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Edward J. Kane

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Title: Edward J. Kane


1
04-6
  • Understanding and Measuring FSF Capital
  • Basel Capital Requirements
  • Limitations of Value at Risk
  • Edward J. Kane
  • Boston College

2
Ownership Capital acts as a shield against loss
for nonowner stakeholders, including guarantors.
Its thickness protects them as long as it retains
positive value.
I. MEASURING CAPITAL
  • When losses move through the Chain of Corporate
    Stakeholders in a workout situation, source of
    capital transitions from original owners to less
    and less senior creditors.
  • The Transitioning is governed by Enforceable
    Contracting Protections subordination
    covenants collateral escrowed balances.
    Enforceability varies across jurisdictions and
    contracting protocols.

3
A bank needs to post enough capital to support
its unhedged risks. Its depositors and other
stakeholders must be satisfied with the
combination of enterprise-contributed and
taxpayer risk capital that cushions or buffers
the net or enterprisewide risk exposure the bank
passes through to them.
Megatheme Risks that are Not Perfectly Hedged
Need Capital Support
4
In Oct. 1999, John Reed, then-CEO of Citigroup
said Our objective is to operate with more
capital than were going to need --ever- -so that
you never have to deal with the markets
perception of not having enough capital. Let me
tell you, Im going to be long dead before were
ever undercapitalized again.Lesson he learned
from the near-failure of a major hedge fund
concerns the necessity of looking at
second-order exposures to risks taken by the
banks counterparties Necessary capital is
that which is necessary to take a hit and still
be able to operate effectively within the
marketplace... Citicorp had no direct exposure
to Long-Term Capital Management, the hedge fund
that flirted with a failure in 1998. But
Citibank was the primary lender to half the
companies that came to Long-Term Capitals
rescue... None of these firms had the capital
to sustain the losses.
5
The Size of the Capital Shield Differs for
Different Stakeholders. Rules for Calculating
Thickness of Protection Vary for Differently
Prioritized Stakeholders in a Bank.
  • 1. For subordinated debtholders
  • 2. For foreign branch depositors and uninsured
    domestic depositors
  • 3. For FDIC.

6
WORKOUT EXAMPLE Crippled
Bank shows the following tangible Balance Sheet,
constructed according to GAAP.
7
  • Exercise Lets calculate the Capital Shield
    protecting various stakeholders (subordinated
    debtholders, uninsured depositors, BIF) assuming
    net intangible assets are worth 15 in market
    value and all tangible items are booked at market
    value
  • a. according to GAAP?
  • b. according to market-value accounting
    principles?
  • Suppose regulators apply an average risk weight
    of 90 percent to the banks tangible assets.
    Would the banks capital be adequate?
  • Suppose that the Market Value of the Banks
    assets is only 75.
  • How much of the banks GAAP assets would have to
    be sold to cover a 100 run by the uninsured
    depositors?
  • b. What would the banks GAAP balance sheet
    look like after paying off all uninsured
    deposits?
  • Under what circumstances would new stockholders
    be willing to invest in a bank that has fallen
    into tangible insolvency?

100 - 95
115 - 95
ANS. Each dollar of book value sold generates on
75, so 4(25)/3 in GAAP assets have to be sold.
ANS. Assets 66.67.TNW -3.33
8
Creditors May be Fooled by Accounting Façade that
Weak Banks Erect to Keep Capital Looking Good
Long After it is First Exhausted
9
Evidence on How Fast Capital Position Can Change
1999
10
FDIC Guarantees and other elements of the
Government Safety Net absorb some of each banks
risk Creditor protection KtKEtKGt.To
protect FDIC reserves and taxpayer wealth from
bank risk-shifting, government regulators engage
in various supervisory activities monitoring
(including on-site examinations) enforcing
risk-based requirements for minimum capital and
dividend restrictions issuing cease-and-desist
orders for unsafe and unsound practices
replacing poor or dishonest managers.
11
Both government and stockholder components of
Bank Capital lack transparency. We have covered
many ways FSFs can use accounting leeway to
confuse regulators and lessen the observability
of adverse changes in net worth
  • 1. Delay asset writedowns restructure hopeless
    loans
  • 2. Employ optimistic loss reserving
  • 3. Engage in gains trading or book nonrecurring
    items
  • 4. Deny materiality of adverse events
  • 5. Use residual Z tranches of securitizations
    and structured derivative transactions to mask
    losses and risk exposures.

