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Yu-Chin Hsu

Personal Details

First Name:Yu-Chin
Middle Name:
Last Name:Hsu
Suffix:
RePEc Short-ID:phs7
http://yuchinhsu.yolasite.com/
Institute of Economics Academia Sinica 128 Academia Road, Section 2 Nankang, Taipei, 115 Taiwan
886-2-27822791 ext. 322

Affiliation

Institute of Economics
Academia Sinica

Taipei, Taiwan
http://www.econ.sinica.edu.tw/

: 886-2-27822791
886-2-27853946

RePEc:edi:sinictw (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Yu-Chin Hsu & Shu Shen, 2017. "Monotonicity Test for Local Average Treatment Effects Under Regression Discontinuity," IEAS Working Paper : academic research 17-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  2. Yu-Chin Hsu & Chung-Ming Kuan & Giorgio Teng-Yu Lo, 2017. "Quantile Treatment Effects in Regression Discontinuity Designs with Covariates," IEAS Working Paper : academic research 17-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  3. Yu-Chin Hsu & Hsiou-Wei Lin & Kendro Vincent, 2017. "Analyzing the Performance of Multi-Factor Investment Strategies under Multiple Testing Framework," IEAS Working Paper : academic research 17-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  4. Hsu, Yu-Chin & Huber, Martin & Lai, Tsung Chih, 2017. "Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting," FSES Working Papers 482, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  5. Yu-Chin Hsu & Ji-Liang Shiu, 2017. "Internally Consistent Estimation of Nonlinear Panel Data Models with Correlated Random Effects," IEAS Working Paper : academic research 17-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  6. Yu-Chin Hsu & Tsung-Chih Lai & Robert P. Lieli, 2017. "Estimating Counterfactual Treatment Effects to Assess External Validity," IEAS Working Paper : academic research 17-A011, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  7. Yu-Chin Hsu & Shu Shen, 2016. "Testing for Treatment Effect Heterogeneity in Regression Discontinuity Design," IEAS Working Paper : academic research 16-A005, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  8. Yu-Chin Hsu, 2016. "Multiplier Bootstrap for Empirical Processes," IEAS Working Paper : academic research 16-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  9. Yu-Chin Hsu & Chu-An Liu & Xiaoxia Shi, 2016. "Testing Generalized Regression Monotonicity," IEAS Working Paper : academic research 16-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  10. Yu-Chin Hsu & Rachel J. Huang & Larry Y. Tzeng & Christine W. Wang, 2016. "Can Investing in Hedge Funds Improve Efficiency for Economically Important Investors?," IEAS Working Paper : academic research 16-A006, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  11. Robert P. Lieli & Yu-Chin Hsu, 2016. "The Null Distribution of the Empirical AUC for Classi ers with Estimated Parameters: a Special Case," IEAS Working Paper : academic research 16-A007, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  12. Yu-Chin Hsu & Robert P. Lieli & Tsung-Chih Lai, 2015. "Estimation and Inference for Distribution Functions and Quantile Functions in Endogenous Treatment Effect Models," IEAS Working Paper : academic research 15-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  13. Wei-Ming Lee & Chung-Ming Kuan & Yu-Chin Hsu, 2014. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 14-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  14. Yu-Chin Hsu & Xiaoxia Shi, 2013. "Model Selection Tests for Conditional Moment Inequality Models," IEAS Working Paper : academic research 13-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  15. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2012. "Estimating Conditional Average Treatment Effects," CEU Working Papers 2012_16, Department of Economics, Central European University, revised 20 Jul 2012.
  16. Joseph Haslag & Yu-Chin Hsu, 2012. "Cyclical Co-movement between Output, the Price Level, and Inflation," Working Papers 1203, Department of Economics, University of Missouri.
  17. Stephen G. Donald & Yu-Chin Hsu, 2012. "Estimation and Inference for Distribution Functions and Quantile Functions in Treatment Effect Models," IEAS Working Paper : academic research 12-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  18. Stephen G. Donald & Yu-Chin Hsu, 2012. "Improving the Power of Tests of Stochastic Dominance," IEAS Working Paper : academic research 12-A015, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Jun 2013.
  19. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2010. "Inverse Propensity Score Weighted Estimation of Local Average Treatment Effects and a Test of the Unconfoundedness Assumption," CEU Working Papers 2012_9, Department of Economics, Central European University, revised 11 Aug 2010.
  20. Yu-Chin Hsu & Chung-Ming Kuan, 2006. "Change-Point Estimation of Nonstationary I(d) Processes," IEAS Working Paper : academic research 06-A007, Institute of Economics, Academia Sinica, Taipei, Taiwan.

