financial risk management
DESCRIPTION
Financial Risk Management. Zvi Wiener [email protected] 02-588-3049. Financial Risk Management. Zvi Wiener Head of Finance Department The Hebrew University of Jerusalem 02-588-3049, [email protected]. Arik Perez [email protected] tel. 050-412-733, 02-531-7751. Statistics. - PowerPoint PPT PresentationTRANSCRIPT
FRM http://pluto.mscc.huji.ac.il/~mswiener/zvi.html
HUJI-03
02-588-3049
Financial Risk Management
Zvi Wiener VaR-PJorion-Ch1-3 slide 2
Financial Risk ManagementZvi Wiener
Head of Finance DepartmentThe Hebrew University of Jerusalem
02-588-3049, [email protected]
Arik [email protected]
tel. 050-412-733, 02-531-7751
Zvi Wiener VaR-PJorion-Ch1-3 slide 3
Statistics
Random variables Mean, Standard Deviation, Correlation Normal distribution
BABA
BABABA 222222
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Basic Corporate Finance
NPV, IRR, YTM Assets, Liabilities Regulators, Bank of Israel, MOF ISDA, SEC
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Investments Stocks, Indices, , CAPM, Bonds, duration, convexity
NIS, CPI linked callable, puttable, convertible
Forwards, Futures, Swaps Options,
European, American Call, Put, BS formula
Markets: prices, volatilites, LIBORs, swap rates
FRM http://pluto.mscc.huji.ac.il/~mswiener/zvi.html
HUJI-03
Following P. Jorion, Value at Risk, McGraw-HillChapter 1
The Need for Risk Management
Financial Risk Management
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Financial Risks
Risk is the volatility of unexpected outcomes.
Business RiskFinancial RiskLegal Risk Operational Risk
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Analytic Risk Management Tools
Duration 1938Markowitz mean-variance 1952Sharpe’s CAPM 1963Multiple factor models 1966Black-Merton-Scholes model 1973RAROC 1983Limits by duration buckets 1986
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Analytic Risk Management Tools
Risk-weighted assets (banks) 1988Stress Testing 1992Value-at-Risk, VaR 1993RiskMetrics 1994CreditMetrics 1997Integration of credit and market 1998-Enterprisewide RM 2000-
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Derivatives and Risk Management
Stocks and bonds are securities – issued to raise capital.
Derivatives are contracts, agreements used for risk transfer.
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Financial Derivatives
Futures, Forwards, Swaps
OptionsEuropean, American, Asian, ParisianCall, PutCap, Floor
Credit derivatives
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Types of Financial Risks
Market Risk
Credit Risk
Liquidity Risk
Operational Risk
Legal Risk
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What is the current Risk?
duration, convexityvolatilitydelta, gamma, vegaratingtarget zone
Bonds Stocks Options Credit Forex
Total ?
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Standard Approach
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Modern Approach
Financial Institution
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Example
You live in Herzliya and work in Tel-Aviv.
When do you have to leave your home to be at work at 8:30?
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How much can we lose?
Everything
correct, but useless answer.
How much can we lose realistically?
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Definition
VaR is defined as the predicted worst-case
loss at a specific confidence level (e.g. 99%)
over a certain period of time.
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Definition (Jorion)
VaR is the worst loss over a target horizon
with a given level of confidence.
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-3 -2 -1 1 2 3
0.2
0.4
0.6
0.8
1
Profit/Loss
VaR
1% VaR1%
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Meaning of VaRA portfolio manager has a daily VaR equal
$1M at 99% confidence level.
This means that there is only one chance in 100 that a daily loss bigger than $1M occurs,
1%VaR
under normal market conditions.
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Returns
year
1% of worst cases
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Main Ideas
A few well known risk factors
Historical data + economic views
Diversification effects
Testability
Easy to communicate
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Conventional Analysis
Risk factor
$ value
sensitivity
scenarios
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VaR approach
Risk factor
$
yield
price
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Important
VaR is a necessary, but not sufficient procedure for controlling risk.
It must be supplemented by limits and controls, in addition to an independent risk-management function.
Sound risk-management practices.
