Regulating Systemic Risk 1

Similar documents
Systemic Risk: What is it? Are Insurance Firms Systemically Important?

FEDERAL RESERVE BANK OF MINNEAPOLIS BANKING AND POLICY STUDIES

VOLATILITY, CORRELATION AND TAILS

VOLATILITY, CORRELATION AND TAILS

Valuing Financial Assets with Liquidity Discount: An Implication to Basel III *

Stress Testing U.S. Bank Holding Companies

Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks

Session 28 Systemic Risk of Banks & Insurance. Richard Nesbitt, CEO Global Risk Institute in Financial Services

Comments on Toward a 3-Tiered Market for US Home Mortgages

ANNUAL MEETING OF STOCKHOLDERS. April 8, 2014

Historical Backdrop to the 2007/08 Liquidity Crunch

SYSTEMIC RISK AND THE PROSPECT FOR GLOBAL FINANCIAL TABILITY BY ROBERT F. ENGLE AND MATTHEW RICHARDSON NYU STERN SCHOOL OF BUSINESS

Lecture 12: Too Big to Fail and the US Financial Crisis

1. What was life like in Iceland before the financial crisis? 3. How much did Iceland s three banks borrow? What happened to the money?

Volume Author/Editor: Joseph G. Haubrich and Andrew W. Lo, editors. Volume Publisher: University of Chicago Press

April 24, Annual Stockholder Meeting

FEDERAL RESERVE BANK OF MINNEAPOLIS BANKING AND POLICY STUDIES

Yesterday s Heroes: Compensation and Creative Risk Taking

New Risk Management Strategies

Composition of the Short-Term Debt Estimate (SNL Definitions)

1 U.S. Subprime Crisis

Systemic Risk and Sentiment

, SIFIs. ( Systemically Important Financial Institutions, SIFIs) Bernanke. (too interconnected to fail), Rajan (2009) (too systemic to fail),

Rethinking Economics after the Crisis. Robert Engle, NYU Stern Policy Panel at ECB June 24,2014

Agenda. Introduction. Securities Strategy. Capital and Risk Management. Environment and Priorities

Regulatory Proposals for Money Market Funds and Current Topics Affecting the Short-Term Investment Marketplace

Stephen S. Crawford, Chief Financial Officer Mitch Merin, President & Chief Operating Officer, Morgan Stanley Investment Management

The ETF Industry! THE ETFs ECOSYSTEM:! KEY TRENDS TO WATCH!

Systemic risk: Applications for investors and policymakers. Will Kinlaw Mark Kritzman David Turkington

Sanford C. Bernstein Conference

The Decline of Too Big to Fail

How to Calculate Systemic Risk Surcharges

Guggenheim Defined Portfolios, Series Financials Portfolio, Series 11

Investment Banking and Capital Markets Market Report Third Quarter 2008

Systemic Risk: Models and Policy Narodna Banka Srbije

Course Outline. Credit Risk. Winter 2014 FINC.GB.3305.W1. Contact information:

Don t Blame the Messenger or Ignore the Message. Ray Ball. The message? Highly leveraged institutions gambling heavily on risky, low-transparency

Market Capitalization $39.0 Billion

Money and Banking ECON3303. Lecture 9: Financial Crises. William J. Crowder Ph.D.

Why Buy Radian? NYSE: RDN

Stress testing and systemic risk

Measuring the TBTF effect on bond pricing: Supplemental data

I. Learning Objectives II. The Functions of Money III. The Components of the Money Supply

Deutsche Bank 2006 Results

Federal Reserve Bank of Chicago Bank Structure Conference May, Armen Hovakimian, Baruch College Edward J. Kane, Boston College Luc Laeven, IMF

ERISA Stock Drop Litigation Against Financial Institutions

Financial Crisis 101: A Beginner's Guide to Structured Finance, Financial Crisis, and Market Regulation

Causes Of The Actual Global Financial Crisis. While many argue that this is the main cause of the global savings glut, the opposite is the

December 31, Semiannual Report. Income Funds

Reviewing DFAST And CCAR Results. Coming off recent passage of living wills, large banks continue to pass stress tests June 2017

UNINTENDED CONSEQUENCES OF LOLR FACILITIES: THE CASE OF ILLIQUID LEVERAGE FOURTEENTH JACQUES POLAK CONFERENCE, IMF, NOVEMBER