12
Government Guarantees Negate the Pin-Prick Test
13
II. Basel Protocols Buy into a Dangerously
Inflexible Way to Assess Capital Adequacy
  • To keep government-contributed capital from
    trending upward, Regulators and Supervisors must
    continually adapt their rules, monitoring,
    penalties, and administrative procedures to
    overcome clients political clout and innovations
    in bank concealment capabilities.
  • RBC supervision has proved highly vulnerable to
    dynamic deterioration risk

14
Capital Regulation uses the Metaphor of a RISK
BUDGET that is Distributed over a series of RISK
BUCKETS
  • What is budgeted is ownership capital.
  • To support their net risks, management must hold
    sufficient capital and allocate it across the
    specific positions that expose the institution
    and its stakeholders to loss.
  • Modern regulators double-check the adequacy of a
    banks budget. They set and enforce risk-based
    minimum requirements for ownership capital.

15
  • In principle, the amount of an institutions
    enterprisewide exposure to loss in any asset or
    liability position (Ai or Lj) that capital
    should be asked to cover varies with the loss
    exposure of the asker. Each stakeholder may
    express its requests as fractions (wi) of each
    positions value 0?wi ?1.
  • Capital is adequate for a given stakeholder when
  • In practice, weights and position values are
    sensitive to correlations and hard-to-observe
    Information Events.

16
Besides Credit Risk, Capital Needs to Cover Other
Kinds of FSF Risks
  • CREDIT Risk that borrower will default.
  • LIQUIDITY Risk that bank wont meet its
    obligations without selling assets at
    below-market prices.
  • MARKET Risk from shifts in interest rates and
    foreign exchange rates.
  • PRICE Risk from changing values in securities
    portfolio
  • REPUTATION Risk of bad publicity.
  • STRATEGIC Risk of making bad business decisions.
  • OPERATIONAL Risk of trouble from inadequate or
    failed internal processes, people, and systems or
    from external events.
  • REGULATORY Risk of adverse changes in the Rules
    of the game

17
Shaping a Standard How the Basel II capital rule
has evolved
1999
2000
2001
2002
2003
July
April
June
Jan.
Final rule pushed back to yearend 03,
with implementation set for yearend 06
Third proposal released
First broad outline proposed
Second, more detailed plan released. Final rule
due yearned, to take effect in 04
Oct.
Final rule pushed back to mid-04, but late
06 effective date confirmed
April
First study of potential impact conducted
Oct.
June
Third impact study launched
Basel announces plans for a third proposal,
expected in early 02, and postpones
Source American Banker Online (10-21-03)
18
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19
Final outline of the new rules
20
  • Basel I and II require internationally active
    banks to set aside specified capital amounts to
    support their on-balance-sheet and
    off-balance-sheet risk exposures. BIS system
    seeks
  • (1) to impose comprehensive capital
    requirements (i.e., to factor in off-balance
    sheet risks) and
  • (2) to do so globally in standardized (i.e.,
    equal-opportunity) fashion in all major
    financial environments.
  • Previously, capital requirements had been linked
    exclusively to accounting measures of a banks
    total on-balance-sheet assets so that
    Off-Balance-Sheet items expanded.
  • Regulatory Intervention System of Risk-Based
    Capital Requirements (RBCR). Prior to RBC
    requirements, off-balance sheet activity avoided
    the burden of capital requirements on the
    business and the risks not being booked on
    balance sheet.

21
RBCR use simplistic ad hoc weights -- not
market-based weights
  • Authorities assigned a unit risk weight to
    ordinary private loans.
  • Judgmentally assign weights for other positions
    (vi) as fractions.
  • Risk-Weighted Assets (RWA)
  • Two-Tier RBCR w1 (RWA) and w2(RWA)

22
  • To risk-weight derivatives positions, a two-part
    method was used
  • 1) Choose a conversion factor, (ci) converting
    each OBS position to an on-balance-sheet credit
    equivalent.
  • 2) Then apply a judgmental credit-risk weight
    (vi) that determines a capital requirement
    appropriate for the credit-equivalent amount.

23
  • Except for swaps, conversion factors and risk
    weights are limited to 0, 20, 50, and 100.
  • No formal market testing is done to justify
    these conversion factors and risk weights.
  • Lack of accountability lets political pressure
    influence weighting. E.g., risk weights for
    subprime mortgages and for securities issued by
    national governments are kept unduly light.
  • RBCR are so simplistic that their burden is so
    easily circumvented that one has to challenge
    either the honesty or the competence of officials
    willing to rely predominantly on this supervisory
    protocol.