Articles

  1. Yu‐Chin Hsu & Xiaoxia Shi, 2017. "Model‐selection tests for conditional moment restriction models," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 52-85, February.
  2. Yu‐Chin Hsu, 2017. "Consistent tests for conditional treatment effects," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 1-22, February.
  3. Barrett, Garry F. & Donald, Stephen G. & Hsu, Yu-Chin, 2016. "Consistent tests for poverty dominance relations," Journal of Econometrics, Elsevier, vol. 191(2), pages 360-373.
  4. Stephen G. Donald & Yu-Chin Hsu, 2016. "Improving the Power of Tests of Stochastic Dominance," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 553-585, April.
  5. Wei‐Ming Lee & Yu‐Chin Hsu & Chung‐Ming Kuan, 2015. "Robust hypothesis tests for M‐estimators with possibly non‐differentiable estimating functions," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 95-116, February.
  6. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2015. "Estimating Conditional Average Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, pages 485-505.
  7. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
  8. Donald, Stephen G. & Hsu, Yu-Chin, 2014. "Estimation and inference for distribution functions and quantile functions in treatment effect models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
  9. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2014. "Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT," Journal of Business & Economic Statistics, Taylor & Francis Journals, pages 395-415.
  10. Donald, Stephen G. & Hsu, Yu-Chin & Lieli, Robert P., 2014. "Inverse probability weighted estimation of local average treatment effects: A higher order MSE expansion," Statistics & Probability Letters, Elsevier, pages 132-138.
  11. Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
  12. Yu-Chin Hsu & Chung-Ming Kuan & Meng-Feng Yen, 2014. "A Generalized Stepwise Procedure with Improved Power for Multiple Inequalities Testing," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(4), pages 730-755.
  13. Stephen G. Donald & Yu‐Chin Hsu & Garry F. Barrett, 2012. "Incorporating covariates in the measurement of welfare and inequality: methods and applications," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 1-30, February.
  14. Donald, Stephen G. & Hsu, Yu-Chin, 2011. "A new test for linear inequality constraints when the variance–covariance matrix depends on the unknown parameters," Economics Letters, Elsevier, vol. 113(3), pages 241-243.
  15. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, pages 471-484.
  16. Kuan, Chung-Ming & Yeh, Jin-Huei & Hsu, Yu-Chin, 2009. "Assessing value at risk with CARE, the Conditional Autoregressive Expectile models," Journal of Econometrics, Elsevier, vol. 150(2), pages 261-270, June.
  17. Hsu, Yu-Chin & Kuan, Chung-Ming, 2008. "Change-point estimation of nonstationary I(d) processes," Economics Letters, Elsevier, vol. 98(2), pages 115-121, February.

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. Yu-Chin Hsu & Shu Shen, 2016. "Testing for Treatment Effect Heterogeneity in Regression Discontinuity Design," IEAS Working Paper : academic research 16-A005, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Yu-Chin Hsu & Chung-Ming Kuan & Giorgio Teng-Yu Lo, 2017. "Quantile Treatment Effects in Regression Discontinuity Designs with Covariates," IEAS Working Paper : academic research 17-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.

