Contents Introduction: When a Tie Is More Than Just a Tie April 28, 2004: Steve Benardete Gets His Wish; The World Suffers Chapter 1: The Greatest Story Never Told Chapter 2: Origins Chapter 3: They Tried to Save Us Chapter 4: Regulatory Embracement Chapter 5: Abetting the CDO Party Chapter 6: VaR Goes to Washington Chapter 7: The Common Sense That Should Rule the World Finale: The Perils of Making the Simple Too Complex Guest Contributions: Why Was VaR Embraced? A Q&A with Nassim Taleb A Pioneer Wall Street Rocket Scientist’s View An Essay by Aaron Brown Acknowledgments About the Author Index Praise for The Number That Killed Us “Finally, here is a book that puts value-at-risk, VaR, at the center of the financial crisis, where it belongs Pablo Triana deftly traces the history of VaR, from what seemed like a good idea at Bankers Trust to a cancer that has infected the markets for more than two decades In the late 1980s, when financial innovation began to explode, VaR-type models appeared to be a reasonable way of capturing mounting new risks with a single numerical measure But, as Triana’s in-depth research shows, regulators foolishly hard-wired VaR into the rules governing risk, and disaster soon followed Even after numerous VaR-related crises—the Asian currency devaluation, the fall of Long-Term Capital Management, and the recent subprime and CDO fiascos—VaR remains a maddeningly central player, even as it promises to continue distorting risk and wreaking financial havoc This book is a cautionary tale.” —Frank Partnoy, University of San Diego School of Law VaR is an essential component of sound risk management systems —Professor Philippe Jorion, April 1997 I believe that VaR is the alibi that bankers will give shareholders (and the bailing-out taxpayer) to show documented due diligence, and will express that their blow-up came from truly unforeseeable circumstances and events with low probability not from taking large risks that they didn’t understand I maintain that VaR encourages untrained people to take misdirected risks with shareholders’, and ultimately the taxpayers’, money.” —Trader and Best-Selling Author Nassim Taleb, April 1997 A mega–financial cataclysm and a mega–public bailout later The risk-taking model that emboldened Wall Street to trade with impunity is broken and everyone is coming to the realization that no algorithm can substitute for old-fashioned due diligence VaR failed to detect the scope of the market’s collapse The past months have exposed the flaws of a financial measure based on historical prices —Financial Reporter Christine Harper, January 2008 It is clear in retrospect that the VaR measures of risk were faulty When the crisis broke VaR proved highly misleading —Financial Regulator Lord Turner, February 2009 Copyright © 2012 by Pablo Triana All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada 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, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750– 8400, fax (978) 646–8600, or on the Web at www.copyright.com Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748–6011, fax (201) 748–6008, or online at www.wiley.com/go/permissions Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose No warranty may be created or extended by sales representatives or written sales materials The advice and strategies contained herein may not be suitable for your situation You should consult with a professional where appropriate Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762–2974, outside the United States at (317) 572–3993 or fax (317) 572–4002 Wiley also publishes its books in a variety of electronic formats Some content that appears in print may not be available in electronic books For more information about Wiley products, visit our web site at www.wiley.com Library of Congress Cataloging-in-Publication Data: Triana, Pablo The number that killed us : a story of modern banking, flawed mathematics, and a big financial crisis / Pablo Triana p cm Includes index ISBN 978-0-470-52973-7 (hardback); 978-1-118-17154-7 (ebk); 978-1-118-17153-0 (ebk); 978-1118-17155-4 (ebk) Financial futures Global Financial Crisis, 2008–2009 Risk management I Title HG6024.A3T75 2012 332.64'52—dc23 2011029937 To those interested in the safety of the markets, the economy, and society Introduction When a Tie Is More Than Just a Tie On September 10, 2009, former trader and best-selling author Nassim Taleb did something that he very seldom does: He wore a tie By so graphically breaking with tradition (Taleb has publicly expressed his distaste for the blood-constraining artifacts, as well as for those who tend to don them), the Lebanese-American let the world know that that was a very special day for him, so special that it amply justified the sacrifice of temporarily betraying a sacred personal predisposition So what prompted the author of The Black Swana to uncharacteristically don such an alien piece of