Question 721
The “dummy variable trap” refers to:
A. Using too few dummy variables
B. Using a dummy variable as the dependent variable
C. Including a full set of dummies plus an intercept, causing perfect multicollinearity
D. Using dummies in time-series models
Check answer
Select an option first.
Correct answer: C — Including a full set of dummies plus an intercept, causing perfect multicollinearity
Explanation: Right: Full set + intercept → perfect collinearity. Wrong: A/B/D: Not the trap.
Question 722
In a regression with a dummy variable for “crisis period” (1 during crisis, 0 otherwise), the coefficient on the dummy measures:
A. The slope of the trend
B. The average change in the dependent variable during crisis vs non-crisis periods
C. The variance of the residuals
D. The correlation between crises and time
Check answer
Select an option first.
Correct answer: B — The average change in the dependent variable during crisis vs non-crisis periods
Explanation: Right: It captures the shift in the level of (Y) during crisis periods. Wrong: A/C/D: Not what the dummy coefficient means.
Question 723
Logistic regression is most appropriate when the dependent variable is:
A. A continuous return
B. A count of events
C. A binary outcome (e.g., default vs no default)
D. A nominal interest rate
Check answer
Select an option first.
Correct answer: C — A binary outcome (e.g., default vs no default)
Explanation: Right: Logistic regression models binary outcomes. Wrong: A/B/D: Different types of data.
Question 724
In logistic regression, the model estimates:
A. The probability of the dependent variable taking a particular value
B. The exact value of the dependent variable
C. The mean of the independent variables
D. The variance of the residuals
Check answer
Select an option first.
Correct answer: A — The probability of the dependent variable taking a particular value
Explanation: Right: Logistic regression outputs probabilities. Wrong: B/C/D: Not its main output.
Question 725
A common use of logistic regression in finance is to:
A. Forecast daily returns
B. Classify firms as likely to default or not
C. Compute moving averages
D. Estimate volatility
Check answer
Select an option first.
Correct answer: B — Classify firms as likely to default or not
Explanation: Right: Default prediction is a classic logistic regression application. Wrong: A/C/D: Different tasks.
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Question 726
In logistic regression, the dependent variable is often coded as:
A. Any real number
B. 0 and 1
C. −1 and 1 only
D. The residuals
Check answer
Select an option first.
Correct answer: B — 0 and 1
Explanation: Right: Binary coding (0/1) is standard. Wrong: A/C/D: Not typical.
Question 727
A time series is:
A. A set of observations ordered over time
B. A set of unordered cross-sectional observations
C. A set of random numbers only
D. A set of categorical labels
Check answer
Select an option first.
Correct answer: A — A set of observations ordered over time
Explanation: Right: Time series are indexed by time. Wrong: B/C/D: Not definitions.
Question 728
A linear trend model for a time series typically includes:
A. Only a constant
B. A constant and a time variable
C. Only lagged values of the series
D. Only dummy variables
Check answer
Select an option first.
Correct answer: B — A constant and a time variable
Explanation: Right: Linear trend: level + slope × time. Wrong: A/C/D: Different structures.
Question 729
A log-linear trend model is often used when:
A. The series grows at a roughly constant percentage rate
B. The series is constant
C. The series is purely random
D. The series is binary
Check answer
Select an option first.
Correct answer: A — The series grows at a roughly constant percentage rate
Explanation: Right: Log-linear models capture constant growth rates. Wrong: B/C/D: Not the main use.
Question 730
A covariance-stationary time series has:
A. Constant mean and variance over time
B. Mean and variance that trend over time
C. No mean
D. No variance
Check answer
Select an option first.
Correct answer: A — Constant mean and variance over time
Explanation: Right: Stationarity requires constant mean and variance. Wrong: B/C/D: Not stationary.
Question 731
An autoregressive (AR) model explains the current value of a series using:
A. Future values of the series
B. Past values of the series
C. Only independent variables
D. Only dummy variables
Check answer
Select an option first.
Correct answer: B — Past values of the series
Explanation: Right: AR models use lagged values of the series. Wrong: A/C/D: Not AR.
Question 732
In an AR(1) model, the current value depends on:
A. One lagged value
B. Two lagged values
C. Three lagged values
D. No lagged values
Check answer
Select an option first.
Correct answer: A — One lagged value
Explanation: Right: AR(1) uses one lag. Wrong: B/C/D: Different orders.
Question 733
Mean reversion in a time series means:
A. The series drifts away from its mean
B. The series tends to move back toward its long-run average
C. The series has no mean
D. The series is purely random
Check answer
Select an option first.
Correct answer: B — The series tends to move back toward its long-run average
Explanation: Right: Mean-reverting series pull back toward a long-run level. Wrong: A/C/D: Opposite or unrelated.
Question 734
A random walk is a time series where:
A. Changes are predictable
B. Changes are completely deterministic
C. Changes are random and the best forecast is the last observed value
D. The series is constant
Check answer
Select an option first.
Correct answer: C — Changes are random and the best forecast is the last observed value
Explanation: Right: Random walk: next value = last value + random shock. Wrong: A/B/D: Not random walk.
Question 735
A unit root in a time series indicates:
A. Strong mean reversion
B. Nonstationarity
C. Perfect stationarity
D. No randomness
Check answer
Select an option first.
Correct answer: B — Nonstationarity
Explanation: Right: Unit root processes are nonstationary. Wrong: A/C/D: Incorrect.
