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Journal of Time Series Analysis is a peer-reviewed journal published by Wiley, covering Financial Risk and Volatility Modeling, Statistical Methods and Inference, Monetary Policy and Economic Impact.
| Publisher | Wiley |
|---|---|
| Reference style | Author–year (Chicago) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Journal of Time Series Analysis 12 (3): 45–58.
Formats any DOI in Journal of Time Series Analysis style. No sign-up. |
| Publishes research in | Financial Risk and Volatility Modeling Statistical Methods and Inference Monetary Policy and Economic Impact Complex Systems and Time Series Analysis Advanced Statistical Methods and Models |
| ISSN | 0143-9782 |
| Citation impact (2-yr) | 1.12 |
| h-index | 105 |
| i10-index | 946 |
| Total citations | 69,274 |
| Article processing charge | $4,020 |
| Top institutions publishing here | University of Manchester |
| Journal website | onlinelibrary.wiley.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Abstract. The idea of fractional differencing is introduced in terms of the infinite filter that corresponds to the expansion of (1‐ B ) d . When the filter is applied to white noise, a class of time series is generated with distinctive properties, particularly in the very low frequencies and provides potentially useful long‐memory forecasting…
Abstract. The definitions of fractional Gaussian noise and integrated (or fractionally differenced) series are generalized, and it is shown that the two concepts are equivalent. A new estimator of the long memory parameter in these models is proposed, based on the simple linear regression of the log periodogram on a deterministic regressor. The estimator is…
A new test is proposed for cointegration in a single‐equation framework where the regressors are weakly exogenous for the parameters of interest. The test is denoted as an error‐correction mechanism (ECM) test and is based upon the ordinary least squares coefficient of the lagged dependent variable in an autoregressive distributed lag model augmented with leads…