  2. Yu-Chin Hsu & Robert P. Lieli & Tsung-Chih Lai, 2015. "Estimation and Inference for Distribution Functions and Quantile Functions in Endogenous Treatment Effect Models," IEAS Working Paper : academic research 15-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly & Kaspar Wuthrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Papers 1608.05142, arXiv.org, revised Oct 2017.
    2. Blaise Melly und Kaspar Wüthrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    3. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

  3. Wei-Ming Lee & Chung-Ming Kuan & Yu-Chin Hsu, 2014. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 14-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Wei-Ming Lee & Chung-Ming Kuan & Yu-Chin Hsu, 2014. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 14-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.

  4. Yu-Chin Hsu & Xiaoxia Shi, 2013. "Model Selection Tests for Conditional Moment Inequality Models," IEAS Working Paper : academic research 13-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Shi, Xiaoxia, 2015. "Model selection tests for moment inequality models," Journal of Econometrics, Elsevier, vol. 187(1), pages 1-17.

  5. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2012. "Estimating Conditional Average Treatment Effects," CEU Working Papers 2012_16, Department of Economics, Central European University, revised 20 Jul 2012.

    Cited by:

    1. Sokbae Lee & Ryo Okui & Yoon-Jae Whang, 2016. "Doubly Robust Uniform Confidence Band for the Conditional Average Treatment Effect Function," Papers 1601.02801, arXiv.org, revised Oct 2016.
    2. Wichman, Casey J., 2016. "Information Provision and Consumer Behavior: A Natural Experiment in Billing Frequency," Discussion Papers dp-15-35-rev, Resources For the Future.

  6. Joseph Haslag & Yu-Chin Hsu, 2012. "Cyclical Co-movement between Output, the Price Level, and Inflation," Working Papers 1203, Department of Economics, University of Missouri.

    Cited by:

    1. Joseph Haslag & William Brock, 2014. "On Understanding the Cyclical Behavior of the Price Level and Inflation," Working Papers 1404, Department of Economics, University of Missouri, revised 01 Jul 2014.
    2. Brock, William A. & Haslag, Joseph H., 2016. "A tale of two correlations: Evidence and theory regarding the phase shift between the price level and output," Journal of Economic Dynamics and Control, Elsevier, vol. 67(C), pages 40-57.
    3. Michal Andrle & Jan Bruha & Serhat Solmaz, 2013. "Inflation and Output Comovement in the Euro Area: Love at Second Sight?," Working Papers 2013/07, Czech National Bank, Research Department.

  7. Stephen G. Donald & Yu-Chin Hsu, 2012. "Estimation and Inference for Distribution Functions and Quantile Functions in Treatment Effect Models," IEAS Working Paper : academic research 12-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
    2. Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly & Kaspar Wuthrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Papers 1608.05142, arXiv.org, revised Oct 2017.
    3. Ying-Ying Lee, 2015. "Efficient propensity score regression estimators of multi-valued treatment effects for the treated," Economics Series Working Papers 738, University of Oxford, Department of Economics.
    4. García, A., 2016. "Oaxaca-Blinder Type Counterfactual Decomposition Methods for Duration Outcomes," DOCUMENTOS DE TRABAJO 014186, UNIVERSIDAD DEL ROSARIO.
    5. Brantly Callaway & Tong Li, 2017. "Quantile Treatment Effects in Difference in Differences Models with Panel Data," DETU Working Papers 1701, Department of Economics, Temple University.
    6. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.

  8. Stephen G. Donald & Yu-Chin Hsu, 2012. "Improving the Power of Tests of Stochastic Dominance," IEAS Working Paper : academic research 12-A015, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Jun 2013.

