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Hawkes-Based Models...
Hawkes-Based Models for High Frequency Financial Data
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- Nyström, Kaj, 1969- (författare)
- Uppsala universitet,Analys och sannolikhetsteori
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- Zhang, Changyong (författare)
- Curtin University, Miri, Malaysia
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(creator_code:org_t)
- 2021-07-23
- 2022
- Engelska.
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Ingår i: Journal of the Operational Research Society. - : Taylor & Francis. - 0160-5682 .- 1476-9360. ; 73:10, s. 2168-2185
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Compared with low frequency data, high frequency data exhibit distinct empirical properties,including, for instance, essentially discontinuous evolution paths, time-varying intensities, and self-exciting features. All these make it more challenging to model appropriately the dynamics associatedwith high frequency data such as order arrival and price formation. To capture more accuratelythe microscopic structures and properties pertaining to the limit order books, this paper focuses onmodeling high frequency data using Hawkes processes. Two models, one with exponential kernels andthe other with power-law kernels, are introduced systematically, algorithmized precisely, and comparedwith each other extensively from various perspectives, including the goodness of fit to the original dataand the computational time in searching for the maximum likelihood estimator, with search algorithmbeing taken into consideration as well. To measure the goodness of fit, a number of quantities areproposed. Studies based on both multiple-trading-day data of one stock and multiple-stock data onone trading day indicate that Hawkes processes with slowly-decaying kernels are able to reproduce theintensity of jumps in the price processes more accurately. The results suggest that Hawkes processeswith power-law kernels and their implied long memory nature of self-excitation phenomena could, onthe level of microstructure, serve as a realistic model for high frequency data.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
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