clothing? Well, he had been invited to a very solemn venue by very distinguished hosts, with such occasion quite likely demanding certain formalism in the way of attire And that was an invitation that Taleb had every intention of accepting In fact, he had been waiting and expecting for more than a decade; there was no way he was going to miss it The raison d’être of the event for which his company was now being required had been close to Taleb’s heart for most of his professional and intellectual life It represented a central theme in his actions and ideas, close to an obsession, akin to an identity definer He had through the years amply warned as to the havoc that might be wreaked should others massively act in a manner counter to his convictions Such concerns typically went unheeded (to the detriment, it turned out, of society), but now he was being offered a pulpit that seemed irresistibly magnificent, impossibly far-reaching This time, it seemed, the world would have no option but to attentively listen As Taleb entered the Rayburn Building of the U.S House of Representatives in the Capitol Hill neighborhood of Washington DC that September morning, he must have felt anticipation and, especially, vindication As he approached the sober room where several men and women awaited the start of the House Committee on Science and Technology’s hearing on the responsibility of mathematical model Value at Risk (VaR) for the terrible economic and financial crisis that had caused so much misery since the previous couple of years, Taleb probably reflected proudly on all those times when, indefatigably, and in the face of harsh opposition, he alerted us of the lethal threat to the system posed by the widespread use of VaR in financeland Now that the damage wrought by VaR was so inescapably obvious that lawmakers from the most powerful nation on the planet had been motivated into investigating the device, Taleb no longer seemed like a lone wolf howling in the markets wild, but rather appeared as imperially prescient What is so wrong about VaR, and why was Taleb so concerned about its impact? Most importantly, why should VaR be held responsible for the historic 2007–2008 credit crisis? VaR is a number that purports to estimate future losses deriving from a portfolio of trading assets, with a degree of statistical confidence, and presents two major problems: (1) it is doomed to being a very wrong estimate, due to its analytical foundations and the realities of real-life markets; and (2) in spite of such (well-known) deficiencies, it has for the past two decades become a ubiquitously influential force in the financial world, capable of directing decision making inside the most important banks In other words, by letting trading activity be guided by VaR, we have essentially exposed our economic fate to a deeply flawed mechanism Such flawedness, as was the case not only in this crisis but also before, can yield untold malaise The main issue with VaR is that it can easily and severely underestimate market risk Given the model’s powerful presence in financeland, that underestimation translates into recklessly huge and recklessly leveraged risk-taking on the part of banks A particularly big problem is that VaR can translate not just into huge risk-taking and leverage for regular assets, but also for very toxic assets As a tool that ignores the fundamental characteristics of assets, VaR can easily label the obviously risky as non-risky VaR can mask risk so well that an entire financial system can be inundated with the worst kinds of exposures and still consider itself comfortably safe, assuaged by the rosy comforting dictates from the glorified analytical radar VaR makes accumulating lots of toxic trading assets extremely feasible VaR, in sum, enables danger VaR is an untrustworthy and dangerous measure of future market risk for one main reason: It is calculated by looking at the past The upcoming risk of a financial asset (a stock, a bond, a derivative) is essentially assumed to mirror its behavior over the historical time period arbitrarily selected for the calculation (one year, five years, etc.) If such past happened to be placid (no big setbacks, no undue turbulence) then VaR would conclude that we should rest easy, safe in the statistical knowledge that no nasty surprises await For instance, in the months prior to the kickstarting of the crisis in mid-2007, the VaR of the big Wall Street firms was relatively quite low, reflecting the fact that the immediate past had been dominated by uninterrupted good times and negligible volatility, particularly when it came to the convoluted mortgage-related securities that investment banks had been enthusiastically accumulating on their balance sheets A one-day 95 percent VaR of $50 million was typical, and typically modest in its estimation of losses: At that level, a firm would be expected to lose no more than $50 million from its trading positions 95 