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Xiaochun Liu

Personal Details

First Name:Xiaochun
Middle Name:
Last Name:Liu
Suffix:
RePEc Short-ID:pli1583
https://sites.google.com/site/xiaochunliu2015/home

Affiliation

Culverhouse College of Business
University of Alabama-Tuscaloosa

Tuscaloosa, Alabama (United States)
https://culverhouse.ua.edu/
RePEc:edi:cbauaus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
  2. Stanislav Anatolyev & Nikolay Gospodinov & Ibrahim Jamali & Xiaochun Liu, 2015. "Foreign exchange predictability during the financial crisis: implications for carry trade profitability," FRB Atlanta Working Paper 2015-6, Federal Reserve Bank of Atlanta.
  3. Liu, Xiaochun, 2013. "Markov-Switching Quantile Autoregression," MPRA Paper 55800, University Library of Munich, Germany.
  4. Liu, Xiaochun, 2013. "Systemic Risk of Commercial Banks: A Markov-Switching Quantile Autoregression Approach," MPRA Paper 55801, University Library of Munich, Germany.
  5. Liu, Xiaochun, 2011. "Modeling the time-varying skewness via decomposition for out-of-sample forecast," MPRA Paper 41248, University Library of Munich, Germany.
  6. Liu, Xiaochun & Jacobsen, Brian, 2011. "The Dynamic International Optimal Hedge Ratio," MPRA Paper 35260, University Library of Munich, Germany.

Articles

  1. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2024. "Are exchange rates absorbers of global oil shocks? A generalized structural analysis," Journal of International Money and Finance, Elsevier, vol. 146(C).
  2. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).
  3. Liu, Xiaochun, 2021. "On fiscal and monetary policy-induced macroeconomic volatility dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
  4. Liu, Xiaochun, 2020. "Quantile-Based Asymmetric Dynamics Of Real Gdp Growth," Macroeconomic Dynamics, Cambridge University Press, vol. 24(8), pages 1960-1988, December.
  5. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).
  6. Yu You & Xiaochun Liu, 2019. "Cyclicality of stock market volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 26(8), pages 645-649, May.
  7. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
  8. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
  9. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
  10. Xiaochun Liu, 2018. "How is the Taylor Rule Distributed under Endogenous Monetary Regimes?," International Review of Finance, International Review of Finance Ltd., vol. 18(2), pages 305-316, June.
  11. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.
  12. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
  13. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
  14. Liu, Xiaochun, 2017. "Measuring systemic risk with regime switching in tails," Economic Modelling, Elsevier, vol. 67(C), pages 55-72.
  15. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017. "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 199-211.
  16. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
  17. Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.
  18. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
  19. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.
  20. Jacobsen, Brian J. & Liu, Xiaochun, 2008. "China's segmented stock market: An application of the conditional international capital asset pricing model," Emerging Markets Review, Elsevier, vol. 9(3), pages 153-173, September.

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. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.

    Cited by:

    1. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    2. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    3. Tobias Fissler & Yannick Hoga, 2021. "Backtesting Systemic Risk Forecasts using Multi-Objective Elicitability," Papers 2104.10673, arXiv.org, revised Feb 2022.

  2. Liu, Xiaochun, 2013. "Markov-Switching Quantile Autoregression," MPRA Paper 55800, University Library of Munich, Germany.

    Cited by:

    1. Gabriel Montes-Rojas & Zacharias Psaradakis & Martín Sola, 2024. "On Regime Separation in Markov-Switching Quantile Regressions," Department of Economics Working Papers 2024_05, Universidad Torcuato Di Tella.
    2. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    3. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
    4. Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
    5. Xiaochun Liu, 2018. "How is the Taylor Rule Distributed under Endogenous Monetary Regimes?," International Review of Finance, International Review of Finance Ltd., vol. 18(2), pages 305-316, June.

  3. Liu, Xiaochun, 2011. "Modeling the time-varying skewness via decomposition for out-of-sample forecast," MPRA Paper 41248, University Library of Munich, Germany.

    Cited by:

    1. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.
    2. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    3. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    4. Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.
    5. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
    6. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).

Articles

  1. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).

    Cited by:

    1. Stewart, Shamar L. & Isengildina Massa, Olga, 2024. "Food & Oil Price Volatility Dynamics: Insights from a TVP-SVAR-DCC-MIDAS Model," 2024 Annual Meeting, July 28-30, New Orleans, LA 343936, Agricultural and Applied Economics Association.

  2. Liu, Xiaochun, 2021. "On fiscal and monetary policy-induced macroeconomic volatility dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).

    Cited by:

    1. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).