    Cited by:

    1. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Esfandiar Maasoumi & Michael McAleer & Teodosio Pérez-Amaral, 2015. "A Stochastic Dominance Approach to the Basel III Dilemma: Expected Shortfall or VaR?," Documentos de Trabajo del ICAE 2015-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. David M. Kaplan & Matt Goldman, 2013. "Comparing distributions by multiple testing across quantiles," Working Papers 16-19, Department of Economics, University of Missouri, revised Nov 2016.
    3. Chang, Chia-Lin & Jiménez-Martín, Juan-Ángel & Maasoumi, Esfandiar & Pérez-Amaral, Teodosio, 2015. "A stochastic dominance approach to financial risk management strategies," Journal of Econometrics, Elsevier, vol. 187(2), pages 472-485.
    4. Chang, C-L. & Jiménez-Martín, J.A. & Maasoumi, E. & McAleer, M.J., 2015. "Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance," Econometric Institute Research Papers EI2015-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2017. "Bayesian assessment of Lorenz and stochastic dominance," Monash Econometrics and Business Statistics Working Papers 15/17, Monash University, Department of Econometrics and Business Statistics.
    6. Arvanitis, Stelios & Topaloglou, Nikolas, 2017. "Testing for prospect and Markowitz stochastic dominance efficiency," Journal of Econometrics, Elsevier, vol. 198(2), pages 253-270.
    7. Chuang, O-Chia & Kuan, Chung-Ming & Tzeng, Larry Y., 2017. "Testing for central dominance: Method and application," Journal of Econometrics, Elsevier, vol. 196(2), pages 368-378.
    8. Barrett, Garry F. & Donald, Stephen G. & Hsu, Yu-Chin, 2016. "Consistent tests for poverty dominance relations," Journal of Econometrics, Elsevier, vol. 191(2), pages 360-373.

  9. Yu-Chin Hsu & Chung-Ming Kuan, 2006. "Change-Point Estimation of Nonstationary I(d) Processes," IEAS Working Paper : academic research 06-A007, Institute of Economics, Academia Sinica, Taipei, Taiwan.

    Cited by:

    1. Giorgio Canarella & Stephen Miller, 2016. "Inflation persistence and structural breaks: the experience of inflation targeting countries and the US," Journal of Economic Studies, Emerald Group Publishing, vol. 43(6), pages 980-1005, November.
    2. Seong Yeon Chang & Pierre Perron, 2014. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Boston University - Department of Economics - Working Papers Series wp2015-011, Boston University - Department of Economics, revised 20 Sep 2015.

Articles

  1. Barrett, Garry F. & Donald, Stephen G. & Hsu, Yu-Chin, 2016. "Consistent tests for poverty dominance relations," Journal of Econometrics, Elsevier, vol. 191(2), pages 360-373.

    Cited by:

    1. David Lander & David Gunawan & William E. Griffiths & Duangkamon Chotikapanich, 2016. "Bayesian Assessment of Lorenz and Stochastic Dominance Using a Mixture of Gamma Densities," Department of Economics - Working Papers Series 2023, The University of Melbourne.
    2. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2017. "Bayesian Assessment of Lorenz and Stochastic Dominance," Department of Economics - Working Papers Series 2029, The University of Melbourne.
    3. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2017. "Bayesian assessment of Lorenz and stochastic dominance," Monash Econometrics and Business Statistics Working Papers 15/17, Monash University, Department of Econometrics and Business Statistics.

  2. Stephen G. Donald & Yu-Chin Hsu, 2016. "Improving the Power of Tests of Stochastic Dominance," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 553-585, April.
    See citations under working paper version above.
  3. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2015. "Estimating Conditional Average Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, pages 485-505.
    See citations under working paper version above.
  4. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.

    Cited by:

    1. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.

  5. Donald, Stephen G. & Hsu, Yu-Chin, 2014. "Estimation and inference for distribution functions and quantile functions in treatment effect models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
    See citations under working paper version above.
  6. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2014. "Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT," Journal of Business & Economic Statistics, Taylor & Francis Journals, pages 395-415.

