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Erscheinungsjahr: 
2022
Quellenangabe: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 10 [Issue:] 1 [Article No.:] 2095764 [Year:] 2022 [Pages:] 1-20
Verlag: 
Taylor & Francis, Abingdon
Zusammenfassung: 
In this paper, we investigate the goodness-of-fit of the flexible four-parameter generalized Lambda Distribution (GLD) for high-frequency 5-min returns sampled from the DJI30 Index. Applying Moment Matching (MM) and Maximum Likelihood Estimation (MLE) techniques, we highlight the significance of the higher-order parameters of the GLD distribution to depict the asymmetric and fat-tailed behaviour observed in high-frequency returns data. We also show and explain why the MLE consistently outperforms the MM; especially in the presence of "outliers". Finally, we use lambda-space scatterplots to introduce, clarify and discuss additional stylized facts of high-frequency index returns not found in the extant high-frequency literature.
Schlagwörter: 
Maximum likelihood
moment matching
generalized lambda distribution
highfrequency
Goodness-of-fit
higher moments
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