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http://hdl.handle.net/2072/5361
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| Title: | A nonlinear threshold model for the dependence of extremes of stationary sequences |
| Authors: | Martínez Ibáñez, Oscar
Olmo, José |
| Other authors: | Universitat Rovira i Virgili. Departament d'Economia |
| Subjects: | Crisis financeres
Observacions aberrants (Estadística)
Hipòtesi estadística -- Proves
Teories no-lineals |
| Creation Date: | 2008 |
| Series/Report no.: | Documents de treball del Departament d'Economia;2008-02 |
| Abstract: | One of the main implications of the efficient market hypothesis (EMH) is that expected
future returns on financial assets are not predictable if investors are risk neutral. In this
paper we argue that financial time series offer more information than that this hypothesis
seems to supply. In particular we postulate that runs of very large returns can be predictable
for small time periods. In order to prove this we propose a TAR(3,1)-GARCH(1,1) model
that is able to describe two different types of extreme events: a first type generated by large
uncertainty regimes where runs of extremes are not predictable and a second type where
extremes come from isolated dread/joy events. This model is new in the literature in nonlinear
processes. Its novelty resides on two features of the model that make it different from previous
TAR methodologies. The regimes are motivated by the occurrence of extreme values and
the threshold variable is defined by the shock affecting the process in the preceding period.
In this way this model is able to uncover dependence and clustering of extremes in high
as well as in low volatility periods. This model is tested with data from General Motors
stocks prices corresponding to two crises that had a substantial impact in financial markets
worldwide; the Black Monday of October 1987 and September 11th, 2001. By analyzing the
periods around these crises we find evidence of statistical significance of our model and thereby
of predictability of extremes for September 11th but not for Black Monday. These findings
support the hypotheses of a big negative event producing runs of negative returns in the first
case, and of the burst of a worldwide stock market bubble in the second example.
JEL classification: C12; C15; C22; C51
Keywords and Phrases: asymmetries, crises, extreme values, hypothesis testing, leverage effect,
nonlinearities, threshold models |
| CDU: | 519.1 - Combinatorial analysis. Graph theory |
| Appears in Collections: | Documents de treball del Departament d'Economia
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