Consider the following GARCH(1,1) model for the volatility of asset returns 𝑟 𝑡 : 𝑟 𝑡 = 𝛼 + 𝛽 𝑟 𝑡 − 1 + 𝜀 𝑡 𝜀 𝑡 = ℎ 𝑡 𝑢 𝑡 ℎ 𝑡 = 𝜇 + 𝛿 ℎ 𝑡 − 1 + 𝜙 𝜀 𝑡 − 1 2 𝔼 𝑡 − 1 ( 𝑢 𝑡 ) = 0 𝔼 𝑡 − 1 ( 𝑢 𝑡 2 ) = 1 You estimated the following values for the parameters Estimates Parameters 𝛼 𝛽 𝜇 𝛿 𝜙 Estimates 0.111 0.8122 0.0011 0.9321 0.0511 Assume that the last 2 observations of the return process are 𝑟 𝑇 = 0.27 and 𝑟 𝑇 − 1 = 0.02 , and the value of the conditional variance in the last period of your sample is ℎ 𝑇 = 0.75 . Then what is the predicted value of the conditional variance ℎ 𝑇 + 1 in period 𝑇 + 1 ? 单项选择题
A
ℎ ̂ 𝑇 + 1 = 0.0729
B
ℎ ̂ 𝑇 + 1 = 0.701216
C
There is not enough data to compute ℎ ̂ 𝑇 + 1 .
D
ℎ ̂ 𝑇 + 1 = 0.519615
E
ℎ ̂ 𝑇 + 1 = 0.866025
F
ℎ ̂ 𝑇 + 1 = 0.75
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类似问题
On Tuesday, you calculated the volatility of Wednesday as 5% using the GARCH model, which information will make the Thursday volatility become even higher?
When estimating the GARCH model, an intermediate step is to predict tomorrow's return.
When estimating the GARCH model, an intermediate step is to predict tomorrow's return.
On Tuesday, you calculated the volatility of Wednesday as 5% using the GARCH model, which information will make the Thursday volatility become even higher?
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