Goldman Sachs U.S. Financial Services Conference

How Curb Risk In Wall Street. Luigi Zingales. University of Chicago

Introduction. Learning Objectives. Chapter 15. Money, Banking, and Central Banking

FEDERAL RESERVE BANK OF MINNEAPOLIS BANKING AND POLICY STUDIES

Q. Are any of your money market funds at risk of breaking the buck?

A Theoretical and Empirical Comparison of Systemic Risk Measures: MES versus CoVaR

Liquidity, Capital and Financial Outlook Todd Gibbons Chief Financial Officer

Goldman, Morgan Scrap Wall Street Model, Become Banks in Bid to Ride Out Crisis

Why Are Financial Intermediaries Special?

Designating Bank SIFIs: An Arbitrary Threshold for Risk

GRADUATE SCHOOL OF BUSINESS Global Risk Management: A Quantitative Guide. Securitization. Ren-Raw Chen Fordham University

Global Securities Lending Business and Market Update

FINC-UB WI11 THE FINANCIAL CRISIS OF : CAUSES, SOLUTIONS and REGULATION

Implications of the Dodd-Frank Act on Too Big to Fail A presentation for Washington University s Life-Long Learning Institute

The Capital and Loss Assessment Under Stress Scenarios (CLASS) Model

Deutsche Bank Dr. Josef Ackermann

2014 MBA SMF ANALYST REPORT

Nasdaq US Large Cap Equities for Rising Rates Index

Investing in the Future. TCF Financial Corporation

Bailout Tally Report

Black Monday Exploring Current Financial Crisis

Robert Engle and Emil Siriwardane Volatility Institute of NYU Stern 6/24/2014 STRUCTURAL GARCH AND A RISK BASED TOTAL LEVERAGE CAPITAL REQUIREMENT

BOX Penny Pilot Report: Penny Pilot Report 5

Systemic Risk from Derivatives: Network Analysis

Safe Capital Ratios for Bank Holding Companies. Roger Craine Professor of Economics University of California, Berkeley CA

Deutsche Bank Roadshow Dr. Josef Ackermann

MSR Industry Report: First Quarter MVFS Client Distribution 2017 MountainView Analytics, LLC. All Rights Reserved.

Sample Equity Attribution Summary PDF

Credit Risk Spillovers among Financial Institutions around the Global Credit Crisis: Firm-Level Evidence

BOX Penny Pilot Report: Penny Pilot Report 7

REVERSE EVENT STUDY: BANK STOCKS AND THE FINANCIAL CRISIS

Aggregate Risk and the Choice Between Cash and Lines of Credit

10 Years After the Financial Crisis: Where Do Shareholder Rights Stand?

Reflections on the Financial Crisis Allan H. Meltzer

Flight to Quality for Large Financial Institutions

TD Bank Financial Group

Lessons Learned? Comparing the Federal Reserve s Response to the Crises of and

Liquidity and Financial Cycles

Recent Debt Summary & Related Issues

Markus K. Brunnermeier (joint with Tobias Adrian) Princeton University

Deutsche Bank. Dr. Josef Ackermann Chairman of the Management Board. San Francisco / San Diego / Denver / Chicago July 2008

Systemic Risk Measures

The Financial Sector. Scott Mertens, Kristen Hecht, Chris Letcher, Chris Weber, Joseph Brendel, Jun Mei. Cougar Investment Fund

Structural GARCH: The Volatility-Leverage Connection

Deutsche Bank. Chief Financial Officer. Frankfurt / New York / Boston / The Netherlands 3 7 November 2008

Goldman Sachs. U.S. Financial Services Conference Richard K. Davis Chairman, President and CEO

U.S. Treasury Department s Capital Purchase Program. Investment Banking Considerations or

Financial Opportunities Portfolio, Series Ubiquitous Strategy Portfolio, Series (Advisors Disciplined Trust 1765) Prospectus

Asymmetric Market Reactions to the Financial Crisis: From Wall Street to Main Street

Transcription:

Regulating Systemic Risk 1 By Viral V. Acharya, Lasse Pedersen, Thomas Philippon and Matthew Richardson NYU Stern School of Business I. Summary II. Measuring Systemic Risk III. Quantifying Systemic Risk a. Example of June 2007 b. Ranking Based on MES 2007 c. Historical Perspective (1963 present) IV. Uses of Systemic Risk Measure a. Some Specific Uses b. An Example of Insurance Charges 1 Based on chapter 13 of Restoring Financial Stability: How to Repair a Failed System, John Wiley & Sons, 2009, and the working paper, Regulating Systemic Risk (Acharya, Lester, Pedersen, Philippon and Richardson).

