financial risk management

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FRM http:// pluto.mscc.huji.ac.i l/~mswiener/zvi.html HUJI-03 Zvi Wiener mswiener @ mscc . huji .ac. il 02-588-3049 Financial Risk Management

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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 Presentation

TRANSCRIPT

Page 2: 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

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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

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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.

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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

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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

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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

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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

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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

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Home assignment

Read chapters 1-3, pay attention to boxes.

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The end