24
OBFUSCATION OF WEAKNESSES BY AUTHORITIES
WELL, YA BETTER LARN HOW IF YORE GONNA BE A
GOVERNMENT OFFICIAL !!
25
VaR
  • Mean-Variance Portfolio Theory has Spawned a
    Formal Theory of Risk Budgeting and Stress
    Testing whose Starting Point is a concept called
    Value-at-Risk VaR

VaR is the maximum potential loss in net
portfolio value (NW) that can occur over a
specific horizon (e.g., two weeks) at a specified
level of statistical confidence (e.g., 99) VaR
asks managers to locate a place in the negative
tail of the distribution of future returns
whose chance of occurrence is remote enough to
neglect. Idea is to capture a worst-case
scenario beyond which owners need not expect to
cover losses.
26
Weekly Profits and Losses of a Hypothetical
Financial InstitutionFrequency Distribution of
Weekly Results
Query Can you locate the 5 VaR for this
example?
of weeks
-15 -10 -5 0 5 10 15 20 25 30
35
27
Foundations
  • 1. Disaggregation of components of R Managers
    distinguish N profit centers, whose returns sum
    to the aggregate FSF Return Rt.
  • 2. Calculation Rt wjtRjt ideally,
    theportfolio weight wjt MVjt/MVt

28
Although it is an aggressive assumption, if
returns on individual positions follow a
stationary and joint normal distribution,
defining VaR is a straightforward statistical
exerciseVaR the mean return (?) minus c
standard deviations (c?).For 5 VaR, is c
1.95 or 1.69?Self-Study Query What does
stationarity entail?
29
The rub is that the true distribution of returns
is unknowable and varies over the business cycle.
At any point in time, its true mean (?) and true
standard deviation (?) can only be estimated.
Just as with Credit Scoring, the
comprehensiveness and relevance of the exercise
must be challenged.
  • Estimation imposes a demand for extensive input
    data
  • 1. The initial value, mean, and standard
    deviation of returns on every tangible and
    intangible position.
  • 2. A correlation matrix detailing how each
    return correlates with the others.

30
The methods assumptions are unduly strong and
unduly static
  • When the method is accepted without question,
    historical data can be used straightforwardly to
    estimate
  • Rj
  • ?j
  • ?ij
  • The this building-block information can be
    plugged into portfolio Rt and formulas.

However, the fragility of the underlying
assumptions require users to have better
understanding, expertise, and systems than their
staff may actually possess.
31
Pluses and Minuses of Using VaR?
  • A framework for Risk Budgeting and Stress
    Testing (as in treadmill testing for heart
    trouble)
  • VaR is an alleged bad case to worry about,
    calculated as the estimated loss that might occur
    in (say) 99 of all ten-day periods, e.g., 100
    million
  • Example JP Morgan once reported that its daily
    trading VaR averaged 15 million at a 95
    confidence level, i.e., it expected to lose 15
    mil. or more on 5 of all trading days
  • But it is not a worst case. It is the least of
    the worst cases. A potential source of false
    reassurance
  • 1) It omits the size of the exposure in the
    tail
  • 2) It neglects changes in correlations and
    volatility that might come into play
    in crisis episodes
  • 3) Blindness to periods beyond the horizon
  • 4) Neglects effects of collateral, insurance,
    etc.

32
A stress test examines an FSFs vulnerability to
particular categories of market events. It
estimates how the value of the firms positions
would change if an exceptional but plausible
change in market conditions were to occur. Each
hypothetical shock is based on a different
scenario and most useful for products and
markets for which VaR seems inadequate. Shocks
are usually sized with reference to historical
patterns of events in past crisis episodes. For
example, movements in interest rates or
credit-swap spreads during
1. The 1998 Russian Crisis 2. The 1987
stock market crash.
33
1995 Reform Basel Committee on Bank Regulation
Mandated Value at Risk (VaR) to Find Capital
Required to Cover Risk Exposure in Trading Book
  • The maximum of
  • the VaR computed yesterday, or
  • a 60-day moving average of VaR, multiplied by a
    constant whose minimum is 3.0
  • An additional charge for notable credit risks
  • Plus a penalty for observed inadequacies in
    internal VaR model (Ideally, the penalty
    structure should feed explicitly into return
    distributions used in VaR calculations.)

