FRM 2026 Part I Quantitative Analysis Time Series Analysis Free Quiz 2

Practice FRM 2026 Part I Quantitative Analysis MCQs from Time Series Analysis. Get instant results with Explanation.

General10 MCQs

1. What is volatility clustering?

A. Volatility clustering means large changes tend to be followed by large changesB. Volatility clustering means volatility is constant over timeC. Volatility clustering means returns are independentD. Volatility clustering is not observed in financial time series

2. What is a GARCH model?

A. GARCH models are used for modeling the meanB. GARCH models assume constant volatilityC. GARCH models are only for cross-sectional dataD. GARCH models are used to model time-varying volatility

3. What does the ARCH model model?

A. ARCH models volatility as a function of past errorsB. ARCH models volatility as a function of past squared errorsC. ARCH models volatility as a constantD. ARCH models are the same as ARIMA

4. What is the leverage effect in financial time series?

A. Leverage effect means positive returns increase volatility moreB. Leverage effect means volatility is symmetricC. Leverage effect means negative returns increase volatility more than positive returnsD. Leverage effect is not observed in markets

5. What is seasonality in time series?

A. Seasonality is a regular pattern that repeats at fixed intervalsB. Seasonality is the same as trendC. Seasonality is not observed in financial dataD. Seasonality cannot be modeled

General10 MCQs

6. What is a random walk?

A. Random walk means prices are predictableB. Random walk means the series is stationaryC. Random walk means the series has no random componentD. Random walk is a non-stationary process where the next value equals the current value plus a random shock

7. What does a Hurst exponent > 0.5 indicate?

A. Hurst exponent > 0.5 indicates mean reversionB. Hurst exponent > 0.5 indicates persistenceC. Hurst exponent < 0.5 indicates persistenceD. Hurst exponent = 0.5 indicates no memory

8. What is cointegration in time series?

A. Cointegration means series are not relatedB. Cointegration means series have no common trendC. Cointegration means a linear combination of non-stationary series is stationaryD. Cointegration is only for cross-sectional data

9. What is the Engle-Granger method used for?

A. Engle-Granger method tests for cointegration by testing residuals for stationarityB. Engle-Granger method tests for serial correlationC. Engle-Granger method tests for heteroskedasticityD. Engle-Granger method is used for model selection

10. What is a vector autoregression (VAR) model?

A. VAR models are used for univariate time seriesB. VAR models are used for cross-sectional dataC. VAR models are the same as ARIMAD. VAR models are used for multivariate time series analysis

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