percent of the time (in other words, it would be expected to lose more than $50 million only 12 days out of a year’s 250 trading days) When you consider that those Wall Street entities owned trading assets worth several hundred billion dollars and that the eventual setbacks amounted to several dozen billion dollars, we can appreciate that VaR’s predictions were excruciatingly off-base The soulless data rearview mirror may have detected no risk, but certainly that did not mean that the system was not flooded with the worst kind of risk, ready to explode at any time In finance, the past is simply not prologue, but someone forgot to tell VaR about it The fact that the mathematical engineering behind VaR tends to assume that markets follow a Normal probability distribution (thus assuming extreme moves to have negligible chance of happening, something obviously quite contrary to empirical evidence) can also contribute to the model churning unrealistically low numbers as big losses are ruled out, as can VaR’s reliance on the statistical concept of correlation, which calculates the future expected co-movement of different asset classes, based on how such codependence worked out in the past If several assets in the portfolio happened to be uncorrelated or, better yet, “negatively correlated” in the past, VaR will take for granted that those exposures should cancel each other out, yielding lower overall portfolio risk estimates However, as any seasoned trader would tell you, just because several assets were negatively correlated we can’t infer that they won’t move in tandem (positively correlated, implying that chances are that they can all tumble concurrently, thus painting a much worse overall risk picture) Eindhoven, Michael Einhorn, David Elliott, Douglas Enhanced bank capital requirements, impact (academic evidence) Equity capital cost enhanced financing costs, comparison increase requirements, enhancement Equity exposures (interest rate charge calculation), VaR technology (usage) Equity financing, cost (Stanford University analysis) Equity investment, riskiness Equity risk specific capital charge Euro Area, G3 bank dependence Exoteric securities, marked-to-market value Fermat, Pierre Finance path complexity reengineering Financial activity, complexity Financial assets charges, SEC knowledge risk Financial crisis, threat Financial engineers Financial estimations, basis Financial intermediation, cost (increase) Financial meltdown, VaR (impact) Financial risk analysis, execution attitudes implication management reform measurement, precision (problem) study/quantification Financial Services Authority (UK) Foreign Exchange/Cash Collateral Trading (FX/CCT) Frequentists advantage gamblers distributions statistician FTSE Global Government Bond Indices, indication Funding costs impact increase Garbade, Kenneth Gates, Bill Gladwell, Malcolm Global bank capital requirements, impact Global financial regulatory system, deficiencies Goldman Sachs capital charges computation equity base one-day VaR level trading decisions VaR-total assets ratio Goldschmid, Harvey Great Depression (1929) Group of Thirty (G30), lobbying Guldimann, Till JPMorgan departure Haircut, penalty Hancock, Peter Harper, Christine Hedged positions Hedge fund trading Historical Simulation function, explanation method, usage usage Iceland, problems Illiquid complex assets, leverage ratios Incremental Risk Charge (IRC) add-ons intention In-house risk management, VaR usage Institute for International Finance (IIF), Basel III study Basel Committee, disagreement Interest rate exposures risk charges (calculation), VaR technology (usage) Interest rate risk, example Internal Models Approach, usage International Association of Financial Engineers (IAFA) Intraday price movements, consideration Intuitional risk management Jacobson, Ken Jorion, Philippe JP Morgan derivatives business, risk number May, impact one-day VaR level trading decisions VaR-total assets ratio Weatherstone/Guldimann departure JP Morgan VaR approach creation RiskMetrics VaR, contrast stress testing Junior tranches, sale Keynes, John Maynard Kolchinsky, Eric Lehman Brothers assets support average daily VaR VaR, amount Lemmas Leverage creation, VaR (impact) defining excess impact implication quantity ratio prudence regulatory limits toxicity VaR impact VaR invention Liquidity disappearance puts VaR, impact Long-term borrowings Long Term Capital Management (LTCM) disaster liquidation VaR-calculated capital charges, insufficiency Long-term frequency, mathematical statement Market crises, data-based risk models (problems) Market-related capital charges, decisions Market risk Basel proposal broker-dealer deductions capital levy, Basel I amendment (impact) capital requirements, impact components, calculation (standardized method) growth management, VaR (impact) measure, VaR role (prominence) regulatory treatment transparency, increase Market Risk Amendment (Basel