models Hull–White model 93 IBNR see Incurred But Not Reported claims IFRS 32, 39 207–10 immediacy 157 in-the-money options 79 income 22, 28, 71, 192–4, 273, 405–6 based on constant effective yield valuation1 199, 199 based on linear write off valuation 202, 202 based on lower of cost or market valuation 202–3, 203 based on minimal value valuation 203, 204 based on MtM valuation 201, 201 based on nominal value 197, 197 dynamic simulation 325–30 elements 301 interest 327 in non-life insurance 365–6 Incurred But Not Reported claims (IBNRs) 362–3 indirect costs 157 P1: JYS ind JWBK356-Brammertz 428 February 6, 2009 19:55 Printer: Yet to come Index industries modeling 375 inhomogeneous models 94 input elements 25–6, 26, 39 insurance-related behavior 146–9 insurance risk 25, 30, 135, 250–1, 258, 261 integrated approach 15–16 interest payment patterns 54–5 interest rate 93–4 risk 5, 241–2, 242 risk limits 238, 238 sensitivities 221–5, 384 interest rate adjustment 145 interest rate gap limit 239, 239 interest rate models constraints 89 dynamic 89 interest rate swap (IRSWP) 50, 65–6 interest rate options (IROPT) 67–8, 67 interest sensitivity gaps 231–4 marginal 232 interfacing transactions 12–13, 13 internal fraud 285 intervals 32 intraday 274–5 invalidity 135, 146–7 invalidity shifting 147 invalidity tables 146 investment horizon 7, 83 IROPT see interest rate options IRSWP see interest rate swaps IT systems 11–15 jump-diffusion models 91 key performance indicators (KPI)s 344 key rate duration 234–5 key risk exposure indicators (KREIs) 283 key risk indicators (KRIs) 283 Keynes, John Maynard 77, 81 knock-in options 59 knock-out options 59 lapse 62, 135, 147–8, 251 Leeson, Nick 30 lemon problem, exemplifying 414–16 LGD see loss given default LGE see loss given event, for operational risk Libor market 76 Libor market model (LMM) 36, 93, 95–6, 293 life annuity 344 life insurance 25, 335–51 analysis elements 347–51 balance sheet and P&L forecast 348–9 balancing 346–7 behavior 345–6 characteristics 344–5 contracts 49 cost 338–9, 346 economic value 349–51 liquidity 346–7 pricing 344–5 retirement benefit 343–4 survival 343–4 volume 343–4 limit 54, 237–9, 331–3 setting process 237–8 linear effects 82–3, 83 linear write off valuation 202, 202 lines of business 376 liquidation view 33–5, 34 liquidity 4, 22, 28, 71, 175–90, 273, 321–5 inter-bank and equity 316–8 in life insurance 346–7 in reinsurance 363–4 risk methods 273 liquidity analysis 82 liquidity at risk (LaR) 24, 29, 71 liquidity gap 6, 186–90 cumulative gap 187–9, 188 including credit defaults 189, 189 including credit risk losses 189 including credit risk recoveries 189 marginal gap 187–8, 187, 188 residual gap 189 liquidity margin 213 liquidity oriented analysis 27 liquidity preference, theory of (Keynes) 81 liquidity reports 186–90 liquidity risk 4, 30–1, 258–9 back testing 269–71 LMM see Libor market model loans 312–13 lognormal forward swap model (LSM) 95 longevity 137, 146–7, 251 longevity tables 420 loss distribution in CreditRisk+ 248, 248 for operational risk 281–2 loss given default (LGD) 110–11, 246, 249 loss given event, for operational risk 280–1 lower of cost or market valuation 66, 202–3, 203 management interest rate risk, duration mapping of contract types 72–3 of data 73 process 72–3 mark-to-market valuation 191, 200–1, 201 market 380 dynamic 36 expectations 76–83 P1: JYS ind JWBK356-Brammertz February 6, 2009 19:55 Printer: Yet to come Index expected 36 shocked 36 market conditions 293–4 correlation with 150 market data 75–6, 272 market forecast 318–20 market liquidity risk 88 market-related behavior 136–46 market risk (MR) 5, 11, 24, 25, 29, 135, 244–6, 253–5, 261 market risk factors 75–110 expectations 76–83 static modelling 83–9 market sensitivities 