    Cited by:

    1. Donald, Stephen G. & Hsu, Yu-Chin, 2014. "Estimation and inference for distribution functions and quantile functions in treatment effect models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
    2. Huber, Martin, 2013. "A simple test for the ignorability of non-compliance in experiments," Economics Letters, Elsevier, vol. 120(3), pages 389-391.
    3. Gerry H. Makepeace & Michael J. Peel, 2013. "Combining information from Heckman and matching estimators: testing and controlling for hidden bias," Economics Bulletin, AccessEcon, vol. 33(3), pages 2422-2436.
    4. Marianna Endresz & Peter Harasztosi & Robert P. Lieli, 2015. "The Impact of the Magyar Nemzeti Bank's Funding for Growth Scheme on Firm Level Investment," MNB Working Papers 2015/2, Magyar Nemzeti Bank (Central Bank of Hungary).
    5. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2012. "Estimating Conditional Average Treatment Effects," CEU Working Papers 2012_16, Department of Economics, Central European University, revised 20 Jul 2012.
    6. de Luna, Xavier & Johansson, Per, 2012. "Testing for Nonparametric Identification of Causal Effects in the Presence of a Quasi-Instrument," IZA Discussion Papers 6692, Institute for the Study of Labor (IZA).
    7. Hsu, Yu-Chin & Huber, Martin & Lai, Tsung Chih, 2017. "Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting," FSES Working Papers 482, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    8. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

  7. Donald, Stephen G. & Hsu, Yu-Chin & Lieli, Robert P., 2014. "Inverse probability weighted estimation of local average treatment effects: A higher order MSE expansion," Statistics & Probability Letters, Elsevier, pages 132-138.

    Cited by:

    1. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

  8. Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
    See citations under working paper version above.
  9. Yu-Chin Hsu & Chung-Ming Kuan & Meng-Feng Yen, 2014. "A Generalized Stepwise Procedure with Improved Power for Multiple Inequalities Testing," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(4), pages 730-755.

    Cited by:

    1. Cheng-Te Lee & Deng-Sing Huang, 2017. "Asymmetric Globalization and Specialization," IEAS Working Paper : academic research 17-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan.

  10. Stephen G. Donald & Yu‐Chin Hsu & Garry F. Barrett, 2012. "Incorporating covariates in the measurement of welfare and inequality: methods and applications," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 1-30, February.

    Cited by:

    1. Donald, Stephen G. & Hsu, Yu-Chin, 2014. "Estimation and inference for distribution functions and quantile functions in treatment effect models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
    2. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
    3. Ying-Ying Lee, 2015. "Efficient propensity score regression estimators of multi-valued treatment effects for the treated," Economics Series Working Papers 738, University of Oxford, Department of Economics.
    4. Frank A. Cowell & Emmanuel Flachaire, 2014. "Statistical Methods for Distributional Analysis," Working Papers halshs-01115996, HAL.
    5. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    6. Jing Dai & Stefan Sperlich & Walter Zucchini, 2016. "A Simple Method for Predicting Distributions by Means of Covariates with Examples from Poverty and Health Economics," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 152(I), pages 49-80, March.
    7. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.

  11. Donald, Stephen G. & Hsu, Yu-Chin, 2011. "A new test for linear inequality constraints when the variance–covariance matrix depends on the unknown parameters," Economics Letters, Elsevier, vol. 113(3), pages 241-243.

    Cited by:

    1. Huber, Martin, 2012. "Statistical verification of a natural "natural experiment": Tests and sensitivity checks for the sibling sex ratio instrument," Economics Working Paper Series 1219, University of St. Gallen, School of Economics and Political Science.
    2. David M. Kaplan & Longhao Zhuo, 2015. "Bayesian and frequentist inequality tests," Working Papers 1516, Department of Economics, University of Missouri, revised Apr 2017.

  12. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, pages 471-484.