Capital Accord) Market risk-based measures, impact Market risk capital change charges reduction deductions, calculation rules Market risk estimation, VaR problems Market signals, implication Market volatility, absence Markowitz, Harry Mark-to-market accounting, benefits Martin, Gorge Mathematical models market signals, impact usage, inquiry Matrices, usage May, Raymond Ray May spreadsheet Ray May VaR RiskMetrics understanding VaR creation Wall Street competitor Merrill Lynch balance sheet market risk treatment, credit risk treatment conversion meltdown net super senior retention exposure portfolio, toxicity regulatory VaR level subprime losses VaR, amount losses, projection Metrics-based approaches, cessation (impact) Mezzanine CDOs, purchases Mezzanine tranches, impact Models-based credit ratings, impact Models-based regulations, impact Modern Portfolio Theory, usage Monte Carlo Simulation, usage Morgan Stanley equity capital net super senior exposure trading decisions Mortgage crisis, accuracy (problem) Municipal bonds, percent weight problems Nader, Ralph Net capital dollar amount SEC limit Net Capital Rule (SEC) amendment Net super senior exposures Normality, usage Northern Rock, debacle Off-balance sheet conduits, back asset sale Organization for Economic Cooperation and Development (OECD) debt, global bank accumulation Originate-and-distribute model Outliers exclusion Pascal, Blaise Persaud, Avinash impact Poisson, Siméon Poker Face of Wall Street (Brown) Portfolios assets examples negative correlation relative riskiness uncorrelated assets, risk-reducing diversification benefits Price movements, shift Probability distributions considerations rocket scientist approach estimation, noise (presence) example theory inadequacy Profit and loss (P&L), focus/computation Quantitative Risk Control (Investment Banking Division) Quantitative risk models QuAnts impact repentance Quants risk-taking backgrounds, absence sports bettors, probability perspective Ray May spreadsheet Ray May VaR Real VaRs, problems Rebonato, Ricardo Red-Blooded Risk (Brown) Regulatory arbitrage Regulatory capital measure, calculation requirements, bank demand Regulatory cushion, impact Regulatory metrics, malfunction Re-securitizations, impact Residential Alt-A mortgage RBMSs/CDO positions Residential mortgage-backed securities (RBMSs) demand placement, VaR (impact) transfer tranches, bank engineering VaR power, problems Return on assets (ROA) Return on equity (ROE), decrease Rickards, James Risk aggregation assessment benchmark buckets, impact calculation/management, VaR in-house method calibration capital, trading charges (calculation), VaR technology (usage) concentration, feasibility control VaR, usage definition, problem estimates estimation, VaR role exploration guidance, problem measurement alternative perspective models, usage rules, simplicity simplicity VaR control, assumption VaR measurement VaR overestimation VaR underestimation Risk-based metrics, bank adoption Risk-free assets, principal (investment) Riskless income, generation Risk management fault goal practices usage types RiskMetrics popularity system understanding VaR, JPMorgan VaR (contrast) VaR methodology, publication Riskmetrics Risk-taking, debt financing Risk-weighted assets charges concept (Basel I introduction) modification Risky investments, equity holder incentive Royal Bank of Scotland, debacle Russia, meltdown/crisis Securities risks/returns toxicity, accumulation Securities and Exchange Commission (SEC) Net Capital Rule Commission amendment policy (2004), impact Securities Industry Association (SIA), lobbying Securitized mortgage exposures, placement Short-term borrowings Short-term market movements (estimation), VaR methodologies (usage) Sigma (standard deviation) two-tailed statistical confidence interval, example VaR, occurrence Societe Generale, trading book leverage Specific risk Standard deviation (sigma) Standardized Approach Standardized method Standard model Statistical arbitrage Statisticians, types Stimmler, Mary Kay Stock market crash (1987) Stressed VaR add-ons Studer, Nick Subcommittee on Investigation and Oversight, U.S House Committee on Science and Technology Subordinated tranches, investor purchase Subprime CDOs assessments bank usage balance sheet location crisis risk, understanding SEC ruling, impact speculation super senior component, retention trading book placement, bank incentive tranches, amount UBS involvement VaR power, problems warehousing, problems Subprime crisis accuracy, problem VaR crisis, impact Subprime loans, losses Subprime market, problems Subprime mortgages impact warehousing Subprime RMBSs, trading book placement (bank incentive) Super senior categories Super senior CDOs, consideration Super senior holdings bank holdings existence, reasons Super senior tranches bank holding, JP Morgan estimate impact retention, problems unattractiveness Swaps BackOffice System, JP Morgan construction