225–6 market value 142 of assets 3520 matched repricing 319 maximal draw-down 145 mean for operational risk 284 mean reversion 93 meta model 376, 380 migration 135, 149–51 migration matrices 135, 149–50, 254, 255 shocks 261 migration probabilities 256, 257 minimal value valuation 203, 204 minimum value principle 28 modelling commodities 100 industries 375 stocks 98–100 modern finance 8–10 Monte-Carlo simulations 11, 24, 71, 99, 293 full 253–4 Delta-Gamma 254 paths generated with Ornstein Uhlenbeck 329 mortality 62, 137, 146–7, 251 classes 146 sensitivity 230–1 shifting 147 tables 146 transition matrix 146 mortgage-backed securities (MBS) 185 mortgages 25, 312–13 MSCI World 107–8 MtM see mark-to-market valuation multicurrency 204–5 multiplicity 152–3, 152 multiplier 56 natural time 7, 7, 33, 33, 291 negative amortizers 52 net exposure 110 net interest income simulation (NII) net present value (NPV) 5, 14, 191 in FTP 215–16 new volume 296 no-arbitrage 91 nominal value (NV) 13, 22, 116, 141, 197 nonamortizing contract 320 nonfinancial cash flows 37–9 nonfinancial corporates 371–6 nonfinancial model 376–83 nonfinancials 369–96 nonlife insurance 353–68 analysis elements 364–8 characteristics 361–2 claims and IBNR 362–3 contracts 49 forecasting new business 361–3 premium written 361–2 pricing 361–2 nonlinear effects 80–1, 80 nonmaturity contracts 46–8, 61, 420 in FTP 216–18 nonoperating financial assets 390–1 nonoperating free cash flows 391–2 nonrational behavior 133 nonrisk ratios 401–3 nonstandard contract types 68–72 construction 69–70, 70 nonsubadditivity 243 notional value 13 NPV see net present value numerical VaR methods 253–59 NV see nominal value OAS see option adjusted spreads obligor 116 OBS see off-balance sheet structure off-balance sheet structure 378–80 operational considerations 206–7 operational risk (OR) 11, 30, 38, 135, 277–90 advanced measurement approach (AMA) 280–1 basic indicator 280–1 output 286 optimal resource allocation 279–80, 280 standardized approach 280–1 operational value at risk (VaR) 287–88 dynamic 286–88 static 285–6 optimization 408–11 dynamic 410–11 static 408–10 option adjusted spread (OAS) 185 options 50–1 Asian 59 binary 59 compound 60 exotic 51, 59–60 plain vanilla 51 429 P1: JYS ind JWBK356-Brammertz 430 February 6, 2009 19:55 Printer: Yet to come Index options (Continued) rainbow 60 single-barrier 59–60 ordering 144 originator 120 Ornstein–Uhlenbeck model 100 out-of-the-money options 79 over-the-counter credit swap transaction 120 profit and loss structure 378–80 profit centers and FTP 210, 211 deal-making 217 protection buyer 120–121 protection seller 120–121 put option 58 puttable loans 46 quick ratio 402 PAM see principal at maturity par rate 56, 83, 320 parallel histories 275 patterns interest payments 54–5 principal draw-down53–4, 53 payback fee 144 payback rule 144 payback value 144, 150 PD see probability of default PE see probability of loss event, for operational risk performance measurements 401–5 perpetual bonds 53 physical assets, damage to 285 pictograms 16 PL see profit and loss structure plain vanilla options 51 patterns 58 plain vanilla swaps 65–6, 65–6 point-in-time 131 political risk 137–8 portfolio structures 309–11 positivity 91 post-fixing (arrears) 56 practice earning (P/E) ratio 402 precisely defined pattern 54 premium gross and net for life insurance 338 in non-life insurance 355, 368 prepayment 61, 137, 143–5, 144, 145, 420 dates 143 models 184 rule 28 speed 143 present value of in-force (PVIF) 350–1 pricing 318–20 principal amortization patterns 51–3, 52 principal at maturity (PAM) 62–3, 67, 138–139, 147 characteristics 221, 222 events 222, 224 principal draw-down patterns (step-up) 53–4, 53 principal reserve pattern 54 probabilities of