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Yubo Tao

Personal Details

First Name:Yubo
Middle Name:
Last Name:Tao
Suffix:
RePEc Short-ID:pta698
[This author has chosen not to make the email address public]
https://sites.google.com/site/ybtao1990/
Avenida da Universidade Taipa, Macau SAR
Terminal Degree:2019 School of Economics; Singapore Management University (from RePEc Genealogy)

Affiliation

Economics
University of Macau

Macau, Macao
http://www.umac.mo/economics/
RePEc:edi:eumacmo (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Liang Jiang & Peter C. B. Phillips & Yubo Tao & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Papers 2105.14752, arXiv.org, revised Sep 2022.
  2. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2019. "Dynamic Network Perspective of Cryptocurrencies," IRTG 1792 Discussion Papers 2019-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  3. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  4. Yubo Tao, 2018. "Limit Theory for Moderate Deviation from Integrated GARCH Processes," Papers 1806.01229, arXiv.org, revised Dec 2018.
  5. Li Guo & Wolfgang Karl Hardle & Yubo Tao, 2018. "A Time-Varying Network for Cryptocurrencies," Papers 1802.03708, arXiv.org, revised Nov 2022.
  6. Yubo Tao & Peter C.B. Phillips & Jun Yu, 2017. "Random Coefficient Continuous Systems: Testing for Extreme Sample Path Behaviour," Cowles Foundation Discussion Papers 2114, Cowles Foundation for Research in Economics, Yale University.
  7. Li Guo & Lin Peng & Yubo Tao & Jun Tu, 2017. "Joint News, Attention Spillover,and Market Returns," Papers 1703.02715, arXiv.org, revised Nov 2022.
  8. Yubo Tao & Jun Yu, 2017. "Model Selection for Explosive Models," Papers 1703.02720, arXiv.org.

Articles

  1. Zhi Da & Ke Tang & Yubo Tao & Liyan Yang, 2024. "Financialization and Commodity Markets Serial Dependence," Management Science, INFORMS, vol. 70(4), pages 2122-2143, April.
  2. Li Guo & Wolfgang Karl Härdle & Yubo Tao, 2024. "A Time-Varying Network for Cryptocurrencies," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 437-456, April.
  3. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
  4. Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023. "Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations," Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
  5. Tao, Yubo, 2019. "Limit theory for moderate deviation from Integrated GARCH processes," Statistics & Probability Letters, Elsevier, vol. 150(C), pages 126-136.
  6. Tao, Yubo & Phillips, Peter C.B. & Yu, Jun, 2019. "Random coefficient continuous systems: Testing for extreme sample path behavior," Journal of Econometrics, Elsevier, vol. 209(2), pages 208-237.

Chapters

  1. Yubo Tao & Jun Yu, 2020. "Model Selection for Explosive Models," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 73-103, Emerald Group Publishing Limited.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Liang Jiang & Peter C. B. Phillips & Yubo Tao & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Papers 2105.14752, arXiv.org, revised Sep 2022.

    Cited by:

    1. Liang Jiang & Liyao Li & Ke Miao & Yichong Zhang, 2023. "Adjustment with Many Regressors Under Covariate-Adaptive Randomizations," Papers 2304.08184, arXiv.org, revised Feb 2024.
    2. Tatsushi Oka & Shota Yasui & Yuta Hayakawa & Undral Byambadalai, 2024. "Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials," Papers 2407.14074, arXiv.org.
    3. Undral Byambadalai & Tatsushi Oka & Shota Yasui, 2024. "Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction," Papers 2407.16037, arXiv.org.
    4. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    5. Liang Jiang & Oliver B. Linton & Haihan Tang & Yichong Zhang, 2022. "Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance," Papers 2201.13004, arXiv.org, revised Jun 2023.

  2. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2019. "Dynamic Network Perspective of Cryptocurrencies," IRTG 1792 Discussion Papers 2019-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  3. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Zhong, Wei & Liu, Xi & Ma, Shuangge, 2018. "Variable selection and direction estimation for single-index models via DC-TGDR method," IRTG 1792 Discussion Papers 2018-050, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Xiaojia Bao & Qingliang Fan, 2020. "The impact of temperature on gaming productivity: evidence from online games," Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
    5. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Min-Bin Lin & Kainat Khowaja & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Blockchain mechanism and distributional characteristics of cryptos," Papers 2011.13240, arXiv.org, revised Aug 2021.
    15. Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    17. Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Nasekin, Sergey & Chen, Cathy Yi-Hsuan, 2018. "Deep learning-based cryptocurrency sentiment construction," IRTG 1792 Discussion Papers 2018-066, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  4. Li Guo & Wolfgang Karl Hardle & Yubo Tao, 2018. "A Time-Varying Network for Cryptocurrencies," Papers 1802.03708, arXiv.org, revised Nov 2022.

    Cited by:

    1. Paola Stolfi & Mauro Bernardi & Davide Vergni, 2022. "Robust estimation of time-dependent precision matrix with application to the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.

