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Zvi Wiener

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Ho-Lee term-structure model ... A plausible stochastic process for the short-term rate is often considered to be ... The value of an Asian option on the short rate. ... – PowerPoint PPT presentation

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Title: Zvi Wiener


1
Financial Risk Management
  • Zvi Wiener
  • Following
  • P. Jorion, Financial Risk Manager Handbook

2
Chapter 4Quantitative AnalysisMonte Carlo
Methods
  • Following P. Jorion 2001
  • Financial Risk Manager Handbook

3
Monte Carlo
4
Monte Carlo Simulation
5
Simulating Markov Process
  • The Wiener process

The Generalized Wiener process
The Ito process
6
The Geometric Brownian Motion
Used for stock prices, exchange rates. ? is the
expected price appreciation ? ?total - q. S
follows a lognormal distribution.
7
The Geometric Brownian Motion
8
value
time
9
Simulating Yields
  • GBM processes are widely used for stock prices
    and currencies (not interest rates). A typical
    model of interest rates dynamics

10
Simulating Yields
  • ? 0 - Vasicek model, changes are normally
    distr.
  • ? 1 - lognormal model, RiskMetrics.
  • ? 0.5 - Cox, Ingersoll, Ross model (CIR).

11
Other models
  • Ho-Lee term-structure model
  • HJM (Heath, Jarrow, Morton) is based on forward
    rates - no-arbitrage type.
  • Hull-White model

12
FRM-99, Question 18
  • If S and Q follow a geometric Brownian Motion
    which of the following is true?
  • A. Log(SQ) is normally distributed
  • B. SQ is lognormally distributed
  • C. SQ is normally distributed
  • D. S Q is normally distributed

13
FRM-99, Question 19
  • Considering a one-factor CIR term structure model
    and the Vasicek model
  • I. Drift coefficients are different
  • II. Both include mean reversion
  • III. Coefficients of the stochastic term, dz, are
    different.
  • IV. CIR is a jump-diffusion model.
  • A. All of the above is true
  • B. I and III are true
  • C. II, III, and IV are true
  • D. II and III are true

14
FRM-99, Question 19
  • Considering a one-factor CIR term structure model
    and the Vasicek model
  • I. Drift coefficients are different
  • II. Both include mean reversion
  • III. Coefficients of the stochastic term, dz, are
    different.
  • IV. CIR is a jump-diffusion model.
  • A. All of the above is true
  • B. I and III are true
  • C. II, III, and IV are true
  • D. II and III are true

15
FRM-99, Question 25
  • The Vasicek modle defines a risk-neutral process
    for r which is dra(b-r)dt ?dz, where a, b, and
    ? are constants, and r represents the rate of
    interest. From the equation we conclude that the
    model is a
  • A. Monte Carlo type model
  • B. Single factor term structure model
  • C. Two-factor term structure model
  • D. Decision tree model

16
FRM-99, Question 26
  • The term a(b-r) in the equation
  • dra(b-r)dt ?dz, represents which term?
  • A. Gamma
  • B. Stochastic
  • C. Mean reversion
  • D. Vega

17
FRM-99, Question 30
  • For which of the following currencies would it be
    most appropriate to choose a lognormal interest
    rate model over a normal model?
  • A. USD
  • B. JPY
  • C. DEM
  • D. GBP

18
FRM-99, Question 30
  • For which of the following currencies would it be
    most appropriate to choose a lognormal interest
    rate model over a normal model?
  • A. USD
  • B. JPY
  • C. DEM
  • D. GBP

19
FRM-98, Question 23
  • Which of the following interest rate term
    structure models tends to capture the mean
    reversion of interest rates?
  • A. dra(b-r)dt ?dz
  • B. dradt ?dz
  • C. drardt ?dz
  • D. dra(r-b)dt ?dz

Bad question
20
FRM-98, Question 24
  • Which of the following is a shortcoming of
    modeling a bond option by applying Black-Scholes
    formula to bond prices?
  • A. It fails to capture convexity in a bond.
  • B. It fails to capture the pull-to-par effect.
  • C. It fails to maintain the put-call parity.
  • D. It works for zero-coupon bond options only.

21
FRM-00, Question 118
  • Which group of term structure models do the
    Ho-Lee, Hull-White and Heath, Jarrow, Morton
    models belong to?
  • A. No-arbitrage models.
  • B. Two-factor models.
  • C. Log normal models.
  • D. Deterministic models.

22
FRM-00, Question 118
  • Which group of term structure models do the
    Ho-Lee, Hull-White and Heath, Jarrow, Morton
    models belong to?
  • A. No-arbitrage models.
  • B. Two-factor models.
  • C. Log normal models.
  • D. Deterministic models.

