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Tests for stochastic seasonality applied to daily financial time series

Tests for stochastic seasonality applied to daily financial time series
Tests for stochastic seasonality applied to daily financial time series
We develop tests for seasonal unit roots for daily data by extending the methodology of Hylleberg et al. ('Seasonal Integration and Cointegration', Journal of Econometrics, Vol. 44 (1990), No. 1–2, pp. 215–238) and apply our tests to UK and US daily stock market indices. We also investigate a suggestion by Franses and Romijn ('Periodic Integration in Quarterly Macroeconomic Variables', International Journal of Forecasting, Vol. 9 (1993), No. 4, pp. 467–476) and Franses ('A Multivariate Approach to Modelling Univariate Seasonal Time Series', Journal of Econometrics, Vol. 63 (1994), No. 1, pp. 133–151) and create a price series for each day of the week and test for cointegration amongst these series. Our Monte Carlo experiments indicate that the Hylleberg et al. procedure is robust to autoregressive conditional heteroscedasticity type errors, while the Franses and Romijn procedure is less so. Finally, we employ Harvey's (Time Series Models, Hemel Hempstead, Harvester Wheatsheaf, 1993) basic structural model to test for the presence of stationary stochastic seasonality. Our results suggest that we can reject the existence of seasonal unit roots at the daily frequency in both of these markets; however, we do find evidence of stationary stochastic seasonality
1463-6786
39-59
Andrade, I.C.
3fd55745-77d9-4694-9d77-9bfa10d921e5
Clare, A.D.
e9a9923a-dee5-4521-a5e1-d404befa7069
O'Brien, R.J.
a34792e2-7b3d-462b-955c-fbccaaaf7b62
Thomas, S.H.
51ff3b62-89ae-4190-8a9e-ed4a76c8297c
Andrade, I.C.
3fd55745-77d9-4694-9d77-9bfa10d921e5
Clare, A.D.
e9a9923a-dee5-4521-a5e1-d404befa7069
O'Brien, R.J.
a34792e2-7b3d-462b-955c-fbccaaaf7b62
Thomas, S.H.
51ff3b62-89ae-4190-8a9e-ed4a76c8297c

Andrade, I.C., Clare, A.D., O'Brien, R.J. and Thomas, S.H. (1999) Tests for stochastic seasonality applied to daily financial time series. The Manchester School, 67 (1), 39-59. (doi:10.1111/1467-9957.00132).

Record type: Article

Abstract

We develop tests for seasonal unit roots for daily data by extending the methodology of Hylleberg et al. ('Seasonal Integration and Cointegration', Journal of Econometrics, Vol. 44 (1990), No. 1–2, pp. 215–238) and apply our tests to UK and US daily stock market indices. We also investigate a suggestion by Franses and Romijn ('Periodic Integration in Quarterly Macroeconomic Variables', International Journal of Forecasting, Vol. 9 (1993), No. 4, pp. 467–476) and Franses ('A Multivariate Approach to Modelling Univariate Seasonal Time Series', Journal of Econometrics, Vol. 63 (1994), No. 1, pp. 133–151) and create a price series for each day of the week and test for cointegration amongst these series. Our Monte Carlo experiments indicate that the Hylleberg et al. procedure is robust to autoregressive conditional heteroscedasticity type errors, while the Franses and Romijn procedure is less so. Finally, we employ Harvey's (Time Series Models, Hemel Hempstead, Harvester Wheatsheaf, 1993) basic structural model to test for the presence of stationary stochastic seasonality. Our results suggest that we can reject the existence of seasonal unit roots at the daily frequency in both of these markets; however, we do find evidence of stationary stochastic seasonality

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Published date: 1999

Identifiers

Local EPrints ID: 37371
URI: http://eprints.soton.ac.uk/id/eprint/37371
ISSN: 1463-6786
PURE UUID: 1460eb84-a3c4-4802-aa61-0e244cbf138c

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Date deposited: 27 Apr 2007
Last modified: 15 Jul 2019 19:04

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Contributors

Author: I.C. Andrade
Author: A.D. Clare
Author: R.J. O'Brien
Author: S.H. Thomas

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