  3. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Bernd Wilfling, 2022. "Forecasting Stock Market Volatility with Regime-Switching GARCH-MIDAS: The Role of Geopolitical Risks," Working Papers 202203, University of Pretoria, Department of Economics.
    2. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    3. J.A. Batten & Sabri Boubaker & H. Kinateder & T. Choudhury & N.F. Wagner, 2023. "Volatility Impacts on Global Banks: Insights from the GFC, COVID-19, and the Russia-Ukraine War," Post-Print hal-04435440, HAL.
    4. Luo, Tao & Sun, Huaping & Zhang, Lixia & Bai, Jiancheng, 2024. "Do the dynamics of macroeconomic attention drive the yen/dollar exchange market volatility?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 597-611.
    5. Batten, Jonathan A. & Mo, Di & Pourkhanali, Armin, 2024. "Can inflation predict energy price volatility?," Energy Economics, Elsevier, vol. 129(C).
    6. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    7. Lyu, Yongjian & Qin, Fanshu & Ke, Rui & Wei, Yu & Kong, Mengzhen, 2024. "Does mixed frequency variables help to forecast value at risk in the crude oil market?," Resources Policy, Elsevier, vol. 88(C).
    8. Adediran, Idris A. & Swaray, Raymond, 2023. "Carbon trading amidst global uncertainty: The role of policy and geopolitical uncertainty," Economic Modelling, Elsevier, vol. 123(C).
    9. Wang, Xinyu & Qi, Zikang & Huang, Jianglu, 2023. "How do monetary shock, financial crisis, and quotation reform affect the long memory of exchange rate volatility? Evidence from major currencies," Economic Modelling, Elsevier, vol. 120(C).
    10. Yemba, Boniface P. & Otunuga, Olusegun Michael & Tang, Biyan & Biswas, Nabaneeta, 2023. "Nowcasting of the Short-run Euro-Dollar Exchange Rate with Economic Fundamentals and Time-varying Parameters," Finance Research Letters, Elsevier, vol. 52(C).
    11. Damien Kunjal & Faeezah Peerbhai & Paul-Francois Muzindutsi, 2022. "Political, economic, and financial country risks and the volatility of the South African Exchange Traded Fund market: A GARCH-MIDAS approach," Risk Management, Palgrave Macmillan, vol. 24(3), pages 236-258, September.
    12. Zhang, Lixia & Bai, Jiancheng & Zhang, Yueyan & Cui, Can, 2023. "Global economic uncertainty and the Chinese stock market: Assessing the impacts of global indicators," Research in International Business and Finance, Elsevier, vol. 65(C).
    13. Riza Demirer & Rangan Gupta & He Li & Yu You, 2021. "Financial Vulnerability and Volatility in Emerging Stock Markets: Evidence from GARCH-MIDAS Models," Working Papers 202112, University of Pretoria, Department of Economics.
    14. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    15. Zuzana Rowland & George Lazaroiu & Ivana Podhorská, 2020. "Use of Neural Networks to Accommodate Seasonal Fluctuations When Equalizing Time Series for the CZK/RMB Exchange Rate," Risks, MDPI, vol. 9(1), pages 1-21, December.
    16. Ding, Shusheng & Cui, Tianxiang & Wu, Xiangling & Du, Min, 2022. "Supply chain management based on volatility clustering: The effect of CBDC volatility," Research in International Business and Finance, Elsevier, vol. 62(C).
    17. Davood Pirayesh Neghab & Mucahit Cevik & M. I. M. Wahab, 2023. "Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning," Papers 2303.16149, arXiv.org.
    18. Chaturvedi, Priya & Kumar, Kuldeep, 2022. "Econometric modelling of exchange rate volatility using mixed-frequency data," MPRA Paper 115222, University Library of Munich, Germany.
    19. Wu, Xinyu & Xie, Haibin & Zhang, Huanming, 2022. "Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).

  4. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).

    Cited by:

    1. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022. "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, vol. 46(PA).
    2. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    3. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    4. Siddhartha Chib & Minchul Shin & Fei Tan, 2020. "High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗," Working Papers 20-35, Federal Reserve Bank of Philadelphia.
    5. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2020. "Modelling Returns in US Housing Prices – You’re the One for Me, Fat Tails," Working Papers 2020:13, Örebro University, School of Business.
    6. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    7. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    8. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.

  5. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.

    Cited by:

    1. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
    2. Donald Lien & Ziling Wang & Xiaojian Yu, 2021. "Optimal quantile hedging under Markov regime switching," Empirical Economics, Springer, vol. 60(5), pages 2177-2201, May.
    3. Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
    4. Maruotti, Antonello & Petrella, Lea & Sposito, Luca, 2021. "Hidden semi-Markov-switching quantile regression for time series," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).

  6. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.

