Access the full text.
Sign up today, get DeepDyve free for 14 days.
E. Cleur (2001)
Maximum Likelihood Estimates of a Class of One‐Dimensional Stochastic Differential Equation Models From Discrete DataJournal of Time Series Analysis, 22
Cheol Eun, Sangdal Shim (1989)
International Transmission of Stock Market MovementsJournal of Financial and Quantitative Analysis, 24
G. Moustakides (1998)
Quickest Detection of Abrupt Changes for a Class of Random ProcessesIEEE Trans. Inf. Theory, 44
Wirtschaftswissenschaftliche Fakult (2004)
Adaptive Estimation for Financial Time Series
Yin-Wong Cheung, Jia He, Lilian Ng (1997)
Common Predictable Components in Regional Stock MarketsJournal of Business & Economic Statistics, 15
Garland Durham, Ronald Gallant (2002)
Numerical Techniques for Maximum Likelihood Estimation of Continuous-Time Diffusion ProcessesJournal of Business & Economic Statistics, 20
Engle Engle, Kozicki Kozicki (1993)
Testing for common featuresJournal of Business and Economic Statistics, 11
F. Diebold, A. Inoue (2000)
Long Memory and Regime SwitchingEconometrics eJournal
King King, Wadhwani Wadhwani (1990)
Transmission of volatility between stock marketsThe Review of Financial Studies, 3
Diebold Diebold, Inoue Inoue (2001)
Long memory and regime switchingJournal of Econometrics, 105
S. Chib, M. Pitt, N. Shephard (2004)
Likelihood based inference for diffusion driven models
P. Kloeden, E. Platen, H. Schurz, Michael Sørensen (1996)
On effects of discretization on estimators of drift parameters for diffusion processesJournal of Applied Probability, 33
S. Kozicki, R. Engle (1990)
Testing for Common FeaturesEconometrics eJournal
R. Dahlhaus (1996)
On the Kullback-Leibler information divergence of locally stationary processesStochastic Processes and their Applications, 62
M. Basseville, A. Benveniste (1985)
Detection of Abrupt Changes in Signals and Dynamical Systems
M. Basseville, I. Nikiforov (1993)
Detection of abrupt changes: theory and applicationTechnometrics, 36
D. Brillinger (1976)
Estimation of the Second-Order Intensities of a Bivariate Stationary Point ProcessJournal of the royal statistical society series b-methodological, 38
Yacine Aït-Sahalia (2002)
Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed‐form Approximation ApproachEconometrica, 70
M. King, S. Wadhwani (1989)
Transmission of Volatility between Stock MarketsNBER Working Paper Series
Filippo Altissimo, V. Corradi (2003)
Strong Rules for Detecting the Number of Breaks in a Time Series
G. Karolyi, René Stulz (1996)
Why Do Markets Move Together? An Investigation of U.S.-Japan Stock Return ComovementsJournal of Finance, 51
Stock market indices from several countries are modelled as discretely sampled diffusions whose parameters change at certain times. To estimate these times of parameter changes we employ both a sequential likelihood‐ratio test and a non‐parametric, spectral algorithm designed specifically for time series with multiple changepoints. Finally, we use point‐process techniques to model relationships between changepoints of different financial time series. Copyright © 2006 John Wiley & Sons, Ltd.
Applied Stochastic Models in Business and Industry – Wiley
Published: Sep 1, 2006
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.