Questions
BU.230.730.81.SP25 Final Exam- Requires Respondus LockDown Browser
Multiple fill-in-the-blank
According to the GARCH model σTHURSDAY2=ω+αRBLANK12+βσBLANK22\sigma_{THURSDAY}^2 = \omega + \alpha R_{BLANK1}^2 +\beta \sigma_{BLANK2}^2 (Hint: fill in day of the week like Monday, Tuesday...) BLANK1:[Fill in the blank], BLANK2:[Fill in the blank],
View Explanation
Verified Answer
Please login to view
Step-by-Step Analysis
The question presents a GARCH(1,1) style equation for the variance on Thursday and asks you to fill two day-of-week blanks.
First, restating the structure: the given form is sigma_thursday^2 = omega + alpha * R_{BLANK1}^2 + beta * sigma_{BLANK2}^2. The hint says fill in the day of the week (Monday, Tuesday, etc.). This means both BLANK1 and BLANK2 should refer to information from the prior day(s) relative to Thursday.
Opti......Login to view full explanationLog in for full answers
We've collected over 50,000 authentic exam questions and detailed explanations from around the globe. Log in now and get instant access to the answers!
Similar Questions
Consider the following GARCH(1,1) model for the volatility of asset returns 𝑟 𝑡 : 𝑟 𝑡 = 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 Parameters Estimates MLE 𝜇 0.0112 𝛿 0.932 𝜙 0.0811 and the variance-covariance matrix is 𝑉 ( 𝜃 ̂ ) = [ 0.0012 − 0.012 0.001 − 0.012 0.102 − 0.003 0.001 − 0.003 0.003 ] Assume the last observation in your sample has ℎ 𝑇 = 1.5056 . What is the value of the conditional variance 𝑉 𝑇 − 1 ( 𝑟 𝑇 ) ?
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 0.1911 0.9722 0.0011 0.9321 0.0821 Assume that the last 2 observations of the return process are 𝑟 𝑇 = 0.07 and 𝑟 𝑇 − 1 = 0.03 , and the value of the conditional variance in the last period of your sample is ℎ 𝑇 = 0.55 . Then what is the predicted value of the conditional variance ℎ 𝑇 + 1 in period 𝑇 + 1 ?
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 𝛼 𝛽 𝜇 𝛿 𝜙 0.5911 0.9222 0.0112 0.9132 0.0611 Assume that the last 2 observations of the return process are 𝑟 𝑇 = 0.04 and 𝑟 𝑇 − 1 = 0.05 , and the value of the conditional variance in the last period of your sample is ℎ 𝑇 = 0.5 . Then what is the predicted value of the conditional variance ℎ 𝑇 + 1 in period 𝑇 + 1 ?
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 𝛼 𝛽 𝜇 𝛿 𝜙 0.5911 0.9222 0.0112 0.9132 0.0611 Assume that the last 2 observations of the return process are 𝑟 𝑇 = 0.04 and 𝑟 𝑇 − 1 = 0.05 , and the value of the conditional variance in the last period of your sample is ℎ 𝑇 = 0.5 . Then what is the predicted value of the conditional variance ℎ 𝑇 + 1 in period 𝑇 + 1 ?
More Practical Tools for Students Powered by AI Study Helper
Making Your Study Simpler
Join us and instantly unlock extensive past papers & exclusive solutions to get a head start on your studies!