Question 736
A moving average (MA) model uses:
A. Past values of the series
B. Past error terms
C. Future values of the series
D. Only dummy variables
Check answer
Select an option first.
Correct answer: B — Past error terms
Explanation: Right: MA models depend on past shocks (errors). Wrong: A/C/D: Not MA.
Question 737
A simple moving average forecast of order (n) is:
A. The sum of all past values
B. The average of the most recent (n) observations
C. The median of the entire series
D. The maximum of the series
Check answer
Select an option first.
Correct answer: B — The average of the most recent (n) observations
Explanation: Right: SMA uses the last (n) observations. Wrong: A/C/D: Not the definition.
Question 738
Seasonality in a time series refers to:
A. Long-term trends
B. Short-term random noise
C. Regular patterns that repeat at fixed intervals
D. Permanent structural breaks
Check answer
Select an option first.
Correct answer: C — Regular patterns that repeat at fixed intervals
Explanation: Right: Seasonality is periodic behavior. Wrong: A/B/D: Different phenomena.
Question 739
A common way to model seasonality is to:
A. Ignore it
B. Add seasonal dummy variables
C. Remove the intercept
D. Use only one observation
Check answer
Select an option first.
Correct answer: B — Add seasonal dummy variables
Explanation: Right: Seasonal dummies capture recurring patterns. Wrong: A/C/D: Poor practice.
Question 740
Comparing forecast models often involves:
A. Comparing their forecast errors (e.g., mean squared error)
B. Comparing their intercepts only
C. Comparing their sample sizes only
D. Comparing their file names
Check answer
Select an option first.
Correct answer: A — Comparing their forecast errors (e.g., mean squared error)
Explanation: Right: Forecast accuracy is judged by error metrics. Wrong: B/C/D: Not meaningful.
Question 741
Instability of regression coefficients over time suggests:
A. The model is stable
B. The relationship between variables may have changed
C. The residuals are always zero
D. The series is stationary
Check answer
Select an option first.
Correct answer: B — The relationship between variables may have changed
Explanation: Right: Changing coefficients indicate evolving relationships. Wrong: A/C/D: Not implied.
Question 742
Unsupervised learning is used to:
A. Predict a known target
B. Discover patterns or groupings without labeled outcomes
C. Estimate regression coefficients
D. Compute moving averages
Check answer
Select an option first.
Correct answer: B — Discover patterns or groupings without labeled outcomes
Explanation: Right: Unsupervised learning finds structure in unlabeled data. Wrong: A/C/D: Different tasks.
Question 743
K-nearest neighbors (KNN) classifies an observation based on:
A. A regression line
B. The majority class among its closest neighbors
C. The intercept only
D. Random assignment
Check answer
Select an option first.
Correct answer: B — The majority class among its closest neighbors
Explanation: Right: KNN uses nearby points to classify. Wrong: A/C/D: Not KNN.
Question 744
Support vector machines (SVM) aim to:
A. Find a hyperplane that maximizes the margin between classes
B. Minimize the number of features
C. Maximize the number of residuals
D. Randomly assign classes
Check answer
Select an option first.
Correct answer: A — Find a hyperplane that maximizes the margin between classes
Explanation: Right: SVMs maximize the margin between classes. Wrong: B/C/D: Not their goal.
Question 745
Clustering algorithms (like k-means) are used to:
A. Predict a numeric target
B. Group similar observations without labels
C. Compute regression coefficients
D. Estimate volatility
Check answer
Select an option first.
Correct answer: B — Group similar observations without labels
Explanation: Right: Clustering finds groups in unlabeled data. Wrong: A/C/D: Different tasks.
Question 746
Unstructured data in finance often includes:
A. Stock prices in a spreadsheet
B. Text from news articles or earnings calls
C. A table of returns
D. A matrix of factor exposures
Check answer
Select an option first.
Correct answer: B — Text from news articles or earnings calls
Explanation: Right: Text is a classic unstructured data type. Wrong: A/C/D: Structured.
Question 747
Data cleaning (or preparation) commonly involves:
A. Ignoring missing values
B. Handling missing values, correcting errors, and standardizing formats
C. Deleting all data
D. Randomly changing values
Check answer
Select an option first.
Correct answer: B — Handling missing values, correcting errors, and standardizing formats
Explanation: Right: Cleaning improves data quality. Wrong: A/C/D: Poor practice.
Question 748
Model evaluation in a data project typically involves:
A. Looking only at the training error
B. Using metrics (e.g., accuracy, mean squared error) on validation or test data
C. Ignoring performance metrics
D. Using only visual inspection
Check answer
Select an option first.
Correct answer: B — Using metrics (e.g., accuracy, mean squared error) on validation or test data
Explanation: Right: Proper evaluation uses metrics on unseen data. Wrong: A/C/D: Incomplete or misleading.
Question 749
A regression coefficient is statistically significant when:
A. Its p‑value is high
B. Its p‑value is low
C. Its sign is positive
D. Its magnitude is large
Check answer
Select an option first.
Correct answer: B — Its p‑value is low
Explanation: Low p‑value → strong evidence the coefficient differs from zero. A/C/D: Sign or size alone does not determine significance.
Question 750
A negative slope coefficient means:
A. The dependent variable decreases as the independent variable increases
B. The dependent variable increases as the independent variable increases
C. The model is invalid
D. The intercept must be removed
Check answer
Select an option first.
Correct answer: A — The dependent variable decreases as the independent variable increases
Explanation: Negative slope = inverse relationship. B/C/D: Incorrect interpretations.
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