risk, calculation Swiss Federal Banking Commission (SFBC) atonement investigation Synthetic CDO, super senior investor payments Tail events Taleb, Nassim Derivatives Strategy interview impact interview VaR explanation/understanding Tartaglia, Nunzio Tett, Gillian Theoretical models, usage Tier capital Tier capital Tier capital introduction Toxic assets acquisition balance sheet appearance SEC treatment Toxic leverage guarantee problems risk mechanism delivery Toxic risks, VaR underestimation Toxic securities, accumulation Traders, risk-lite approach Trading affordability/leverage, costliness (VaR calculation) asset, defining bets, financing desks/business, usage opportunities portfolio, leverage Trading book asset placement, easement bank abuse bank usage capital result, assumption CDO/RMBS placement credit-related assets, placement exposures, capital support impact leverage presence securitized mortgage exposures, placement treatment, bank preference usage VaR, impact Trading-related capital requirements Trading-related leverage Tranches, enhancement Trigger algorithms, adoption Turner Report (2009) Turner Review (UK Financial Services Authority) UBS assets carry trade, profitability CDO purchase CDO toxicity level complacency confidence level credit crisis Foreign Exchange/Cash Collateral Trading (FX/CCT) internal funding, problems leverage market risk treatment, credit risk treatment conversion off-balance sheet activities on-balance sheet CDO positions, trading book treatment risk management, robustness (assumption) structuring fees subprime losses subprime positions, filtration subprime risk, Group Senior Management comprehension super seniority, selection super senior positions, positive carry super senior tranches accumulation net positive carry super-senior tranches, addition super senior trouble Swiss Federal Banking Commission investigation total equity capital, amount VaR measurement warehousing exposure United States, housing bubble (collapse) U.S House Committee on Science and Technology, Subcommittee on Investigation and Oversight U.S mortgage market, disruptions Value at Risk (VaR) academics, impact add-ons adoption phase-in period, absence appearance ascension, reasons assumptions, violation bank calculation banker usage bank limits, problems Benardete perspective benefits calculations example methodology capital calculation methodology cessation, impact comparison, Brown perspective comprehensive approach computation cost difficulty constructs, adoption/promotion contrarians counterrevolution coverage credibility credit ratings reliance crisis impact criticisms danger Danielsson perspective presence decline deficiencies destruction capacity due diligence exceptions, bank registration exposure/fragility failure guidelines, reliance historical data historical evidence, statistical dissection impact problems reduction imposition, regulatory measure indictment internal competition international regulators usage invention, reason knowledge, absence limit breach imposition liquidations, impact logic Lord Turner perspective low level malfunction market risk measurement tool, acceptance mathematical engineering May creation measure, problems Merrill Lynch statement methodology design publication models impact regulatory adoption normal markets No-VaR, improvement performance, problem personal advantages popularity reasons power endowment, problems height predictability predictions failure inaccuracies presence, impact probabilistic foundations problems promotion QuAnt usage relevance reliance rigor risk management device usage risk measure, usage risk metric RiskMetrics, impact role SEC policy, interaction side effect solutions spreadsheet, development standard model Taleb explanation Taleb understanding term, appearance tests, types toxic leverage trading desk limit breaches trading-related leverage value, Bookstaber perspective VaR neutral VaR-total assets ratios VaR-type models, creation violations Wall Street lobby Wall Street perspective zero VaR Value at Risk (VaR) risk absence, assumption blindness estimator role Variance-Covariance method dominance explanation power usage Volatility estimates, unreliability Wall Street, rules (application) Weatherstone, Dennis JPMorgan departure Wellink, Nout Whalen, Christopher Wilmott, Paul World of Chance, A (Brown) Zero VaR ... estimated that broker-dealers taking advantage of the alternative capital computation would realize an average reduction in capital deductions of approximately 40%.” Whatever the actual accuracy of. .. ridiculously off-target rating agencies It is clear that each and every one of those factors played a substantial role and deserves a large share of the blame But the familiar list has tended to leave... sales pitch can be built around it, and as long as financing the purchase of the asset is made easy by easy monetary policy, the reign of VaR as capital king can guarantee the emergence of an