34
  • Like credit scoring and pvbp,VaR appears more
    elegant than it is. It actually represents a
    crude statistics-101 way for FSF managers to
    figure out how much capital they should hold to
    cover adverse movements in their institutions
    total return, Rt.
  • It is restrictive to measure an FSFs
    enterprisewide risk as the ? of its return
    distribution, ft(Rt), over a managerially-specifi
    ed time horizon, k.

35
  • The stationarity assumption lets us calculate VaR
    over a period of n days as vn times the daily
    VaR.
  • It is dangerous to assume that returns on every
    business day come as independent draws from the
    same distribution
  • Such an assumption neglects event risk and
    evidence of day-of-the-week and intraday effects

36
In practical applications, VaR focuses
principally on justifying a capital level by
itemizing and aggregating elements of credit risk
and IRR in a banks tangible positions over a
particular horizon k.
  • In most uses, VaR focuses on credit or market
    risk and pvbp of tangible positions and neglects
    operational risk (including ethical risk),
    liquidity risk, and risk due to
    underdiversification (concentration risk).
  • In the end, the reliability of VaR estimates
    depends on the sincerity with which data are
    collected, adjusted, and processed.
  • CROs are often told what the CEO wants the VaR to
    be.

37
VaR Can Measure Leverage Source Risk (July 2004)
38
Steps in Implementing VaR
  • Consolidate mark-to-market positions into one
    database
  • Set time horizon (period over which portfolio
    composition is presumed not to change)
  • Obtain necessary data
  • Generate and validate a frequency distribution
    of mark-to-market returns
  • Parametric (variance-covariance)
  • Historical
  • Stochastic simulation (Monte Carlo)
  • Historical simulation
  • Given confidence level, pinpoint the VaR and
    treat it as the endpoint of an out-of-sample
    fiducial interval

or combinations
39
Usefulness of VaR is Challenged by Stylized Facts
of Credit Losses
  • Credit loss distribution is highly asymmetric.
    Relatively fat-tailed.
  • Credit portfolios hard to trade/hedge, especially
    during bad times.
  • When storm comes, ride it out.
  • Observable credit events arrive at low frequency.
    Data sparse and badly measured
  • Implications
  • Sample should cover a long horizon, but one year
    is standard.
  • Direct validation of tail behavior impossible.

40
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41
  • ANSWER KEY TO EXERCISE FOR WEEK 11
  • Part a. Definition A quantile is a variate
    value that divides the density of a frequency or
    probability distribution of potential outcomes
    into specified proportions. For example, the 5th
    percentile of distribution is the value that
    partitions the density between the 5-percent
    lowest outcomes and the other 95 percent.
  • The X-percent VaR of a portfolio with a known
    distribution is the X-percent quantile of the
    probability distribution of returns over a given
    horizon. In practice where one works with an
    unknown distribution, VaR is estimated as the
    lower bound of a one-sided confidence interval.

42
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43
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44
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45
Dangers in using VaR may be likened to those in
setting up a VCR to record a program on a distant
day vs. TIVO. Four items must be set, knowing
that uncontrollable events like interim schedule
changes, power failures, or burglaries may foul
up the result
  • 1. A channel The frequency distribution over
    which we assume the signal of an FSFs net
    returns travel each day
  • 2. A targeted number of days ahead to ask the
    mechanism to look at the signal a cumulative
    return horizon of (say) 10 consecutive days
  • 3. An interval within which the channel is to be
    sampled as long as the signal remains above a
    management-selected cut-off level of tolerable
    deterioration
  • 4. A safe speed (safety factor) at which to spin
    the amount of tape available (capital) so it
    doesnt run out during the program.

46
Item 1. Verifying the choice of frequency
distribution assumed to govern daily returns is a
technical statistical issue.
  • Verification employs simulation or estimation
    techniques
  • Approximation error is inevitable and the size of
    such errors is seldom adequately researched

47
Many Institutions Use Their Own Historical
Profile of Weekly Profits and Losses Frequency
Distribution of Weekly Results
of weeks
-15 -10 -5 0 5 10 15 20 25 30
35
48
Item 2. In practice, choosing a return horizon
is a problem for joint managerial and regulatory
optimization. The horizon can be shorter
  • a. The less risk-averse managers happen to be
  • b. The more quickly and more cheaply management
    can raise outside capital to restore depletion in
    an institutions capital shield.