  5. Yubo Tao & Peter C.B. Phillips & Jun Yu, 2017. "Random Coefficient Continuous Systems: Testing for Extreme Sample Path Behaviour," Cowles Foundation Discussion Papers 2114, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Offer Lieberman & Peter C.B. Phillips, 2018. "Understanding Temporal Aggregation Effects on Kurtosis in Financial Indices," Cowles Foundation Discussion Papers 2151, Cowles Foundation for Research in Economics, Yale University.
    2. Yang, Bingduo & Long, Wei & Yang, Zihui, 2022. "Testing predictability of stock returns under possible bubbles," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 246-260.
    3. Nishi, Mikihito & 西, 幹仁 & Kurozumi, Eiji & 黒住, 英司, 2022. "Stochastic Local and Moderate Departures from a Unit Root and Its Application to Unit Root Testing," Discussion Papers 2022-02, Graduate School of Economics, Hitotsubashi University.
    4. Yanbo Liu & Peter C.B. Phillips, 2021. "Robust Inference with Stochastic Local Unit Root Regressors in Predictive Regressions," Cowles Foundation Discussion Papers 2305, Cowles Foundation for Research in Economics, Yale University.
    5. Shuping Shi & Jun Yu, 2023. "Volatility Puzzle: Long Memory or Antipersistency," Management Science, INFORMS, vol. 69(7), pages 3861-3883, July.
    6. Offer Lieberman & Peter C.B. Phillips, 2017. "Hybrid Stochastic Local Unit Roots," Cowles Foundation Discussion Papers 2113, Cowles Foundation for Research in Economics, Yale University.
    7. Xuanling Yang & Dong Li & Ting Zhang, 2024. "A simple stochastic nonlinear AR model with application to bubble," Papers 2401.07038, arXiv.org.

  6. Li Guo & Lin Peng & Yubo Tao & Jun Tu, 2017. "Joint News, Attention Spillover,and Market Returns," Papers 1703.02715, arXiv.org, revised Nov 2022.

    Cited by:

    1. Xia, Jingjing, 2024. "Stealing the show: The negative effects of media coverage on peers’ stock liquidity," Finance Research Letters, Elsevier, vol. 59(C).
    2. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Zhi-Qiang Jiang & Wei-Xing Zhou, 2018. "Multifractal characteristics and return predictability in the Chinese stock markets," Papers 1806.07604, arXiv.org.
    3. Zhibing Li & Jie Liu & Xiaoyu Liu & Chonglin Wu, 2024. "Investor attention and stock price efficiency: Evidence from quasi‐natural experiments in China," Financial Management, Financial Management Association International, vol. 53(1), pages 175-225, March.
    4. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
    5. Qinkai Chen & Christian-Yann Robert, 2021. "Graph-Based Learning for Stock Movement Prediction with Textual and Relational Data," Papers 2107.10941, arXiv.org, revised Dec 2021.

  7. Yubo Tao & Jun Yu, 2017. "Model Selection for Explosive Models," Papers 1703.02720, arXiv.org.

    Cited by:

    1. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2023. "Robust dynamic space–time panel data models using $$\varepsilon $$ ε -contamination: an application to crop yields and climate change," Empirical Economics, Springer, vol. 64(6), pages 2475-2509, June.

Articles

  1. Li Guo & Wolfgang Karl Härdle & Yubo Tao, 2024. "A Time-Varying Network for Cryptocurrencies," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 437-456, April.
    See citations under working paper version above.
  2. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).

    Cited by:

    1. Bajra, Ujkan Q. & Aliu, Florin, 2023. "Deciphering the cryptocurrency conundrum: Investigating speculative characteristics and volatility," Finance Research Letters, Elsevier, vol. 58(PC).

  3. Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023. "Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations," Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
    See citations under working paper version above.
  4. Tao, Yubo & Phillips, Peter C.B. & Yu, Jun, 2019. "Random coefficient continuous systems: Testing for extreme sample path behavior," Journal of Econometrics, Elsevier, vol. 209(2), pages 208-237.
    See citations under working paper version above.

Chapters

  1. Yubo Tao & Jun Yu, 2020. "Model Selection for Explosive Models," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 73-103, Emerald Group Publishing Limited.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-SEA: South East Asia (3) 2017-10-08 2017-12-11 2018-04-23. Author is listed
  2. NEP-BAN: Banking (2) 2021-08-30 2021-09-20. Author is listed
  3. NEP-ECM: Econometrics (2) 2017-10-08 2017-12-11. Author is listed
  4. NEP-ETS: Econometric Time Series (2) 2017-10-08 2018-04-23. Author is listed
  5. NEP-ISF: Islamic Finance (2) 2021-08-30 2021-09-20. Author is listed
  6. NEP-ORE: Operations Research (2) 2021-06-21 2021-09-20. Author is listed
  7. NEP-PAY: Payment Systems and Financial Technology (2) 2021-08-30 2021-09-20. Author is listed
  8. NEP-CWA: Central and Western Asia (1) 2021-09-20
  9. NEP-NET: Network Economics (1) 2021-09-20

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