I. Summary We argue that financial regulation be focused on limiting systemic risk, that is, the risk of a crisis in the financial sector and its spillover to the economy at large. To this end, we provide a simple and intuitive way to measure systemic risk in the financial sector and suggest novel regulations to limit it. Current financial regulations seek to limit each institution s risk. Unless the external costs of systemic risk are internalized by each financial institution, the institution will have the incentive to take risks that are borne by all. In other words, each individual firm may take actions to prevent their own collapse but not necessarily the collapse of the system. It is in this sense that the financial institution s risk is a negative externality on the system. 2 An illustration of the current crisis is that financial institutions took bets on securities and portfolios of loans which faced almost no idiosyncratic risk, but large amounts of systematic risk. Our approach to regulating systemic risk is twofold: The regulator would assess the contribution of each firm to the downside aggregate risk of the economy. The firm s individual contribution to aggregate risk would then determine the extent of regulatory constraints, which can be implemented as ex ante capital requirements and required contributions to capital insurance. Each firm would be required to buy insurance against its own losses in a scenario in which the whole financial sector or economy are doing poorly. In the event of a payoff on the insurance, the payment should not go to the firm itself, but to the regulator in charge of stabilizing the financial sector. This would provide incentives for a company to limit systemic risk (to lower its insurance premium), provide a market based estimate of the risk (the cost of insurance) and avoid moral hazard (because the firm does not get the insurance payoff). 2 An analogy can be made to an industrial company who produces emissions that might lower its costs but pollutes the environment.

II. Measuring Systemic Risk (i) Intuition: Suppose that the economy incurs a systemic cost (a negative externality of the financial sector) whenever there is a "crisis", measured as the return to the financial sector being sufficiently bad, say in the 5% left tail of the market return distribution. Suppose further that the cost is proportional to the extent of loss incurred below the 5% cutoff. Then the contribution of each individual financial institution to this cost is proportional to its size and to the percentage loss or negative return it suffers when the market is in its left 5% tail. The "tax" to be imposed on each institution should thus be the average of this contribution, or in other words, its Marginal Expected Shortfall (MES) multiplied by its (dollar) weight in the economy. To summarize, MES of a financial institution can be interpreted as the per dollar systemic risk contribution of that institution. (ii) Marginal Expected Shortfall (MES) The idea behind MES is that one calculates the losses experienced by each firm when aggregate losses are large. The MES is the contribution of each firm to the aggregate losses.

III. Quantifying Systemic Risk For the example to follow, we calculate the losses of the market value of equity of financial firms in the prior year s 5% worst case periods of aggregate stock market losses (measured on a daily basis). We focus on financial firms with at least $5 billion in market capitalization (as of June 2007), leaving us with 102 financial firms. We explore three periods: A pre event period for systemic risk measurement (June 2006 June 2007) An event period to explain realized performance (July 2007 December 2008) An historical period from 1963 to 2008 Some general conclusions (not shown here but available in the working paper) are: a. Systemic measures like MES and Beta outperform institutional risk measures like expected shortfall (ES). b. In a horse race, MES contains more relevant information than Beta. c. The MES measures seem to have predictive power up to 3 4 months lead time.

A. June 2007 This figure depicts the dollar valued marginal expected shortfall, MES5, for the 20 companies with the largest dollar values. MES5 is the average return of an individual stock conditioned on the market return being below the 5 th percentile as determined by the distribution of market returns. MES5 was computed using the pre crisis period June 2006 till June 2007. To obtain an estimate in dollar values the measure was multiplied by the size of the firm determined by the market cap as of end of June 2007. Expected Shortfall (in Billion Dollars) Data throughjune 07 0 1 2 3 4 5 C JPM BAC MS GS MER WFC FNM AIG WB AXP LEH BEN MET WM SCH PRU BK NYX FRE BSC USB UNH UNP STT