    Cited by:

    1. Fengler, Matthias & Polivka, Jeannine, 2022. "Structural Volatility Impulse Response Analysis," Economics Working Paper Series 2211, University of St. Gallen, School of Economics and Political Science.
    2. Liu, Xiaochun, 2021. "On fiscal and monetary policy-induced macroeconomic volatility dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    3. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).

  7. Xiaochun Liu, 2018. "How is the Taylor Rule Distributed under Endogenous Monetary Regimes?," International Review of Finance, International Review of Finance Ltd., vol. 18(2), pages 305-316, June.

    Cited by:

    1. Christou Christina & Naraidoo Ruthira & Gupta Rangan, 2020. "Conventional and unconventional monetary policy reaction to uncertainty in advanced economies: evidence from quantile regressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-17, June.
    2. Christina Christou & Ruthira Naraidoo & Rangan Gupta & Christis Hassapis, 2019. "Monetary Policy Reaction to Uncertainty in Japan: Evidence from a Quantile-on-Quantile Interest Rate Rule," Working Papers 201929, University of Pretoria, Department of Economics.

  8. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.

    Cited by:

    1. Suzanne G. M. Fifield & David G. McMillan & Fiona J. McMillan, 2020. "Is there a risk and return relation?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(11), pages 1075-1101, July.

  9. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.

    Cited by:

    1. Wen, Fenghua & Zhang, Minzhi & Xiao, Jihong & Yue, Wei, 2022. "The impact of oil price shocks on the risk-return relation in the Chinese stock market," Finance Research Letters, Elsevier, vol. 47(PB).
    2. Tsuji, Chikashi, 2020. "Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management," International Review of Financial Analysis, Elsevier, vol. 70(C).
    3. John Cotter & Enrique Salvador, 2022. "The non-linear trade-off between return and risk and its determinants," Working Papers 202203, Geary Institute, University College Dublin.
    4. Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
    5. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
    6. Shoka Hayaki, 2024. "The Impact of Individual Loss Aversion on Market Risk-Return Trade-off: A Non-linear Approach," Discussion Paper Series DP2024-05, Research Institute for Economics & Business Administration, Kobe University.
    7. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

  10. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.

    Cited by:

    1. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.

  11. Liu, Xiaochun, 2017. "Measuring systemic risk with regime switching in tails," Economic Modelling, Elsevier, vol. 67(C), pages 55-72.

    Cited by:

    1. Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
    2. Marion Dupire & Christian Haddad & Regine Slagmulder, 2022. "The Importance of Board Risk Oversight in Times of Crisis," Journal of Financial Services Research, Springer;Western Finance Association, vol. 61(3), pages 319-365, June.
    3. Nandita Bhattacharjee & Ambika Prasad Pati, 2023. "Exploring Systemic Risk Measurement Issues in Shadow Banks: A Case of an Emerging Economy," South Asian Journal of Macroeconomics and Public Finance, , vol. 12(2), pages 186-217, December.
    4. Adnan Safi & Xianrong Yi & Salman Wahab & Yingying Chen & Hassan Hassan, 2021. "CEO overconfidence, firm-specific factors, and systemic risk: evidence from China," Risk Management, Palgrave Macmillan, vol. 23(1), pages 30-47, June.
    5. Ben Ameur, Hachmi & Jawadi, Fredj & Jawadi, Nabila & Cheffou, Abdoulkarim Idi, 2020. "Assessing downside and upside risk spillovers across conventional and socially responsible stock markets," Economic Modelling, Elsevier, vol. 88(C), pages 200-210.
    6. Badarau, Cristina & Lapteacru, Ion, 2020. "Bank risk, competition and bank connectedness with firms: A literature review," Research in International Business and Finance, Elsevier, vol. 51(C).
    7. Fengyun Liu & Chuanzhe Liu & Honghao Ren, 2018. "Urban Housing Price Fluctuations and Regional Systemic Financial Risks: Panel Spatial Economic Models in Jiangsu, China," Sustainability, MDPI, vol. 10(10), pages 1-17, September.
    8. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    9. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
    10. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2021. "Systemically important banks in Asian emerging markets: Evidence from four systemic risk measures," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    11. Van Cauwenberge, Annelies & Vancauteren, Mark & Braekers, Roel & Vandemaele, Sigrid, 2019. "International trade, foreign direct investments, and firms’ systemic risk : Evidence from the Netherlands," Economic Modelling, Elsevier, vol. 81(C), pages 361-386.
    12. Zhang, Ailian & Pan, Mengmeng & Liu, Bai & Weng, Yin-Che, 2020. "Systemic risk: The coordination of macroprudential and monetary policies in China," Economic Modelling, Elsevier, vol. 93(C), pages 415-429.
    13. Fenghua Wen & Kaiyan Weng & Wei-Xing Zhou, 2020. "Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach," Risk Management, Palgrave Macmillan, vol. 22(4), pages 310-337, December.
    14. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).
    15. Li, Xindan & Yu, Honghai & Fang, Libing & Xiong, Cheng, 2019. "Do firm-level factors play forward-looking role for financial systemic risk: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).

