About: Market-crash forecasting based on the dynamics of the alpha-stable distribution

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Market-crash forecasting based on the dynamics of the alpha-stable distribution
Creator	Mora-Valencia, Andrés Perote, Javier Molina-Muñoz, Jesús-Enrique
Source	Elsevier; Medline; PMC
abstract	This paper investigates on the alpha-stable distribution capacity to capture the probability of market crashes by means of the dynamic forecasting of its alpha and beta parameters. On the basis of the GARCH-stable model, we design a market crash forecasting methodology that involves three-stepwise procedure: (i) Recursively estimation the GARCH-stable parameters through a rolling window; (ii) alpha-stable parameters forecasting according to a VAR model; and (iii) Crash probabilities forecasting and analysis. The model performance for alternative crash definitions is assessed in terms of different accuracy criteria, and compared with a random walk model as benchmark. Our applications to a wide variety of stock indexes for developed and emerging markets reveals a high degree of accuracy and replicability of the results. Hence the model represents an interesting tool for risk management and the design of early warning systems for future crashes.
has issue date	2020-11-01(xsd:dateTime)
bibo:doi	10.1016/j.physa.2020.124876
bibo:pmid	32834434
has license	no-cc
sha1sum (hex)	904ec2da17b03ebf28162cfe41aa32bfd0b70095
schema:url	https://doi.org/10.1016/j.physa.2020.124876
resource representing a document's title	Market-crash forecasting based on the dynamics of the alpha-stable distribution
has PubMed Central identifier	PMC7320685
has PubMed identifier	32834434
schema:publication	Physica A
resource representing a document's body	covid:904ec2da17b03ebf28162cfe41aa32bfd0b70095#body_text
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