FRM http://pluto.mscc.huji.ac.il/~mswiener/zvi.html
HUJI-03
Following P. Jorion, Value at Risk, McGraw-HillChapter 2
Lessons from Financial Disasters
Financial Risk Management
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Derivatives 1993-1995
($ million)Shova Shell, Japan 1,580Kashima Oil, Japan 1,450Metallgesellschaft 1,340Barings, U.K. 1,330Codelco, Chile 200Procter & Gamble, US 157
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Public Funds
($ million) Orange County 1,640 San Diego357 West Virginia 279 Florida State Treasury 200 Cuyahoga County 137 Texas State 55
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Barings
February 26, 1995
233 year old bank
28 year old Nick Leeson
$1,300,000,000 loss
bought by ING for $1.5
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Metallgesellshaft
14th largest industrial group 58,000 employees offered long term oil contracts hedge by long-term forward contracts short term contracts were used (rolling hedge) 1993 price fell from $20 to $15 $1B margin call in cash
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Orange County
Bob Citron, the county treasures
$7.5B portfolio (schools, cities)
borrowed $12.5B, invested in 5yr. notes
interest rates increased
reported at cost - big mistake!
realized loss of $1.64B
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Daiwa12-th largest bank in Japan
September 1995
Hidden loss of $1.1B accumulated over 11 years
Toshihide Igushi, trader in New York
Had control of front and back offices
In 92 and 93 FED warned Daiwa about bad management structure.
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Big Losses
Bank Negara, Malaysia $3B 92Banesto (Spain’s 5th bank) $4.7B 93Credit Lyonnais $15B 94S&L short deposits, long loans $150 80sJapan $550 90s
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ResponsesG-30 reportDPG = Derivatives Policy Group, risk.ifci.ch
JPMorgan’s RiskMetrics www.riskmetrics.com GARP www.garp.com PRMIA www.prmia.org
GAO = General Accounting Office, www.gao.gov/reports.htm FASB FAS 133 www.fas133.com, FAS 107IASC, IAS 39 www.iasc.org.uk SEC = Securities and Exchange Commissionwww.sec.gov/rules/final/33-7386.txt
FRM http://pluto.mscc.huji.ac.il/~mswiener/zvi.html
HUJI-03
Following P. Jorion, Value at Risk, McGraw-HillChapter 3
Regulatory Capital Standards with VaR
Financial Risk Management
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Why regulation?ExternalitiesDeposit insuranceMoral hazard – less incentives to control riskBasel Accord 1988measure of solvency = Cooke ratio
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Cooke ratioThe Basel Accord requires capital to be at least 8% of the total risk-weighted assets of the bank.
Capital definition is broad:Tier 1. Stocks, reserves (retained earnings) ( 50%)Tier 2. Perpetual securities, undisclosed reserves, subordinated debt >5 years.
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Weights Asset Type
0% CashClaims on OECD central governmentlocal currency claims on central banks
20% Cash to be receivedOECD banks and regulated securities firmsnon-OECD banks below 1 yearmultilateral development banksforeign OECD public sector entities
50% residential mortgage loans
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Weights Asset Type100% Claims on private sector (corp. debt, equity…)
Claims on non-OECD banks above 1 yearReal estatePlant and equipment
At national discretion0-50% Claims on domestic OECD public-sector entities
OECD (Organization for Economic Cooperation and Development): Austria, Belgium, Canada, Denmark, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, The Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, UK, Japan, Finland, Australia, New Zealand, Mexico, Czech Republic, Hungary, Korea and Poland.
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Credit Risk Charge
iii assetwCRC %8
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Activity Restrictions
Restrictions on large risks (over 10% of capital)must be reportedover 25% prohibitedtotal of large risks can not exceed 8*capital
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Criticism of 1988 Approach
Regulatory arbitrage (securitization)Credit derivativesInadequate differentiation of credit risksNon-recognition of term structure effectNon-recognition of risk mitigationNon-recognition of diversificationNon-recognition of market risk
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Market Risk Amendment 1996
Trading book – financial instruments that intentionally held for short-term resale and are typically marked-to-market
Banking book – other instruments, like loans.
