CFA Level I · CFA Level I Exam · Applications of Simple Linear Regression in Finance
In a log-log regression of ln(quantity demanded) on ln(price), the estimated slope is -1.4. The slope is best interpreted as:
In a log-log model the slope is an elasticity, so -1.4 means a 1% increase in price is associated with about a 1.4% decrease in quantity demanded. Both variables are in logs, so changes are proportional.
- Aa 1% rise in price is associated with a 1.4% fall in quantity demandedCorrect
- Ba one-unit rise in price is associated with a 1.4% fall in quantity demanded
- Ca 1% rise in price is associated with a 1.4-unit fall in quantity demanded
Explanation
In a log-log model the slope is an elasticity: the percentage change in Y for a 1% change in X. So a slope of -1.4 means a 1% price rise goes with a 1.4% fall in quantity. The other options mix level and percentage changes.
Did you get it right without looking?
One question tells you little. A timed set on Applications of Simple Linear Regression in Finance shows your real accuracy, how long you take and where you lose marks.
More Applications of Simple Linear Regression in Finance questions
- An analyst builds a prediction interval for a dependent variable using a simple linear regression. Holding the confidence level and the esti…
- A simple linear regression ANOVA table shows a regression mean square of 60 and an error mean square of 4, with 1 degree of freedom for regr…
- In a simple linear regression of a stock's excess returns on the market's excess returns, the sum of squares total (SST) is 80 and the sum o…
- An analyst estimates the regression ln(Y) = b0 + b1X, where X is the number of years since a firm's founding and Y is its revenue. This func…
- A regression of a fund's returns on a benchmark's returns yields an intercept (alpha) of 0.9% with a t-statistic of 1.40. The critical t-val…
- A researcher finds that the residuals from a linear regression of company revenue on years since founding fan out and show a curved pattern,…