49
Item 3. Choosing the time when the machine turns
it self off is partly a technical statistical
issue and partly a matter of management tradeoffs.
  • a. Statistically, the cut-off level is a
    quantile or confidence bound that is
    calculated under the (unproven) assumption that
    daily returns are independently and identically
    distributed another under-researched source of
    approximation error.
  • b. The more risk averse is management and the
    higher the cost of raising additional capital
    quickly, the more conservatively the lower
    confidence bound (L) should be set
  • L ? - c?

50
Item 4. Regulators interpose a multiplicative
safety factor m (conventionally3) to require
capital to be several times the cutoff level of
tolerable losses over the target
horizon.Regulatory VaR
Statistical VaR
51
Simplistic Version of VaR is the Delta-Normal
Method. It aggressively assumes
  • 1. ft(Rt) is normal.
  • 2. ft(Rt) is stationary across time periods
  • ft(Rt) f(Rt)
  • 3. Returns on the firms individual positions
    Rjt(j1, , n) are independently and identically
    (normally) distributed (I.I.D) across time.
  • 4. Component building blocks of positions and
    activities that govern return generation are
    known and measurable.

52
How to Fulfill Informational Needs of
Delta-Normal VaR?
  • Query Can statistical staff estimate
  • , , and from historical
  • data?
  • ANS. Yes and no.

53
Why No? ANS Limitations
  • 1. What to do about new products, new business
    units, new competitors, etc? Weak history of data
    points for new items.
  • 2. Need to allow for known breakpoints in the
    FSFs strategy or implementation techniques.
  • Need to identify and correct for variation over
    time in the applicability of VaRs
    more-aggressive assumptions.
  • Limitations guarantee inaccuracy like using a
    one-inch ruler to measure a very large room.

54
It is dangerous to accept the methods
assumptions even with repeated sensitivity testing
  • 1. Normality econometric tests indicate that
    returns on financial instruments (esp., stock)
    are generally more fat-tailed than the normal.
  • 2. Stationarity econometric tests and
    commonsense indicate that information flows can
    change the true distribution of returns sharply
    and suddenly. Even assuming ft(Rt) were normal,
    future and past means, standard deviations, and
    correlations are subject to unpredictable jump
    shifts (also called event risk).
  • 3. Independence serial correlation of returns
    often exists inherent cyclicality in alternating
    gain and loss periods.
  • 4. Nonlinearities caps, floors, and
    optionality. The existence of customer rights to
    prepay loans, make early withdrawals from
    deposits, and to draw down credit lines in an
    opportunistic manner undermines all three
    assumptions.

55
  • VaR neglects strategic risks tradeoffs between
    short-term (i.e., within the selected horizon)
    and long-term effects of managerial strategies on
    a banks creditworthiness structure and KGt.
  • Lack of Robustness VaR fails to incorporate the
    exposures and penalties that arise when lower
    bound is violated.
  • Scenario Analysis uses additional Ad Hoc Stress
    Tests as a crude way to address VaRs weaknesses.

56
In Making VaR a Rising Star, Regulators May or
May not Have Good Intentions
57
PROPERTIES THAT HAVE MADE VaR A STAR
  • A single number
  • Reproducible and understandable
  • Quantifies the risk of entire portfolio
  • Accounts for interactions among assets
  • Acceptance by regulators makes it the de facto
    standard for measuring market risk

58
Lets Compare it to Longins Supplement BVaR
Why VaR is also a Dim Star
  • BVaR accounts for the size of expected losses
    beyond the VaR
  • But BVaR is also a function of assumed
    probability density function of return fR and
    confidence level set in VaR calculation.

59
  • The denominator is the selected tail
    probability.
  • If tail probability is low, but LGD is high,
    ranking on BVaR will be much worse than ranking
    on VaR

60
  • BVaR resembles (1-s) in credit-risk calculations.
    It puts the magnitude of extreme losses into the
    control strategy.
  • For Fat-Tailed distributions, BVaR is critical
    because the difference between BVaR and VaR
    increases with tail thickness and may not
    disappear asymptotically with increases in the
    confidence level.

