Number of items: 34.
Article
Liu, Z., Lu, S., Li, B. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2023)
Time series momentum and reversal: intraday information from realized semivariance.
Journal of Empirical Finance, 72.
pp. 54-77.
ISSN 0927-5398
doi: https://doi.org/10.1016/j.jempfin.2023.03.001
Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521, Syntetos, A. A., Liu, Y., Di Cairano-Gilfedder, C. and Naim, M. M.
(2023)
Improving automotive garage operations by categorical forecasts using a large number of variables.
European Journal of Operational Research, 306 (2).
pp. 893-908.
ISSN 0377-2217
doi: https://doi.org/10.1016/j.ejor.2022.06.062
Apergis, N., Pan, W.-F., Reade, J.
ORCID: https://orcid.org/0000-0002-8610-530X and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2023)
Modelling Australian electricity prices using indicator saturation.
Energy Economics, 120.
106616.
ISSN 1873-6181
doi: https://doi.org/10.1016/j.eneco.2023.106616
Lazar, E.
ORCID: https://orcid.org/0000-0002-8761-0754, Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521 and Xue, X.
(2023)
Loss function-based change point detection in risk measures.
European Journal of Operational Research.
ISSN 0377-2217
doi: https://doi.org/10.1016/j.ejor.2023.03.033
Rostami-Tabar, B., Goltsos, T. E. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2023)
Forecasting for lead-time period by temporal aggregation: whether to combine and how.
Computers in Industry, 145.
103803.
ISSN 0166-3615
doi: https://doi.org/10.1016/j.compind.2022.103803
Li, B., Liu, Z., Teka, H. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2023)
The evolvement of momentum effects in China: evidence from functional data analysis.
Research in International Business and Finance, 64.
101833.
ISSN 1878-3384
doi: https://doi.org/10.1016/j.ribaf.2022.101833
Horváth, L., Kokoszka, P., VanderDoes, J. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2022)
Inference in functional factor models with applications to yield curves.
Journal of Time Series Analysis, 43 (6).
pp. 872-894.
ISSN 1467-9892
doi: https://doi.org/10.1111/jtsa.12642
Horváth, L., Liu, Z., Rice, G., Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521 and Zhan, Y.
(2022)
Testing stability in functional event observations with an application to IPO performance.
Journal of Business and Economic Statistics.
ISSN 0735-0015
doi: https://doi.org/10.1080/07350015.2022.2118127
Pan, W.-F., Reade, J.
ORCID: https://orcid.org/0000-0002-8610-530X and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2022)
Measuring US regional economic uncertainty.
Journal of Regional Science, 62 (4).
pp. 1149-1178.
ISSN 1467-9787
doi: https://doi.org/10.1111/jors.12590
Bouri, E., Gupta, R. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2022)
Nonlinear contagion between stock and real estate markets: international evidence from a local Gaussian correlation approach.
International Journal of Finance and Economics, 27 (2).
pp. 2089-2109.
ISSN 1099-1158
doi: https://doi.org/10.1002/ijfe.2261
Li, H., Liu, Z. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2022)
Vines climbing higher: risk management for commodity futures markets using a regular vine copula approach.
International Journal of Finance and Economics, 27 (2).
pp. 2438-2457.
ISSN 1099-1158
doi: https://doi.org/10.1002/ijfe.2280
Han, X., Liu, Z. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2022)
An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting.
Journal of Commodity Markets, 25.
100188.
ISSN 2405-8513
doi: https://doi.org/10.1016/j.jcomm.2021.100188
Pan, W.-F., Wang, X. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2022)
Measuring economic uncertainty in China.
Emerging Markets Finance and Trade, 58 (5).
pp. 1359-1389.
ISSN 1540-496X
doi: https://doi.org/10.1080/1540496X.2021.1873764
Liu, Z., Lu, S. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2021)
Asymmetry, tail risk and time series momentum.
International Review of Financial Analysis, 78.
101938.
ISSN 1057-5219
doi: https://doi.org/10.1016/j.irfa.2021.101938
Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521, Rangan, G. and Yue-Jun, Z.
(2021)
Bear, bull, sidewalk, and crash: the evolution of the US stock market using over a century of daily data.
Finance Research Letters, 43.
101998.
ISSN 1544-6123
doi: https://doi.org/10.1016/j.frl.2021.101998
Horváth, L., Kokoszka, P. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2021)
Monitoring for a change point in a sequence of distributions.
Annals of Statistics, 49 (4).
pp. 2271-2291.
ISSN 2168-8966
doi: https://doi.org/10.1214/20-AOS2036
Bouri, E., Lau, C. K. M., Saeed, T., Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521 and Zhao, Y.
(2021)
On the intraday return curves of Bitcoin: predictability and trading opportunities.
International Review of Financial Analysis, 76.
101784.
ISSN 1057-5219
doi: https://doi.org/10.1016/j.irfa.2021.101784
Apergis, N., Lau, C. K. M., Şen, F. Ö. and Wang, S.
ORCID: https://orcid.org/0000-0003-2113-5521
(2021)
Market integration between Turkey and Eurozone countries.
Emerging Markets Finance and Trade, 57 (9).
pp. 2674-2686.