Scatterplot of the marginal expected shortfall measure, MES5, against the return during the crisis. The sample consists of the 102 companies selected based on their inclusion in the U.S. financial sector and their market cap as of end of June 2007. Return during crisis: July07 to Dec08-1 -.5 0.5 BRK HCBK UB SAF AOC BOT ATPBCT BER AGE CBSS CBH CB CG AFL TRV MA WFC BLK USB MMCFNF UNPNTRS SCHW NYB CINF PNC BBTUNM FIS BK TMK PGR JPMWUTROW AMTD SNV NMX HUM ALL AET MTBLTRLUK STT MET SEIC ICE UNHWLP AIZ EVBEN STI MI COF CNA HBAN CME PFG GS CMA AMP NYX ZION PRU BACI AXP CVH RF KEY LNC JNS FITB LM MS HNT HIG SLM WB C SOVCFC MER CBG GNW NCC MBI ACAS CIT BSCETFC AIG FRE ABK WM FNM LEH 0.01.02.03.04 MES5 measured June06 to June07

B. June 07 Rankings of MES Top 4 out of 10 firms ranked by MES pre crisis have effectively failed (Bear, Lehman, ML, CIT), two received government support (GS, MS), others interesting (etrade, CBRE, Charles Schwab, Ameritrade) On a dollar basis for MES or insurance costs, Citigroup and JPMorgan also enter top 10.

C. Historical Perspective The graph depicts for each year from 1963 until 2008 the market cap weighted Marginal ES(5%) for each of the four categories conditioned on above 22 days of trading within a year. Annual Value-Weighted Marginal ES(5% ) by groups. 0.11 0.09 0.07 0.05 0.03 0.01-0.01 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 NBER Recession Depositories Others Insurance Sec. and Comm. The graph depicts for each year from 1963 until 2008 the equally weighted Marginal ES(5%) for each of the four categories conditioned on above 22 days of trading within a year. Annual Equally-Weighted Marginal ES(5%) by groups. 0.095 0.075 0.055 0.035 0.015-0.005 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 NBER Recession Depositories Others Insurance Sec. and Comm.

IV. Uses of Systemic Risk A. Some Specific Uses Capital Requirement Capital requirements could be set as a function of a financial firm s MES, in particular, the systemic capital charge (SCC) could be written as: SCC=S x MES% x A where S would be the systemic factor chosen by the regulator to achieve a given degree of aggregate safety and soundness, MES% is the marginal expected shortfall expressed in percent of assets, and A would be the assets of the firm. 3 This gives the right incentives to firms to limit their holding on aggregate risk since keeping capital reserves is costly and, additionally, it gives the firm an appropriate safety buffer in systemic crises. Forced Conversion of Debt Financial institutions have incentives to take excessive risks as long as there is a lack of market discipline, that is, as long as distressed risk is not borne by the creditors. This is because of government guarantees deposit insurance and too big to fail, as well as a zero price for systemic risk. One way to avoid the ex post problem of dealing with failed institutions during the crisis is to require financial firms to issue some amount of debt that automatically gets converted into equity during a crisis. The amount of this debt should be directly tied to the MES of the firm, that is, to the amount of systemic risk the firm imposes on the system. Because the holders of these securities receive no government guarantees, the investors will impose market costs on the firm. Presumably, the more the firm has to issue this type of debt, the greater the costs. Insurance Charge As mentioned above, the systemic risk of financial institutions is a pollutant, imposing a negative externality on financial markets. One efficient solution to handle a negative externality is to tax it. This provides financial firms with incentives to organically limit their systemic risk and it also contributes taxes to a systemic fund. The next page describes an example of how it would work. 3 Note that S could be chosen in such a way as to be counter cyclical, in other words, higher in boom times than current periods. The primary function of the MES% is to separate more systemic institutions from the field.