TRC = CRC + MRCTier 3 capital: short-term subordinated debt (must be less than 2.5*Tier1)
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The Standardized Model
Maturity bandsPartial nettingDuration weightsNo diversification across risks
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The Internal Models Approach
Quantitative parameters for VaR10 business days or 2 weeks99% confidence levelat least one year of historical data updated at least quarterly
Treatment of correlations – can be recognized
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1 day can be scaled by square root of 10Typically average times k is used.k initially is set to 3, but later it can be increasedSpecific Risk Charge SRC is added.
ti
titt SRCVaRVaRkMaxMRC
60
11,
60
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Basel Rules MRC
Market Risk Charge = MRC
SRC - specific risk charge, k 3.
tti
itt SRCVaRVaRkMaxMRC
1
60
1
,60
10%)99,1( dVaRVaR tt
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BacktestingVerification of Risk Management models.
Comparison if the model’s forecast VaR with the actual outcome - P&L.
Exception occurs when actual loss exceeds VaR.After exception - explanation and action.
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Stress
Designed to estimate potential losses in abnormal markets.
Extreme eventsFat tails
Central questions:How much we can lose in a certain scenario?What event could cause a big loss?
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Further development
Basel IIBetter treatment of credit riskOperational risk
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Non banks
Securities FirmsInsurance companiesPension fundsSEC reporting 7A in 10K
בארץ – ועדת גלאי – דיווח איכותי, אחר כך כמותי
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FRM-99, Question 89What is the correct interpretation of a $3 overnight VaR figure with 99% confidence level?
A. expect to lose at most $3 in 1 out of next 100 daysB. expect to lose at least $3 in 95 out of next 100 daysC. expect to lose at least $3 in 1 out of next 100 days D. expect to lose at most $6 in 2 out of next 100 days
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FRM-99, Question 89What is the correct interpretation of a $3 overnight VaR figure with 99% confidence level?
A. expect to lose at most $3 in 1 out of next 100 daysB. expect to lose at least $3 in 95 out of next 100 daysC. expect to lose at least $3 in 1 out of next 100 days D. expect to lose at most $6 in 2 out of next 100 days
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Properties of Risk Measure
Monotonicity (X<Y, R(X)>R(Y))
Translation invariance R(X+k) = R(X)-k
Homogeneity R(aX) = a R(X) (liquidity??)
Subadditivity R(X+Y) R(X) + R(Y)
the last property is violated by VaR!
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No subadditivity of VaR
Bond has a face value of $100,000, during the target period there is a probability of 0.75% that there will be a default (loss of $100,000).Note that VaR99% = 0 in this case.
What is VaR99% of a position consisting of 2 independent bonds?
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FRM-98, Question 22Consider arbitrary portfolios A and B and their combined portfolio C. Which of the following relationships always holds for VaRs of A, B, and C? A. VaRA+ VaRB = VaRC
B. VaRA+ VaRB VaRC
C. VaRA+ VaRB VaRC
D. None of the above
Zvi Wiener VaR-PJorion-Ch1-3 slide 59
FRM-98, Question 22Consider arbitrary portfolios A and B and their combined portfolio C. Which of the following relationships always holds for VaRs of A, B, and C? A. VaRA+ VaRB = VaRC
B. VaRA+ VaRB VaRC
C. VaRA+ VaRB VaRC
D. None of the above
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Confidence level
low confidence leads to an imprecise result.
For example 99.99% and 10 business days will require history of100*100*10 = 100,000 days in order to have only 1 point.
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Time horizonlong time horizon can lead to an imprecise result. 1% - 10 days means that we will see such a loss approximately once in 100*10 = 3 years.
5% and 1 day horizon means once in a month.
Various subportfolios may require various horizons.
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Time horizon
When the distribution is stable one can translate VaR over different time periods.
TdayVaRdaysTVaR )1()(
This formula is valid (in particular) for iid normally distributed returns.
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FRM-97, Question 7To convert VaR from a one day holding period to a ten day holding period the VaR number is generally multiplied by: A. 2.33B. 3.16C. 7.25D. 10
Zvi Wiener VaR-PJorion-Ch1-3 slide 64
FRM-97, Question 7To convert VaR from a one day holding period to a ten day holding period the VaR number is generally multiplied by: A. 2.33B. 3.16C. 7.25D. 10
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Home assignment
Read chapters 1-3, pay attention to boxes.
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The end