default 111–13, 247, 257 probability of loss event, for operational risk 280 product rates 100–101 rainbow options 60 RAROC see return on risk adjusted capital rate term 56 rating agencies parameters 152 rating states 257, 258 rating validation data 268 ratings see credit ratings ratios activity 402 debt 402 liquidity 402 market 402 profitability 402 risk 403–5 Sharpe 404 Treynor 404 re-securitization 415 real investments 316 real production 377–9 real world expectations 106 receivables in non-life insurance 356 reconciliation 304–5 recovery 62, 111, 113, 137, 152–3, 153, 266 gross 111 net 111 parameters 153 patterns 153 regular amortizer (RGM) 65, 65 regulations 421–2 regulatory risk 262–3 reinsurance contracts 360–1 liquidity 363–4 types 359 replication 137, 138–43 replication portfolio 140–2, 142 reporting 271 repricing 319 repricing term 56 reputation risk 30, 137–138 reserves 316 for life insurance 340–1 for non-life insurance 367–8 reserving pattern of life assurance contracts 54 reserving risk in non-life insurance 358–9 residual mortgage backed securities (RMBS) 416 P1: JYS ind JWBK356-Brammertz February 6, 2009 19:55 Printer: Yet to come Index retirement benefit, choice of 346 retirement time, choice of 345 return 410 return on equity (ROE) 404 return on risk adjusted capital (RORAC) 24, 405–6 RGM see regular amortizer risk 29, 71, 241–4, 331–3 combining 252–3 correlation 252 risk adjusted return on capital (RAROC) 404 risk analysis 23–4 risk categories 29–31 risk controlling 10 risk departments 11 risk drivers 377 risk factors 25, 29–31, 380 in unified financial language 419 risk-free investment rates 81 risk indicators approach, for operational risk 283 risk neutrality limitation risk premium 106 for life insurance 339–40 risk ratios 403–5 risk-neutral expectations 106 probabilities 79 probability measure 89–90 risk-neutral (risk-adjusted) valuation 101 arbitrage-free and complete markets 102–3 arbitrage-free incomplete markets 103–5 discounting with deflators 105–7 risk-neutral view 89–90 roll-down analysis 33, 295 rolling forward risk-neutral measure 96 roll-over 295 RORAC see Return on risk adjusted capital rule families 44 rule of 78 53 run-off analysis 33, 295 sales 61, 143–4 modeling parameters 144 savings 313–4 savings and loans (S&L) crisis scenarios, what-if 97, 209, 209, 293, 386 see also Monte Carlo simulations scrapping 140 securitization 415 security gain and loss 327 self-assessment approach, for operational risk 278 selling 135 senior tranches 121 sensitivities 71, 245–6 behavioral 226–31 431 interest rates 221–5 market 225–6 sensitivity 28, 219–39, 273 calculation 219–20 conditions for calculation 221, 221 dynamic simulation 331–3 sensitivity analysis 23–4 sensitivity oriented analysis 27 sensitivity reports 231–9 shifts for Solvency II 261 shock scenarios 260–1 shocked behavior 36 shocked market 36 shocks on add-ons 261 on haircuts 261 on market conditions 260 on migration matrices 261 on prepayments 261 on replications 261 short rate models 92–3 inhomogeneous 93 time-homogeneous 92–3 two-factors 93 short rates 85 single-barrier options 59–60 Solvency II expected defaults 249, 249 internal models 347–8, 367–8 regulation 16 special purpose vehicle (SPV) 120–1 special rates 320 specific margin, institution 213 speed factors 133 spot curve 84 spot LIBOR measure 96 spread curves 86 spread recoveries 258 spreads 56 as risk factors 87–9 St Petersburg paradox Standard & Poor (S&P) 130 standard contract types 46–51 basic 47 compound 47 standard contracts, rules and mechanisms 51–62 static analysis 33, 34, 82, 383–4 static modelling 83–9 interest rates 83–5 spreads as risk factors 87–9 stocks, exchange rates and commodities 86–7 step-up 53–4, 53 stochastic market models 89–98 stock price models 