23
FRM-00, Question 119
  • A plausible stochastic process for the short-term
    rate is often considered to be one where the rate
    is pulled back to some long-run average level.
    Which one of the following term structure models
    does NOT include this?
  • A. The Vasicek model.
  • B. The Ho-Lee model.
  • C. The Hull-White model.
  • D. The Cox-Ingersoll-Ross model.

24
FRM-00, Question 119
  • A plausible stochastic process for the short-term
    rate is often considered to be one where the rate
    is pulled back to some long-run average level.
    Which one of the following term structure models
    does NOT include this?
  • A. The Vasicek model.
  • B. The Ho-Lee model.
  • C. The Hull-White model.
  • D. The Cox-Ingersoll-Ross model.

25
Simulations for VaR
  • Choose a stochastic process
  • Generate a pseudo-sequence of variables
  • Generate prices from these variables
  • Calculate the value of the portfolio
  • Repeat steps above many times
  • Calculate VaR from the resulting distribution of
    values.

26
Risk-neutral approach
  • Standard approach assumes some risk aversion and
    utility function.
  • Risk neutral approach - change probabilities in
    order to get

27
Accuracy
  • Sampling variability

Antithetic Variable Technique Control Variable
Technique Quasi-Random Sequences
Very difficult to use for American types.
28
Monte Carlo
29
Monte Carlo
30
Monte Carlo
31
Monte Carlo
32
Speed of convergence
Whole circle
Upper triangle
33
Smart Sampling
34
Spectral Truncation
35
Regular Grid
  • An alternative to MC is using a regular grid to
    approximate the integral.
  • Advantages
  • The speed of convergence is error1/N.
  • All areas are covered more uniformly.
  • There is no need to generate random numbers.
  • Disadvantages
  • One cant improve it a little bit.
  • It is more difficult to use it with a measure.

36
FRM-99, Question 8
  • VaR of a portfolio was estimated with 1,000
    independent log-normally distributed runs. The
    standard deviation of the results was 100,000.
    It was then decided to re-run the VaR calculation
    with 10,000 independent samples. The standard
    deviation of the result
  • A. about 10,000 USD
  • B. about 30,000 USD
  • C. about 100,000 USD
  • D. can not be determined from this information

37
FRM-98, Question 34
  • The value of an Asian option on the short rate.
    The Asian option gives the holder an amount equal
    to the average value of the short rate over the
    period to expiration less the strike rate. With a
    one-factor binomial model of interest rates what
    method you will recommend using?

38
FRM-98, Question 34
  • A. The backward induction method, since it is the
    fastest?
  • B. The simulation method, using path averages,
    since the option is path dependent.
  • C. The simulation method, using path averages,
    since the option is path independent.
  • D. Either the backward induction or the
    simulation method since both methods give the
    same value.

39
FRM-97, Question 17
  • The measurement error in VaR, due to sampling
    variation should be greater with
  • A. more observations and a high confidence level
    (e.g. 99).
  • B. fewer observations and a high confidence
    level.
  • C. more observations and a low confidence level.
    (e.g. 95).
  • D. more observations and a low confidence level.

40
Multiple Sources of Risk
  • GBM model with j1,,N independent risk factors

correlated risk factors
41
Multiple Sources of Risk
  • Correlation matrix R
  • Cholesky decomposition RA AT, where A is a lower
    triangular matrix with zeros in the upper left
    corner.
  • Then ? A ?
  • Example

42
Cholesky Decomposition
43
FRM-99, Question 29
  • Covariance matrix

Let ?A AT, where A is lower triangular, be a
Cholesky decomposition. Then the four elements in
the upper left hand corner of A, a11, a12, a21,
a22, are respectively A. 3, 0, 4, 2 B. 3,
4, 0, 2 C. 3, 0, 2, 1 D. 2, 0, 3, 1
44
FRM-99, Question 29
  • Covariance matrix

Let ?A AT, where A is lower triangular, be a
Cholesky decomposition. Then the four elements in
the upper left hand corner of A, a11, a12, a21,
a22, are respectively A. 3, 0, 4, 2 B. 3,
4, 0, 2 C. 3, 0, 2, 1 D. 2, 0, 3, 1
45
FRM-99, Question 29
46
FRM-99, Question 29
47
FRM-99, Question 29
  • Given the following covariance matrix

Given the following covariance matrix A.
Log(SQ) is normally distributed B. SQ is
lognormally distributed C. SQ is normally
distributed D. S Q is normally distributed
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