    Cited by:

    1. Coakley, Jerry & Marzano, Michele & Nankervis, John, 2016. "How profitable are FX technical trading rules?," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 273-282.
    2. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 4181, WU Vienna University of Economics and Business.
    3. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
    4. Andriosopoulos, Kostas & Doumpos, Michael & Papapostolou, Nikos C. & Pouliasis, Panos K., 2013. "Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 16-34.
    5. Wang, Shan & Jiang, Zhi-Qiang & Li, Sai-Ping & Zhou, Wei-Xing, 2015. "Testing the performance of technical trading rules in the Chinese markets based on superior predictive test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 114-123.
    6. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    7. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    8. Zarrabi, Nima & Snaith, Stuart & Coakley, Jerry, 2017. "FX technical trading rules can be profitable sometimes!," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 113-127.
    9. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, pages 188-208.
    10. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
    11. Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 089-115, December.
    12. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, pages 675-685.
    13. Kearney, Fearghal & Cummins, Mark & Murphy, Finbarr, 2014. "Outperformance in exchange-traded fund pricing deviations: Generalized control of data snooping bias," Journal of Financial Markets, Elsevier, vol. 19(C), pages 86-109.
    14. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    15. Suzuki, Tomoya & Ohkura, Yuushi, 2016. "Financial technical indicator based on chaotic bagging predictors for adaptive stock selection in Japanese and American markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 50-66.
    16. Christopher J. Bennett, 2009. "p-Value Adjustments for Asymptotic Control of the Generalized Familywise Error Rate," Vanderbilt University Department of Economics Working Papers 0905, Vanderbilt University Department of Economics.
    17. Zongwu Cai & Jiancheng Jiang & Jingshuang Zhang & Xibin Zhang, 2015. "A new semiparametric test for superior predictive ability," Empirical Economics, Springer, pages 389-405.
    18. Mihai Cristian Dinică & Erica Cristina (Balea) Dinică, 2015. "Testing the Weak-Form Market Eficiency of the Euronext Wheat," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 18(55), pages 25-38, March.
    19. Joseph P. Romano & Michael Wolf, 2017. "Multiple testing of one-sided hypotheses: combining Bonferroni and the bootstrap," ECON - Working Papers 254, Department of Economics - University of Zurich.
    20. Hsu, Po-Hsuan & Taylor, Mark P, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in the Foreign Exchange Market," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    21. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    22. Shynkevich, Andrei, 2016. "Predictability in bond returns using technical trading rules," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 55-69.
    23. Crespo Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava, 2017. "Exchange rate forecasting and the performance of currency portfolios," Economics Series 326, Institute for Advanced Studies.
    24. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, pages 64-85.
    25. Kao, Yi-Cheng & Kuan, Chung-Ming & Chen, Shikuan, 2013. "Testing the predictive power of the term structure without data snooping bias," Economics Letters, Elsevier, vol. 121(3), pages 546-549.
    26. Cheng-Te Lee & Deng-Sing Huang, 2017. "Asymmetric Globalization and Specialization," IEAS Working Paper : academic research 17-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    27. Chen, Shi & Bao, Si & Zhou, Yu, 2016. "The predictive power of Japanese candlestick charting in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 148-165.
    28. Zongwu Cai & Jiancheng Jiang & Jingshuang Zhang, 2013. "A New Test for Superior Predictive Ability," WISE Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.

  13. Kuan, Chung-Ming & Yeh, Jin-Huei & Hsu, Yu-Chin, 2009. "Assessing value at risk with CARE, the Conditional Autoregressive Expectile models," Journal of Econometrics, Elsevier, vol. 150(2), pages 261-270, June.

    Cited by:

