On the parameter estimation in the Schwartz-Smith's two-factor model

Karol Binkowski; Peilun He; Nino Kordzakhia; Pavel Shevchenko

doi:10.1007/978-981-15-1960-4_16

On the parameter estimation in the Schwartz-Smith's two-factor model

Karol Binkowski, Peilun He, Nino Kordzakhia, Pavel Shevchenko

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

Abstract

The two unobservable state variables representing the short and long term factors introduced by Schwartz and Smith in [16] for risk-neutral pricing of futures contracts are modelled as two correlated Ornstein-Uhlenbeck processes. The Kalman Filter (KF) method has been implemented to estimate the "short" and "long" term factors jointly with unknown model parameters. The parameter identification problem arising within the likelihood function in the KF has been addressed by introducing an additional constraint. The obtained model parameter estimates are the Maximum Likelihood Estimators (MLEs) evaluated within the KF. Consistency of the MLEs is studied. The methodology has been tested on simulated data.

Original language	English
Title of host publication	Statistics and data science
Subtitle of host publication	Research School on Statistics and Data Science, RSSDS 2019 Melbourne, VIC, Australia, July 24–26, 2019 proceedings
Editors	Hien Nguyen
Place of Publication	Singapore
Publisher	Springer, Springer Nature
Pages	226-237
Number of pages	12
ISBN (Electronic)	9789811519604
ISBN (Print)	9789811519598
DOIs	https://doi.org/10.1007/978-981-15-1960-4_16
Publication status	Published - 2019
Event	Research School on Statistics and Data Science 2019 - Melbourne, Australia Duration: 24 Jul 2019 → 26 Jul 2019

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	1150
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	Research School on Statistics and Data Science 2019
Abbreviated title	RSSDS 2019
Country	Australia
City	Melbourne
Period	24/07/19 → 26/07/19

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Keywords

Kalman Filter
Parameter estimation
Partially observed linear system

Cite this

Binkowski, K., He, P., Kordzakhia, N., & Shevchenko, P. (2019). On the parameter estimation in the Schwartz-Smith's two-factor model. In H. Nguyen (Ed.), Statistics and data science: Research School on Statistics and Data Science, RSSDS 2019 Melbourne, VIC, Australia, July 24–26, 2019 proceedings (pp. 226-237). (Communications in Computer and Information Science; Vol. 1150). Singapore: Springer, Springer Nature. https://doi.org/10.1007/978-981-15-1960-4_16

Binkowski, Karol ; He, Peilun ; Kordzakhia, Nino ; Shevchenko, Pavel. / On the parameter estimation in the Schwartz-Smith's two-factor model. Statistics and data science: Research School on Statistics and Data Science, RSSDS 2019 Melbourne, VIC, Australia, July 24–26, 2019 proceedings. editor / Hien Nguyen. Singapore : Springer, Springer Nature, 2019. pp. 226-237 (Communications in Computer and Information Science).

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Binkowski, K, He, P , Kordzakhia, N & Shevchenko, P 2019, On the parameter estimation in the Schwartz-Smith's two-factor model. in H Nguyen (ed.), Statistics and data science: Research School on Statistics and Data Science, RSSDS 2019 Melbourne, VIC, Australia, July 24–26, 2019 proceedings. Communications in Computer and Information Science, vol. 1150, Springer, Springer Nature, Singapore, pp. 226-237, Research School on Statistics and Data Science 2019, Melbourne, Australia, 24/07/19. https://doi.org/10.1007/978-981-15-1960-4_16

On the parameter estimation in the Schwartz-Smith's two-factor model. / Binkowski, Karol; He, Peilun ; Kordzakhia, Nino ; Shevchenko, Pavel.

Statistics and data science: Research School on Statistics and Data Science, RSSDS 2019 Melbourne, VIC, Australia, July 24–26, 2019 proceedings. ed. / Hien Nguyen. Singapore : Springer, Springer Nature, 2019. p. 226-237 (Communications in Computer and Information Science; Vol. 1150).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

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AB - The two unobservable state variables representing the short and long term factors introduced by Schwartz and Smith in [16] for risk-neutral pricing of futures contracts are modelled as two correlated Ornstein-Uhlenbeck processes. The Kalman Filter (KF) method has been implemented to estimate the "short" and "long" term factors jointly with unknown model parameters. The parameter identification problem arising within the likelihood function in the KF has been addressed by introducing an additional constraint. The obtained model parameter estimates are the Maximum Likelihood Estimators (MLEs) evaluated within the KF. Consistency of the MLEs is studied. The methodology has been tested on simulated data.

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Binkowski K, He P , Kordzakhia N , Shevchenko P. On the parameter estimation in the Schwartz-Smith's two-factor model. In Nguyen H, editor, Statistics and data science: Research School on Statistics and Data Science, RSSDS 2019 Melbourne, VIC, Australia, July 24–26, 2019 proceedings. Singapore: Springer, Springer Nature. 2019. p. 226-237. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-15-1960-4_16

Access to Document

10.1007/978-981-15-1960-4_16

Link to publication in Scopus