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标题: 13: Time-Series Analysis-LOS a习题精选 [打印本页]
作者: 土豆妮    时间: 2010-4-8 15:34     标题: [2010]Session 3:-Reading 13: Time-Series Analysis-LOS a习题精选

Session 3: Quantitative Methods: Quantitative
Methods for Valuation
Reading 13: Time-Series Analysis

LOS a: Calculate and evaluate the predicted trend value for a time series, modeled as either a linear trend or a log-linear trend, given the estimated trend coefficients.

 

 

 

David Wellington, CFA, has estimated the following log-linear trend model: LN(xt) = b0 + b1t + εt. Using six years of quarterly observations, 2001:I to 2006:IV, Wellington gets the following estimated equation: LN(xt) = 1.4 + 0.02t. The first out-of-sample forecast of xt for 2007:I is closest to:

A)
 1.88.
B)
 4.14.
C)
 6.69.

作者: 土豆妮    时间: 2010-4-8 15:34

David Wellington, CFA, has estimated the following log-linear trend model: LN(xt) = b0 + b1t + εt. Using six years of quarterly observations, 2001:I to 2006:IV, Wellington gets the following estimated equation: LN(xt) = 1.4 + 0.02t. The first out-of-sample forecast of xt for 2007:I is closest to:

A)
 1.88.
B)
 4.14.
C)
 6.69.


Wellington’s out-of-sample forecast of LN(xt) is 1.9 = 1.4 + 0.02 × 25, and e1.9 = 6.69.

作者: 土豆妮    时间: 2010-4-8 15:34

Modeling the trend in a time series of a variable that grows at a constant rate with continuous compounding is best done with:

A)

a moving average model.

B)

simple linear regression.

C)

a log-linear transformation of the time series.

作者: 土豆妮    时间: 2010-4-8 15:35

Modeling the trend in a time series of a variable that grows at a constant rate with continuous compounding is best done with:

A)

a moving average model.

B)

simple linear regression.

C)

a log-linear transformation of the time series.



The log-linear transformation of a series that grows at a constant rate with continuous compounding (exponential growth) will cause the transformed series to be linear.

作者: 土豆妮    时间: 2010-4-8 15:35

In the time series model: yt=b0 + b1 t + εt, t=1,2,…,T, the:

A)

disturbance terms are autocorrelated.

B)

disturbance term is mean-reverting.

C)

change in the dependent variable per time period is b1.

作者: 土豆妮    时间: 2010-4-8 15:35

In the time series model: yt=b0 + b1 t + εt, t=1,2,…,T, the:

A)

disturbance terms are autocorrelated.

B)

disturbance term is mean-reverting.

C)

change in the dependent variable per time period is b1.



The slope is the change in the dependent variable per unit of time. The intercept is the estimate of the value of the dependent variable before the time series begins. The disturbance term should be independent and identically distributed. There is no reason to expect the disturbance term to be mean-reverting, and if the residuals are autocorrelated, the research should correct for that problem.

作者: xiamity    时间: 2010-5-19 14:56

A
作者: luqian55    时间: 2010-5-30 11:20

thanks
作者: annyyu    时间: 2010-12-1 05:25

re



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