    1. Hamidi, Benjamin & Maillet, Bertrand & Prigent, Jean-Luc, 2014. "A dynamic autoregressive expectile for time-invariant portfolio protection strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 46(C), pages 1-29.
    2. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2017. "Extreme M-quantiles as risk measures: From L1 to Lp optimization," TSE Working Papers 17-841, Toulouse School of Economics (TSE).
    3. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    4. Edgars Jakobsons & Steven Vanduffel, 2015. "Dependence Uncertainty Bounds for the Expectile of a Portfolio," Risks, MDPI, Open Access Journal, vol. 3(4), pages 1-25, December.
    5. Zhang, Feipeng & Li, Qunhua, 2017. "A continuous threshold expectile model," Computational Statistics & Data Analysis, Elsevier, pages 49-66.
    6. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2015. "Systemic risk and asymmetric responses in the financial industry," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 471-485.
    7. Carol Alexander & Jose Maria Sarabia, 2010. "Endogenizing Model Risk to Quantile Estimates," ICMA Centre Discussion Papers in Finance icma-dp2010-07, Henley Business School, Reading University.
    8. Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.
    9. Huang, Xiaolin & Shi, Lei & Suykens, Johan A.K., 2014. "Asymmetric least squares support vector machine classifiers," Computational Statistics & Data Analysis, Elsevier, pages 395-405.
    10. Huang, Alex YiHou, 2010. "An optimization process in Value-at-Risk estimation," Review of Financial Economics, Elsevier, vol. 19(3), pages 109-116, August.
    11. Ngoc M. Tran & Petra Burdejová & Maria Osipenko & Wolfgang K. Härdle, 2016. "Principal Component Analysis in an Asymmetric Norm," SFB 649 Discussion Papers SFB649DP2016-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Jakobsons Edgars, 2016. "Scenario aggregation method for portfolio expectile optimization," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 51-65, September.
    13. Natalia Nolde & Johanna F. Ziegel, 2016. "Elicitability and backtesting: Perspectives for banking regulation," Papers 1608.05498, arXiv.org, revised Feb 2017.
    14. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," IEFE Working Papers 56, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    15. Bellini, Fabio & Klar, Bernhard & Müller, Alfred & Rosazza Gianin, Emanuela, 2014. "Generalized quantiles as risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 41-48.
    16. Marcelo Bianconi & Xiaxin Hua & Chih Ming Tan, 2013. "Determinants of Systemic Risk and Information Dissemination," Working Paper series 67_13, Rimini Centre for Economic Analysis.
    17. Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    18. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2015. "A comparison of Expected Shortfall estimation models," Journal of Economics and Business, Elsevier, pages 14-47.
    19. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2015. "Estimation of Tail Risk based on Extreme Expectiles," TSE Working Papers 15-566, Toulouse School of Economics (TSE), revised Jul 2017.
    20. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Zhijie Xiao & Roger Koenker, 2009. "Conditional Quantile Estimation for GARCH Models," Boston College Working Papers in Economics 725, Boston College Department of Economics.
    22. Wolfgang Karl Härdle & Ya’acov Ritov & Song Song, 2010. "Partial Linear Quantile Regression and Bootstrap Confidence Bands," SFB 649 Discussion Papers SFB649DP2010-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Xiu Xu & Andrija Mihoci & Wolfgang Karl Härdle, "undated". "lCARE – localizing Conditional AutoRegressive Expectiles," SFB 649 Discussion Papers SFB649DP2015-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Johanna F. Ziegel, 2013. "Coherence and elicitability," Papers 1303.1690, arXiv.org, revised Mar 2014.

  14. Hsu, Yu-Chin & Kuan, Chung-Ming, 2008. "Change-point estimation of nonstationary I(d) processes," Economics Letters, Elsevier, vol. 98(2), pages 115-121, February.
    See citations under working paper version above.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 18 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-ECM: Econometrics (14) 2012-12-22 2012-12-22 2013-06-16 2014-02-15 2015-08-30 2016-05-21 2016-07-02 2016-07-23 2016-09-11 2017-01-15 2017-05-21 2017-08-27 2017-08-27 2017-08-27. Author is listed
  2. NEP-EFF: Efficiency & Productivity (1) 2016-06-18
  3. NEP-GER: German Papers (1) 2015-08-30
  4. NEP-LMA: Labor Markets - Supply, Demand, & Wages (1) 2017-08-27
  5. NEP-MAC: Macroeconomics (1) 2012-04-17
  6. NEP-ORE: Operations Research (1) 2012-12-22
  7. NEP-RMG: Risk Management (1) 2012-11-03
  8. NEP-SEA: South East Asia (1) 2016-06-18
  9. NEP-SOG: Sociology of Economics (1) 2014-02-15

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