B. Insurance Charges Steps Each financial institution would be required to take out insurance against its own losses during a general crisis (i.e., against its MES). The price of this insurance would be set by the private insurance industry. If losses take place, the payment does not go to the financial institution, but to a systemic fund. Thus, the insurance acts like a tax. The pricing of the insurance is a multivariate put option on the firm s losses conditional on the aggregate market falling. One of the issues is that there may not be enough capital available in the private insurance industry to cover the potential losses from a systemic event (as with the monolines and A.I.G.). Thus, we advocate that the majority of the insurance (say 90%) is offered by the government. The insurance fees would be paid to the government, and the government would provide self insurance. There is already a successful program that does something similar, namely the Terrorism Risk Insurance Act of 2002. On the next page, we provide a table of the ranking of estimated insurance charges for financial institutions during the 2004 2007period. 4 In practice, the insurance (i) should have a maturity that covers business cycles (say five years), (ii) should be purchased on a rolling, quarterly basis to prevent gaming of the insurance (e.g., 1/20 th of the total amount purchased each quarter), and (iii) should be bought only from well capitalized institutions (even given the public private insurance scheme). For the estimated costs below, we have assumed multivariate normality for pricing the multivariate put option. 5 This represents a large underestimate of the true cost, yet perhaps not the relative costs across firms. Equity returns have fat tails and tend to be more highly correlated in severe down states, both of which contribute to higher option prices. The benefit of a private public insurance scheme in which the insurance would be priced by the market would allow fat tails and high correlation to be priced directly into the option. Even without this market pricing, however, the estimated costs from theoretical option pricing allow the regulator 4 We treat the liabilities of insurance companies, investment banks and commercial banks on the same level in terms of measuring the MES and the insurance payoff. It is desirable to perhaps treat different types of financial institutions differently. 5 Of 102 financial firms, the Tables below present the top 20 in terms of insurance costs during the period June 2004 to June 2007. The insurance payoff is triggered when the market drops 40% and the firm s ratio of market value of equity to total liabilities + market equity value falls below 10% at the end of a four year period. The payoff equals the difference between the equity value implied by the 10% ratio and the final equity value. The volatility of the firm s equity, the volatility of the market, and the correlation between the two, are estimated using daily data over the prior year.

to observe red flags to initiate a further investigation of the financial firm beyond the typical violation of capital requirements. As an indicator of potential success, we rank the top 20 firms based on their insurance fee ($ and $ as a % of equity) from June 2004 to June 2007 (the month before the crisis started). The insurance fee chooses a list of firms familiar to observers of the crisis, namely Bear Stearns, Lehman Brothers, Merrill Lynch, Morgan Stanley, Countrywide, Freddie Mac, Fannie Mae, Goldman Sachs, Citigroup and JP Morgan. Rank 2004 2005 2006 2007 FEDERAL NATIONAL FEDERAL NATIONAL MORTGAGE MORGAN STANLEY DEAN WITTER MORGAN STANLEY DEAN 1 MORTGAGE ASSN ASSN & CO WITTER & CO MORGAN STANLEY DEAN MORGAN STANLEY DEAN WITTER FEDERAL NATIONAL MORTGAGE 2 WITTER & CO & CO ASSN CITIGROUP INC 3JPMORGAN CHASE & CO FEDERAL HOME LOAN MORTGAGE CORP GOLDMAN SACHS GROUP INC MERRILL LYNCH & CO INC 4 MERRILL LYNCH & CO INC JPMORGAN CHASE & CO MERRILL LYNCH & CO INC JPMORGAN CHASE & CO 5GOLDMAN SACHS GROUP INC MERRILL LYNCH & CO INC JPMORGAN CHASE & CO GOLDMAN SACHS GROUP INC LEHMAN BROTHERS HOLDINGS LEHMAN BROTHERS HOLDINGS FEDERAL HOME LOAN 6 INC GOLDMAN SACHS GROUP INC INC MORTGAGE CORP 7PRUDENTIAL FINANCIAL INC LEHMAN BROTHERS HOLDINGS INC METLIFE INC FEDERAL NATIONAL MORTGAGE ASSN 8CITIGROUP INC PRUDENTIAL FINANCIAL INC BEAR STEARNS COMPANIES INC LEHMAN BROTHERS HOLDINGS INC BEAR STEARNS COMPANIES 9 INC METLIFE INC PRUDENTIAL FINANCIAL INC BEAR STEARNS COMPANIES INC 10 METLIFE INC CITIGROUP INC GROUP I METLIFE INC 11 GROUP I BEAR STEARNS COMPANIES INC CITIGROUP INC BANK OF AMERICA CORP 12 BANK OF AMERICA CORP BANK OF AMERICA CORP BANK OF AMERICA CORP PRUDENTIAL FINANCIAL INC 13 WACHOVIA CORP 2ND NEW AMERICAN INTERNATIONAL GROUP IN WASHINGTON MUTUAL INC GROUP I 14WASHINGTON MUTUAL INC GROUP I COUNTRYWIDE FINANCIAL CORP COUNTRYWIDE FINANCIAL CORP 15 LINCOLN NATIONAL CORP IN WACHOVIA CORP 2ND NEW WACHOVIA CORP 2ND NEW WACHOVIA CORP 2ND NEW RANKINGS of MOST SYSTEMIC FINANCIAL INSTITUTIONS BY HYPOTHETICAL $ INSURANCE CHARGES from 2004-2007

