Measuring and Managing Market Risk Flashcards

1
Q

An advantage of statistical factor models

A

They make minimal assumptions.

However, the interpretation of statistical factors is generally more difficult than the interpretation of macroeconomic and fundamental factor models.

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2
Q

Assumption of CAPM

A
  • Perfect competition - Frictionless and can borrow a the RfR
  • Rational, mean-variance optimizer
  • Perfect information (same variance and covariance matrix)
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3
Q

What is the purpose of VaR

A

Value at Risk is to capture market risk.

Equity prices
Commodity prices
Forex
Interest rates

Does not tell about about average loss

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4
Q

How to interpret a one day 95% VaR

A

95% confidence that we will NOT lose more than … per day

with 95% probability, we will experience a maximum loss of …

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5
Q

How to interpret 5% VaR

A

The 5% minimum loss of a portfolio over a 1 day period

or…

A expected loss of … to occure every 20 days (depend on duration)

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6
Q

3 different ways to estimate VaR

A

Parametric method
Historical simulation method
Monte Carlo Simulation

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7
Q

Explain Parametric Method

A

Variance - Covariance method
Begins with risk decomposition of the portfolio holdings
Assumes return distribution for risk factor is normal distributed
We need expected returns and standard deviation of portfolio

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8
Q

Calculate VaR for parametric method

A

[Expected return - Z* Portfolio standard dev]*(-1) * Pv

Z = Standard deviation number

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9
Q

Pros and Cons of parametric method

A

Pro: Simple and straightforward

Con: VaR is very sensitive to expected returns and standard deviation
Difficult to use of portfolio contains options since it threatens normality. Options have a non normal payoff function.

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10
Q

Historical simulation method

A

We set / construct a portfolio with fixed weights
We measure portfolio return over the observed period
We then rank the portfolio returns from smallest to largest
We then use percentile to find 1,5,10 % VaR

  • I we have 500 observation, and we want to find 5% VaR, the 25th observation os our 5% VaR

.

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11
Q

Brief characteristics of historical simulation method

A

Not constrained by normality assumption
Estimates VaR based on what actually happened
Can handle any kind of financial instruments

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12
Q

Monte Carlo Simulation

A

Not constrained by any distribution - We can define the distribution

Avoids complexity of parametric method when portfolio has many risk factors

Calculating VaR is the same as historical method

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13
Q

Conditional VaR - CVaR

A

Relies on a particular VaR measure - Average loss greater than our particular VaR measure.

average loss on the condition that VaR > Cut off

Informs us about average loss

Typically obtained by backtesting

Also known as Expected tail loss or expected shortfall

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14
Q

Incramental VaR - IVaR

A

How VaR will change if a position size changes relative to the remaining position.

example:
SPY - 80 % weight - > 90% weight
LWC - 20 % weight -> 10% Weight

VaR 2,407,503 -> 2,733,722

IVaR = 2,733,722 - 2,407,503 = 326,192

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15
Q

Marginal VaR - MVaR

A

Conceptually the same to IVaR, but reflects the effects of a very small change in a position - 1 unit change in position.

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16
Q

Relative VaR - Ex Ante tracking error

A

The degree to which the performance of a given portfolio might deviate from a benchmark.

Portfolio vs Benchmark

17
Q

What is Sensitivity risk measure

A

Examines how performance responds to a single change in an underlying risk factor.

Remember; How SENSITIVE a FACTOR is to a change

18
Q

What is scenario risk measure

A

Estimates the portfolio returns that would result from a hypothetical change in the market or historical events.

Scenario = What if something was different

Scenario = What if something was different

19
Q

Sensitivity and Scenario vs VaR

A

VaR: measure of loss and probability of large loss

SS: Change in the value of an asset in response tp a change in something else

VaR: Uses market returns from a look back period

SS: Uses market returns from a specific unrepresentative time period

20
Q

Constraints in measuring and managing market risk

A

Risk Budgeting
Position Limits
Scenario Limits
Stop-loss Limits

21
Q

Explain the following constraint - Risk Budgeting

A

Total risk appetite allocated to sub activities

22
Q

Explain the following constraint - Position Limits

A

A control on overconcentration

23
Q

Explain the following constraint - Scenario Limits

A

A limit on the estimated loss for a gain scenario

24
Q

Explain the following constraint - Stop-loss Limits

A

When a loss of a particular size occurs in a specific period - reduce or liquidate portfolio position.

25
Q

Name the 3 factors that influence the types of risk measuers

A
  1. Degree of leverage
  2. Mix of risk factor exposure
  3. Accounting / Regulatory requirement
26
Q

surplus at risk in regards to VaR

A

How assets might underperform to their liabilities.

Surplus at risk is an application of VaR; it estimates how much the assets might underperform the liabilities with a given confidence level, usually over a year

27
Q

Liquidity Gap

A

Relevant to the banks.
Liquidity between the assets and liabilities.
How quickly can I get cash for my assets to pay my liabilities?

28
Q

Is credit spread a market risk sensitivity measure?

A

No it is not!!!

29
Q

Risky financial assets tend to display

A

High returns when the marginal value of consumption is low.

and

Low returns when the marginal value of consumption is high.

30
Q

What is the difference between the nominal and risk free interest rate?

A

Break-even inflation rate

31
Q

The component of the discount rate that is most viable between asset class and another is the ..

A

Risk preimiums related to cash flow uncertainity.

The size of the risk premiums will vary among asset classes and the variation is largely resposnible for the distinction between one asset class and another.

32
Q

Amount of standard deviation 1% VaR

A

2.33 Sdv

33
Q

Amount of standard deviation 5% VaR

A

1.65 Sdv

34
Q

VaR at 1 Standard deviation

A

16% VaR