61
Suppose (1) The one-percent 60-day VaR for Banks
A and B is 50 mil for both banks (2) But the
conditional expectation of bank B is twice that
of Bank A. Then the BVaR of Bank B will also be
twice the BVaR of Bank A.
62
IV. Three Policy Issues In Relying On This System
  • Issue A Is it safe for Regulators to Allow Bank
    Discretion to Estimate own VaR?
  • Historical Method
  • A sample of past periods (at least one year
    according to 1995 Basel Committee)
  • Empirical estimation of volatilities and
    correlations, perhaps over broad asset categories
  • Prospective Method
  • Forecast values of volatilities and correlations
    based on predictions from an FSFs own
    internally developed econometric model
    (required for top 10 banks and allowed for
    others).

63
  • Reliance on internal models puts an intolerable
    weight on individual and firm ethics.
  • External credit ratings (CRt) are a
    single-dimensional proxy for an institutions
    creditworthiness structure, are produced by
    conflicted parties, and do not identify the
    relative roles played by KGt and KEt in
    supporting CRt.
  • (A proxy stands in for an unobservable variable
    that it is imperfectly correlated with).

64
A banks economic capital is the sum of its
enterprise-contributed capital (KEtMVTtEit) and
government-contributed risk capital (KGt).
  • Neither KEt or KGt is observable without error.
  • Policy Concern Banks can extract hard-to-verify
    increases in KGt by engaging in clever forms of
    dealmaking and by cooking internal models to
    plausibly understate effects on KG.

65
For each future date tk, VaR analysis maps a
banks economic capital (Kt) into a particular
probability pp(k,Kt) of becoming unable to
cover its liabilities at a particular date tk
e.g., p might equal .0001 for a horizon k of 6
months.For fixed Kt, p(k,Kt) implicitly
establishes a term structure of bank default
probability over the full range of possible
horizons but incorporates no vector of LGDs.
Focus On Single Horizon Is MYOPIC
66
Issues Verification and Validation
  • Bank managers would prefer a particular mix of KE
    and KG. Often, this entails a higher level of KG
    than a perfectly informed regulator could or
    would openly approve Rent-seeking
  • Regulators are asked to devise and enforce
    capital requirements to guard against their being
    gamed by internal models.
  • Banks need only claim to have validated their VaR
    models. Regulators lack tools for verifying such
    claims.

67
Issue B. Even if VaR were perfectly measured,
Does it measure what Regulators Need to
Measure?VaR is only a starting point. The
continuing challenge for regulators in this Game
of Cat and Mouse is to incent the industry and
their own staffs to devise better and better
definitions, indices, and strategies for
measuring and controlling enterprisewide risk and
KG.
68
Advances in Risk Management Come from Advances in
Understanding and Measuring Risk
Level of Sophistication
V
VAR stress tests
IV
Portfolio Risk/Return
Finance Theory
III
Scoring Expected Loss
II
Generators of Improvements
Information Technology
Formal Loan Rating
I
Development Path
Subjective Instincts
time
69
Regulatory Dialectic continually revises the
Contractual Architecture for Distributing
Possible FSF losses.
  • Persistent use of any loopholes eventually
    triggers regulatory response. Basel II proposals
    focus on revising system negotiated at the BIS in
    Basel during 1987-1988 to close some of the
    loopholes authorities have observed since.

70
Reasonableness of Hoping for a Clean Getaway
Feeds Policy Delays, Creating a Long Reregulation
Lag
71
Basels Reregulation Lag Not until 6-99 did
Basel Committee on Banking Supervision Formally
Propose
  • to introduce external credit risk assessments
    from credit rating agencies so as to reduce risk
    weights for high-quality corporate credits
  • to treat structured securitization, noncredit
    risk, and risk mitigation in a more satisfactory
    way and
  • to set standards for individual-bank disclosure
    of derivative positions for internal
    capital-assessment procedures and for
    operational-risk controls.

72
Issue C Three Obvious and Large Loopholes in RBCR
  • 1. Risk weights focus on credit risk (rather
    than firm-wide risk) and are too few in number
    to track the capital needed to support individual
    positions.
  • 2. Regulatory requirements are set much too high
    on safe instruments and much too low on very
    risky ones.
  • 3. Regulatory Dialectic authorities lag behind
    the market in understanding how to analyze
    supervise the values and risks of complicated
    derivatives.
  • Weaknesses in rules induce a mutation of
    derivatives that resembles mutation of bacteria
    to make antibiotics ineffective on them.