Rank 2004 2005 2006 2007 1BEAR STEARNS COMPANIES INC BEAR STEARNS COMPANIES INC BEAR STEARNS COMPANIES INC BEAR STEARNS COMPANIES INC FEDERAL HOME LOAN FEDERAL NATIONAL MORTGAGE FEDERAL HOME LOAN 2GENWORTH FINANCIAL INC MORTGAGE CORP ASSN MORTGAGE CORP LEHMAN BROTHERS HOLDINGS FEDERAL NATIONAL MORTGAGE MORGAN STANLEY DEAN WITTER LEHMAN BROTHERS HOLDINGS 3 INC ASSN & CO INC MORGAN STANLEY DEAN WITTER LEHMAN BROTHERS HOLDINGS 4PRUDENTIAL FINANCIAL INC & CO INC MERRILL LYNCH & CO INC MORGAN STANLEY DEAN 5 WITTER & CO LINCOLN NATIONAL CORP IN GOLDMAN SACHS GROUP INC MORGAN STANLEY DEAN WITTER & CO 6LINCOLN NATIONAL CORP IN LEHMAN BROTHERS HOLDINGS INC MERRILL LYNCH & CO INC FEDERAL NATIONAL MORTGAGE ASSN FEDERAL NATIONAL MORTGAGE 7 ASSN GOLDMAN SACHS GROUP INC METLIFE INC GOLDMAN SACHS GROUP INC 8 GROUP I MERRILL LYNCH & CO INC GROUP I COUNTRYWIDE FINANCIAL CORP 9METLIFE INC GROUP I PRUDENTIAL FINANCIAL INC METLIFE INC 10 MERRILL LYNCH & CO INC PRUDENTIAL FINANCIAL INC LINCOLN NATIONAL CORP IN GROUP I 11 GOLDMAN SACHS GROUP INC GENWORTH FINANCIAL INC AMERIPRISE FINANCIAL INC PRINCIPAL FINANCIAL GROUP INC 12 JPMORGAN CHASE & CO METLIFE INC COUNTRYWIDE FINANCIAL CORP LINCOLN NATIONAL CORP IN PRINCIPAL FINANCIAL GROUP 13 INC PRINCIPAL FINANCIAL GROUP INC JPMORGAN CHASE & CO PRUDENTIAL FINANCIAL INC 14 E TRADE FINANCIAL CORP JPMORGAN CHASE & CO UNUM GROUP JPMORGAN CHASE & CO 15 UNUM GROUP E TRADE FINANCIAL CORP SOVEREIGN BANCORP INC CITIGROUP INC 16 TRAVELERS COMPANIES INC UNUM GROUP PRINCIPAL FINANCIAL GROUP INC AMERIPRISE FINANCIAL INC 17 C I G N A CORP WASHINGTON MUTUAL INC E TRADE FINANCIAL CORP E TRADE FINANCIAL CORP 18 SOVEREIGN BANCORP INC C N A FINANCIAL CORP WASHINGTON MUTUAL INC C I T GROUP INC NEW 19 WASHINGTON MUTUAL INC COUNTRYWIDE FINANCIAL CORP COMMERCE BANCORP INC NJ WASHINGTON MUTUAL INC 20 COMMERCE BANCORP INC NJ COMMERCE BANCORP INC NJ HUNTINGTON BANCSHARES INC COMMERCE BANCORP INC NJ RANKINGS of MOST SYSTEMIC FINANCIAL INSTITUTIONS BY HYPOTHETICAL $ INSURANCE CHARGES from 2004-2007 as a % of EQUITY