ISSN 1540-496X
doi: https://doi.org/10.1080/1540496X.2019.1658070
Horváth, L., Kokoszka, P. and Wang, S.
(2020)
Testing normality of data on a multivariate grid.
Journal of Multivariate Analysis, 179.
104640.
ISSN 0047-259X
doi: https://doi.org/10.1016/j.jmva.2020.104640
Apergis, N., Gozgor, G., Lau, C. K. M. and Wang, S.
(2020)
Dependence structure in the Australian electricity markets: new evidence from regular vine copulae.
Energy Economics, 90.
104834.
ISSN 0140-9883
doi: https://doi.org/10.1016/j.eneco.2020.104834
Bonato, M., Gupta, R., Lau, C. K. M. and Wang, S.
(2020)
Moments-based spillovers across gold and oil markets.
Energy Economics, 89.
104799.
ISSN 0140-9883
doi: https://doi.org/10.1016/j.eneco.2020.104799
Balcilar, M., Gupta, R., Wang, S. and Wohar, M. E.
(2020)
Oil price uncertainty and movements in the US Government bond risk premia.
North American Journal of Economics and Finance, 52.
101147.
ISSN 1062-9408
doi: https://doi.org/10.1016/j.najef.2020.101147
Chen, C., Liu, Y., Wang, S., Sun, X., Di Cairano-Gilfedder, C., Titmus, S. and Syntetos, A. A.
(2020)
Predictive maintenance using cox proportional hazard deep learning.
Advanced Engineering Informatics, 44.
101054.
ISSN 1474-0346
doi: https://doi.org/10.1016/j.aei.2020.101054
Horváth, L., Liu, Z., Rice, G. and Wang, S.
(2020)
Sequential monitoring for changes from stationarity to mild non-stationarity.
Journal of Econometrics, 215 (1).
pp. 209-238.
ISSN 0304-4076
doi: https://doi.org/10.1016/j.jeconom.2019.08.010
Horváth, L., Liu, Z., Rice, G. and Wang, S.
(2020)
A functional time series analysis of forward curves derived from commodity futures.
International Journal of Forecasting, 36 (2).
pp. 646-665.
ISSN 0169-2070
doi: https://doi.org/10.1016/j.ijforecast.2019.08.003
Apergis, N., Gozgor, G., Lau, C. K. M. and Wang, S.
(2019)
Decoding the Australian electricity market: new evidence from three-regime hidden semi-Markov model.
Energy Economics, 78.
pp. 129-142.
ISSN 0140-9883
doi: https://doi.org/10.1016/j.eneco.2018.10.038
Antoch, J., Hanousek, J., Horváth, L., Hušková, M. and Wang, S.
(2019)
Structural breaks in panel data: large number of panels and short length time series.
Econometric Reviews.
ISSN 1532-4168
doi: https://doi.org/10.1080/07474938.2018.1454378
Goltsos, T. E., Ponte, B., Wang, S., Liu, Y., Naim, M. M. and Syntetos, A. A.
(2019)
The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems.
International Journal of Production Research, 57 (23).
pp. 7361-7394.
ISSN 0020-7543
doi: https://doi.org/10.1080/00207543.2018.1510191
Bouri, E., Gupta, R., Lau, C. K. M., Roubaud, D. and Wang, S.
(2018)
Bitcoin and global financial stress: a copula-based approach to dependence and causality in the quantiles.
The Quarterly Review of Economics and Finance, 69.
pp. 297-307.
ISSN 1062-9769
doi: https://doi.org/10.1016/j.qref.2018.04.003
Liu, Z. and Wang, S.
(2017)
Decoding Chinese stock market returns: three-state hidden semi-Markov model.
Pacific-Basin Finance Journal, 44.
pp. 127-149.
ISSN 0927538X
doi: https://doi.org/10.1016/j.pacfin.2017.06.007
Horváth, L., Pouliot, W. and Wang, S.
(2017)
Detecting at-most-m changes in linear regression models.
Journal of Time Series Analysis, 38 (4).
pp. 552-590.
ISSN 1467-9892
doi: https://doi.org/10.1111/jtsa.12228
Lau, M. C. K., Vigne, S. A., Wang, S. and Yarovaya, L.
(2017)
Return spillovers between white precious metal ETFs: the role of oil, gold, and global equity.
International Review of Financial Analysis, 52.
pp. 316-332.
ISSN 1057-5219
doi: https://doi.org/10.1016/j.irfa.2017.04.001
Liu, Z. and Wang, S.
(2017)
Understanding the Chinese stock market: international comparison and policy implications.
Economic and Political Studies, 5 (4).
pp. 441-455.
ISSN 2095-4816
doi: https://doi.org/10.1080/20954816.2017.1384616
Book or Report Section
Liu, Z., Han, D. and Wang, S.
(2016)
Testing bubbles: exuberance and collapse in the Shanghai a-share stock market.
In: Song, L., Garnaut, R., Cai, F. and Johnston, L. (eds.)
China's New Sources of Economic Growth.
ANU Press, pp. 247-270.
ISBN 9781760460358
doi: https://doi.org/10.22459/CNSEG.07.2016.11
This list was generated on Thu Jun 1 18:59:41 2023 UTC.