TM
,INV4801 ASSIGNMENT 2 2026 - DUE DATE: 18 AUGUST 2026
QUESTION 1
(a) GARCH (1,1) CASE STUDY
(i) Using the re-parameterized GARCH (1,1) model, compute the conditional
variance for today. (6 Marks)
Formula
The re-parameterized GARCH (1,1) model is
Today's Conditional Variance
= γ + α(Return Shock)² + β(Previous Variance)
where
γ = 0.00010
α = –0.08
β = 0.35
Previous variance = 0.0144
Current return above expectation = 7.77%
Convert the return into decimal form:
7.77%
= 0.0777
Square the return innovation
(0.0777)²
, = 0.00603729
Now substitute into the GARCH equation.
Conditional Variance
= 0.00010 + (−0.08 × 0.00603729) + (0.35 × 0.0144)
Calculate each term separately.
α(Return Shock)²
= −0.08 × 0.00603729
= −0.00048298
β(Previous Variance)
= 0.35 × 0.0144
= 0.00504
Now compute the variance.
Conditional Variance
= 0.00010 − 0.00048298 + 0.00504
= 0.00465702
Final Answer
Today's conditional variance
= 0.004657
Explanation
,INV4801 ASSIGNMENT 2 2026 - DUE DATE: 18 AUGUST 2026
QUESTION 1
(a) GARCH (1,1) CASE STUDY
(i) Using the re-parameterized GARCH (1,1) model, compute the conditional
variance for today. (6 Marks)
Formula
The re-parameterized GARCH (1,1) model is
Today's Conditional Variance
= γ + α(Return Shock)² + β(Previous Variance)
where
γ = 0.00010
α = –0.08
β = 0.35
Previous variance = 0.0144
Current return above expectation = 7.77%
Convert the return into decimal form:
7.77%
= 0.0777
Square the return innovation
(0.0777)²
, = 0.00603729
Now substitute into the GARCH equation.
Conditional Variance
= 0.00010 + (−0.08 × 0.00603729) + (0.35 × 0.0144)
Calculate each term separately.
α(Return Shock)²
= −0.08 × 0.00603729
= −0.00048298
β(Previous Variance)
= 0.35 × 0.0144
= 0.00504
Now compute the variance.
Conditional Variance
= 0.00010 − 0.00048298 + 0.00504
= 0.00465702
Final Answer
Today's conditional variance
= 0.004657
Explanation