Arbeitspapier
Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends
I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of additive low-frequency contamination in log-squared returns. The types of lowfrequency contamination covered include level shifts as well as deterministic trends. I establish consistency and asymptotic normality in the presence or absence of such lowfrequency contamination under certain conditions on the growth rate of the trimming parameter. I also provide theoretical guidance on the choice of trimming parameter by heuristically obtaining its asymptotic MSE-optimal rate under certain types of lowfrequency contamination. A simulation study examines the finite sample properties of the robust estimator, showing substantial gains from its use in the presence of level shifts. The finite sample analysis also explores how different levels of trimming affect the parameter estimates in the presence and absence of low-frequency contamination and long-memory.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 2012-17
- Klassifikation
-
Wirtschaft
Financial Econometrics
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Estimation: General
Methodological Issues: General
- Thema
-
stochastic volatility
frequency domain estimation
robust estimation
spurious persistence
long-memory
level shifts
structural change
deterministic trends
- Ereignis
-
Geistige Schöpfung
- (wer)
-
McCloskey, Adam
- Ereignis
-
Veröffentlichung
- (wer)
-
Brown University, Department of Economics
- (wo)
-
Providence, RI
- (wann)
-
2012
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- McCloskey, Adam
- Brown University, Department of Economics
Entstanden
- 2012
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