73
Regulatory Arbitrage
Capital Ratio
Market vs. BIS Capital Requirements
Hypothetical Market Requirements
too low
BIS Minimum
4
too high
too high
Middle Market Business
Closely Followed Large Corporations
Prime Households
Small Business
Borrower Size
74
Even with a specified horizon and confidence
level, regulatory VaR can be made as low as
managers want it to be.
  • Arbitrage Opportunity No. 1 Identify and hold
    assets with low regulatory charges relative to
    the risks they pose.
  • Arbitrage Opportunity No. 2 Unscrupulously
    manipulate unverifiable internal Value-at-Risk
    models for self-assessing risk exposure to
    understate need for capital. Another form of
    accounting gimmickry.

75
  • Imperfections in enforcement open and solidify
    Avoidance Opportunities that make the hypothesis
    that most banks would crunch profitable but
    risky opportunities seem awfully naïve.
  • The naïveté lies in the twin presumptions that
    accounting ratios are difficult to misrepresent
    and that banks passively accept statutory burdens
    rather than work to adjust their risk profile to
    minimize the net effect on RBC system bank
    profits and market capitalization.

76
Bank Responses to Basel I Range Across a Spectrum
  • Some healthy banks held enough risky assets at
    the outset that the market made them hold ratios
    of LLR plus Book NW to Risk-Weighted Assets (kM)
    that approach the regulatory minimum kR. These
    banks increased accounting capital by reducing
    LLR.
  • At the other extreme, healthy banks holding
    substantial amounts of low-risk assets did not
    need capital to close the gap between kM and kR.
    They could meet the requirements by securitizing
    safe assets and adding some risky ones. This may
    be expected to raise their loan-to-asset ratios
    (U.S.).
  • N.B. If the costs of offloading safe assets and
    assuming new risks were zero, both types of banks
    would wipe out the burden of risk-based capital
    requirements completely and at no cost.

77
Proposed Basel II More Weights Categories
External Credit Rating (e.g., Standard Poors)
vs. use of internal systems to gauge risk and
set capital levels
78
HISTORICAL CORRELATION BETWEEN CREDIT RATINGS AND
DEFAULT RATES
Source Adapted by Jorion from Moodys default
rates from 1920-1998.
79
Self-Study for Ph.D Students Only Fatal Flaw
Mapping Between Capital set by VaR or BVaR Lacks
Coherence as Measure of Risk Passed Through to
Deposit Insurers
The concept of coherence of risk measures states
four desirable properties for a risk measure to
possess (Artzner et al, 1999). Let Xf represent
the amount of a banks net worth that is held in
a perfectly hedged position. With random
variables X1, X2 representing the future net
worths of two banks, the four properties can be
envisioned as tests the FDIC would ideally like
a risk measure ? to pass
Subadditivity Monotonicity Linear
Homogeneity Translation invariance
Query Which tests does VaR fail?
80
Consequences of Normality and I.I.D Assumptions
Self-Study
  • 1. is a quadratic form
  • 2. ?t the variance-covariance matrix of
    position returns ?t is diagonal only if returns
    are not correlated across positions

81
Consequences of Stationarity
Self-Study
  • 1. One can suppress the subscript t.
  • Choosing a longer decisionmaking horizon
    predictably increases the ? that applies (as
    opposed to subjectively having to make increasing
    allowances for extrapolation error).
  • Permits the extrapolation VaR (n days)
  • (vn) times the daily VaR.

82
VaR and Kurtosis
Self-Study
  • Most VaR models conveniently and inappropriately
    assume
  • normal distributions for daily returns
  • stationary means, volatilities, and correlations
  • Kurtosis (peakedness) unambiguously causes a
    serious understatement in VaR
  • Relaxing any of the aggressive assumptions
    implies that the true tail probability and
    expected loss given VaR violation are much
    higher than the normal distribution would imply
    (Key).

83
Methods for Sensitivity-Testing VaR Models
Self-Study
  • 1. Back testing of model fit against history.
  • 2. Forward-looking stress testing of predicted
    responses
  • a. To variation in doubtful assumptions
  • b. To extreme movements in particular sources of
    risk (scenario analysis designed to identify
    potential nonlinearities)
  • 3. Testing for dangerous ethical interfaces How
    can unit or division managers distort measures
    and tests in their favor?
  • 4. Supplementation because VaR is not additive
    across stakeholders, shifting of risks to other
    parties needs to be assessed.
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