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Time series: Quiz


Question 1: where the term εt is the source of randomness and is called ________.
Noise reductionJohnson–Nyquist noiseWhite noiseShot noise

Question 2: Performing a ________ to investigate the series in the frequency domain.
Hilbert spaceFourier analysisFourier transformConvolution

Question 3: is a common notation which specifies a time series X which is indexed by the ________.
IntegerCardinal numberReal numberNatural number

Question 4: ________ analysis to examine serial dependence
Fourier transformTime seriesAutocorrelationCorrelation and dependence

Question 5: These models are called ________ (ARCH) and the collection comprises a wide variety of representation (GARCH, TARCH, EGARCH, FIGARCH, CGARCH, etc).
Implied volatilityStochastic volatilityLocal volatilityAutoregressive conditional heteroskedasticity

Question 6: If the noise also has a ________, it is called normal white noise (denoted here by Normal-WN):
Probability distributionGeneralized normal distributionNormal distributionStudent's t-distribution

Question 7: An example of time series forecasting in ________ is predicting the opening price of a stock based on its past performance.
Heterodox economicsEconometricsEconomic historyEconomics

Question 8: The former include spectral analysis and recently wavelet analysis; the latter include ________ and cross-correlation analysis.
Fourier transformCorrelation and dependenceAutocorrelationTime series

Question 9: In statistics, signal processing and ________, a time series is a sequence of data points, measured typically at successive times spaced at uniform time intervals.
Futures contractMathematical financeBlack–ScholesComputational finance

Question 10: When modeling variations in the level of a process, three broad classes of practical importance are the ________ (AR) models, the integrated (I) models, and the moving average (MA) models.
Stationary processAutoregressive moving average modelAutoregressive modelCentral limit theorem

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