| Record |
| Author |
Leiva, V.; Saulo, H.; Leao, J.; Marchant, C. |
| Title |
A family of autoregressive conditional duration models applied to financial data |
Type |
|
| Year |
2014 |
Publication |
Computational Statistics & Data Analysis |
Abbreviated Journal |
Comput. Stat. Data Anal. |
| Volume |
79 |
Issue |
|
Pages |
175-191 |
| Keywords |
Birnbaum-Saunders distribution; EM algorithm; High-frequency data; Maximum likelihood estimator; Monte Carlo simulation |
| Abstract |
The Birnbaum-Saunders distribution is receiving considerable attention due to its good properties. One of its extensions is the class of scale-mixture Birnbaum-Saunders (SBS) distributions, which shares its good properties, but it also has further properties. The autoregressive conditional duration models are the primary family used for analyzing high-frequency financial data. We propose a methodology based on SBS autoregressive conditional duration models, which includes in-sample inference, goodness-of-fit and out-of-sample forecast techniques. We carry out a Monte Carlo study to evaluate its performance and assess its practical usefulness with real-world data of financial transactions from the New York stock exchange. (C) 2014 Elsevier B.V. All rights reserved. |
| Address |
[Leiva, Victor; Marchant, Carolina] Univ Valparaiso, Inst Estadist, Valparaiso, Chile, Email: victor.leiva@yahoo.com |
| Corporate Author |
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Thesis |
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| Publisher |
Elsevier Science Bv |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0167-9473 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000340139900013 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
396 |
| Permanent link to this record |