89–92 stochastic market models 96–101 stock market indices 294 P1: JYS ind JWBK356-Brammertz 432 February 6, 2009 19:55 Printer: Yet to come Index stock patterns 57 stocks 22, 48, 86–7 modelling 98–100 stock price models 48, 89–92 stress assumptions 324 stress scenarios 260–1, 324 stress testing 190, 271 structural liquidity risk 30 sub-prime crisis 110, 413 subadditivity 243 super cash flow 15 surrender 137, 147–8, 342, 345 value 342 swaps 50, 182–3 Swiss Solvency test 134 systems failures 285 target 376 target amount 144 target function 144 term selection 55–6 terminal value 392–4 Thrift Bulletin 13 5, 11 through-the-cycle 129 time 31–3, 274 calendar 31–2 double existence 32–3 intervals 32 time evolution time-homogeneous models 94–5 time line time value of options and guarantees (TVOG) 351 TOM 31 TOM next 31 tracing 271–2 tractability 91 trading 10 and off balance sheet 314–5 tranches 121 transaction analysis 72 transaction systems 45 transaction volume 309 Treasury 10 Treasury margin 213 two-factor models 93 Type I 36–7 Type I errors 264, 265 Type II 37 Type II errors 265, 266 Type III 37 Type IV 37 Type V 37 uncollateralized exposure 109 unearned premium reserve (UPR) 355, 368 Unified Financial Language 413–22 unit linked 345 unwinding 142 upfront payment 55 used at default 153–4 valuation 5, 71, 108 alternative techniques 202–7 amortized cost 191 balance sheets and 195–7 in credit risk 189 fair value 200–1 historic 199 linear write off 202, 202 lower of cost or market 202–3, 203 mark-to-market 200–1, 201 minimal value 203, 204 nominal value 197 risk-neutral 77–81 write-off at end 299 valuation principles 191–7 coexistence 193, 193 market dependent 194, 194 overview 194–5 time dependent 194, 194 valuation, special cases geometric 207 linear 207 operational considerations 206–7 physical investments 206 sum of digits 207 see also credit related impairments; multicurrency value 5, 22, 28, 34, 194–6, 275 based on constant effective yield valuation 199 based on linear write off valuation 202, 202 based on lower of cost or market valuation 202–3, 203 based on minimal value valuation 203, 204 based on MtM valuation 200–1, 201 based on nominal value 197, 197 based on write off at end valuation 199, 200 dynamic simulation 325–30 in non-life insurance 365–6 payback 144, 150 value at risk (VaR) 29, 71, 241–4 analytical methods 244–53 backtesting 265–7 Delta-gamma 245–6 Delta-normal 244–5 methods 253–59 operational risk 285–8 reports 14, 14 value date (VD) 53 value factor 144, 146 VaR see value at risk P1: JYS ind JWBK356-Brammertz February 6, 2009 19:55 Printer: Yet to come Index variable bond 63, 63 variable costs 168, 170 variable rate instruments 180–2 Vasicek model 92–93 volatility for operational risk 284 volatility smile 104 volatility term structure 91 volume 294–6, 294, 295 weighted average cost of capital (WACC) 108, 394–6 what-if scenarios 97, 209, 2091, 293, 386 433 Wiener process driftless 90 standard 88 workplace safety 285 write-off at end valuation 199, 200 yield curves 221, 260 zero coupon equivalent for sensitivity (ZES) 175, 177–180, 180, 181, 182, 185–186 zero coupon rates 82–3 Zillmer reserves 342 ... come The Evolution of Financial Analysis This was roughly the state of financial analysis regulation before the FASB 1335 and the Basel II regulations and before the advent of modern finance The. .. chaos that characterizes the state of financial analysis today It is followed by a condensed summary of the main themes of this book We introduce the principles of unified analysis, and important... that The aim of this book is to expose these shared elements and show how they can be combined to produce the results needed for any type of financial analysis Our focus lies on the analysis of financial