  12. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017. "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 199-211.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Maake, Tebogo & Bonga-Bonga, Lumengo, 2019. "The relationship between carry trade and asset markets in South Africa," MPRA Paper 96667, University Library of Munich, Germany.
    3. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    4. Qian Zhang & Kuo-Jui Wu & Ming-Lang Tseng, 2019. "Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
    5. Fu, Hsuan & Luger, Richard, 2022. "Multiple testing of the forward rate unbiasedness hypothesis across currencies," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 232-245.

  13. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
    See citations under working paper version above.
  14. Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Suzanne G. M. Fifield & David G. McMillan & Fiona J. McMillan, 2020. "Is there a risk and return relation?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(11), pages 1075-1101, July.
    3. Osman Kilic & Joseph M. Marks & Kiseok Nam, 2022. "Predictable asset price dynamics, risk-return tradeoff, and investor behavior," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 749-791, August.
    4. Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
    5. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.
    6. Liu, Jingzhen, 2019. "Impacts of lagged returns on the risk-return relationship of Chinese aggregate stock market: Evidence from different data frequencies," Research in International Business and Finance, Elsevier, vol. 48(C), pages 243-257.
    7. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
    8. Sunday Akpan & Fauziah Mahat & Bany-Ariffin Noordin & Annuar Nassir, 2017. "Revisiting Insurance Capital Structure, Risk-Taking Behaviour and Performance between 1995 – 2002," Asian Social Science, Canadian Center of Science and Education, vol. 13(11), pages 128-128, November.
    9. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    10. Shoka Hayaki, 2024. "The Impact of Individual Loss Aversion on Market Risk-Return Trade-off: A Non-linear Approach," Discussion Paper Series DP2024-05, Research Institute for Economics & Business Administration, Kobe University.
    11. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

  15. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    See citations under working paper version above.
  16. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    3. Stanislav Anatolyev & Nikolay Gospodinov, 2015. "Multivariate return decomposition: theory and implications," FRB Atlanta Working Paper 2015-7, Federal Reserve Bank of Atlanta.
    4. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
    5. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.
    6. León, Ángel & Ñíguez, Trino-Manuel, 2021. "The transformed Gram Charlier distribution: Parametric properties and financial risk applications," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 323-349.
    7. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    8. Simon Lalancette & Jean†Guy Simonato, 2017. "The Role of the Conditional Skewness and Kurtosis in VIX Index Valuation," European Financial Management, European Financial Management Association, vol. 23(2), pages 325-354, March.
    9. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
    10. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    11. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).

  17. Jacobsen, Brian J. & Liu, Xiaochun, 2008. "China's segmented stock market: An application of the conditional international capital asset pricing model," Emerging Markets Review, Elsevier, vol. 9(3), pages 153-173, September.

    Cited by:

    1. Antonio Diez de los Rios, 2007. "Exchange Rate Regimes, Globalisation, and the Cost of Capital in Emerging Markets," Staff Working Papers 07-29, Bank of Canada.
    2. Huang, Lin & Wu, Jia & Zhang, Rui, 2014. "Exchange risk and asset returns: A theoretical and empirical study of an open economy asset pricing model," Emerging Markets Review, Elsevier, vol. 21(C), pages 96-116.
    3. Lehkonen, Heikki, 2010. "Bubbles in China," International Review of Financial Analysis, Elsevier, vol. 19(2), pages 113-117, March.
    4. Korkmaz, Turhan & Cevik, Emrah Ismail & Gurkan, Serhan, 2010. "Testing the international capital asset pricing model with Markov switching model in emerging markets," MPRA Paper 71481, University Library of Munich, Germany, revised 2010.

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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-RMG: Risk Management (4) 2011-12-13 2014-05-17 2020-10-26 2020-11-23
  2. NEP-FOR: Forecasting (3) 2015-11-01 2020-10-26 2020-11-23
  3. NEP-ECM: Econometrics (2) 2014-05-17 2020-10-26
  4. NEP-BAN: Banking (1) 2014-05-17
  5. NEP-ETS: Econometric Time Series (1) 2014-05-17
  6. NEP-MAC: Macroeconomics (1) 2014-05-17
  7. NEP-OPM: Open Economy Macroeconomics (1) 2015-11-01
  8. NEP-ORE: Operations Research (1) 2020-11-23

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