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Yin Liao

Personal Details

First Name:Yin
Middle Name:
Last Name:Liao
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RePEc Short-ID:pli536

Affiliation

(90%) School of Economics and Finance
Business School
Queensland University of Technology

Brisbane, Australia
https://www.qut.edu.au/business/about/school-of-economics-and-finance
RePEc:edi:sequtau (more details at EDIRC)

(10%) Centre for Applied Macroeconomic Analysis (CAMA)
Crawford School of Public Policy
Australian National University

Canberra, Australia
https://cama.crawford.anu.edu.au/
RePEc:edi:cmanuau (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
  2. Serkan Arslanalp & Yin Liao, 2013. "Contingent Liabilities and Sovereign Risk: Evidence from Banking Sectors," CAMA Working Papers 2013-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  3. Di Bu & Yin Liao, 2013. "Structural Credit Risk Model with Stochastic Volatility: A Particle-filter Approach," NCER Working Paper Series 98, National Centre for Econometric Research.
  4. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.
  5. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
  6. Yin Liao, 2012. "Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction," CAMA Working Papers 2012-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  7. Yin Liao & John Stachurski, 2011. "Parametric Conditional Monte Carlo Density Estimation," ANU Working Papers in Economics and Econometrics 2011-562, Australian National University, College of Business and Economics, School of Economics.
  8. Yin Liao & Heather M. Anderson, 2011. "Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices," Monash Econometrics and Business Statistics Working Papers 9/11, Monash University, Department of Econometrics and Business Statistics.
  9. Yin Liao & Heather M. Anderson & Farshid Vahid, 2010. "Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps," Monash Econometrics and Business Statistics Working Papers 11/10, Monash University, Department of Econometrics and Business Statistics.
  10. Adam Clements & Yin Liao, "undated". "News and network structures in equity market volatility," NCER Working Paper Series 110, National Centre for Econometric Research.

Articles

  1. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
  2. Di Bu & Yin Liao, 2016. "The Small and Medium Enterprises and the Credit Reporting System in China," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 41-48.
  3. Yin Liao & John Stachurski, 2015. "Simulation-Based Density Estimation for Time Series Using Covariate Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 595-606, October.
  4. Bu, Di & Liao, Yin, 2014. "Corporate credit risk prediction under stochastic volatility and jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 263-281.
  5. Arslanalp, Serkan & Liao, Yin, 2014. "Banking sector contingent liabilities and sovereign risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 316-330.
  6. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.

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. Serkan Arslanalp & Yin Liao, 2013. "Contingent Liabilities and Sovereign Risk: Evidence from Banking Sectors," CAMA Working Papers 2013-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Corsetti, Giancarlo & Kuester, Keith & Meier, André & Müller, Gernot J., 2014. "Sovereign risk and belief-driven fluctuations in the euro area," Journal of Monetary Economics, Elsevier, vol. 61(C), pages 53-73.
    2. Ms. Elva Bova & Marta Ruiz-Arranz & Mr. Frederik G Toscani & H. Elif Ture, 2016. "The Fiscal Costs of Contingent Liabilities: A New Dataset," IMF Working Papers 2016/014, International Monetary Fund.
    3. Choy, Swee Yew & Chit, Myint Moe & Teo, Wing Leong, 2021. "Sovereign credit ratings: Discovering unorthodox factors and variables," Global Finance Journal, Elsevier, vol. 48(C).

  2. Di Bu & Yin Liao, 2013. "Structural Credit Risk Model with Stochastic Volatility: A Particle-filter Approach," NCER Working Paper Series 98, National Centre for Econometric Research.

    Cited by:

    1. Jessen, Cathrine & Lando, David, 2015. "Robustness of distance-to-default," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 493-505.

  3. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.

    Cited by:

    1. Márcio Poletti Laurini & Roberto Baltieri Mauad & Fernando Antonio Lucena Aiube, 2016. "Multivariate Stochastic Volatility-Double Jump Model: an application for oil assets," Working Papers Series 415, Central Bank of Brazil, Research Department.
    2. Caporin, Massimiliano & Kolokolov, Aleksey & Renò, Roberto, 2014. "Multi-jumps," MPRA Paper 58175, University Library of Munich, Germany.
    3. Laurini, Márcio Poletti & Mauad, Roberto Baltieri, 2015. "A common jump factor stochastic volatility model," Finance Research Letters, Elsevier, vol. 12(C), pages 2-10.
    4. Andrey Itkin, 2017. "Modeling stochastic skew of FX options using SLV models with stochastic spot/vol correlation and correlated jumps," Papers 1701.02821, arXiv.org, revised Jan 2017.
    5. Baruník Jozef & Fišer Pavel, 2024. "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(3), pages 481-506.
    6. Gresnigt, Francine & Kole, Erik & Franses, Philip Hans, 2015. "Interpreting financial market crashes as earthquakes: A new Early Warning System for medium term crashes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 123-139.

  4. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.

    Cited by:

    1. Arnerić Josip & Poklepović Tea & Teai Juin Wen, 2018. "Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data," Business Systems Research, Sciendo, vol. 9(2), pages 18-34, July.

  5. Yin Liao & Heather M. Anderson, 2011. "Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices," Monash Econometrics and Business Statistics Working Papers 9/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Cao, Guangxi & Han, Yan & Cui, Weijun & Guo, Yu, 2014. "Multifractal detrended cross-correlations between the CSI 300 index futures and the spot markets based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 308-320.
    2. LUPU, Radu & MATEESCU, Alexandra, 2016. "Systemic Risk And Cojumps In High Frequency Data," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 20(4), pages 6-16.
    3. Guido Russi, 2012. "Estimating the Leverage Effect Using High Frequency Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 1-24, February.
    4. Zebende, G.F. & da Silva, M.F. & Machado Filho, A., 2013. "DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1756-1761.

  6. Yin Liao & Heather M. Anderson & Farshid Vahid, 2010. "Do Jumps Matter? Forecasting Multivariate Realized Volatility allowing for Common Jumps," Monash Econometrics and Business Statistics Working Papers 11/10, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jin, Xiaoye, 2015. "Volatility transmission and volatility impulse response functions among the Greater China stock markets," Journal of Asian Economics, Elsevier, vol. 39(C), pages 43-58.
    2. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
    3. Yuta Koike, 2014. "An estimator for the cumulative co-volatility of asynchronously observed semimartingales with jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 460-481, June.
    4. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    5. Yin Liao, 2012. "Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction," CAMA Working Papers 2012-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2013. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 28/13, Monash University, Department of Econometrics and Business Statistics.
    7. Mohammad Abu Sayeed & Mardi Dungey & Wenying Yao, 2018. "High-frequency Characterisation of Indian Banking Stocks," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 213-238, August.

Articles

  1. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.

    Cited by:

    1. Arif, Muhammad & Naeem, Muhammad Abubakr & Farid, Saqib & Nepal, Rabindra & Jamasb, Tooraj, 2022. "Diversifier or more? Hedge and safe haven properties of green bonds during COVID-19," Energy Policy, Elsevier, vol. 168(C).
    2. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
    3. Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
    4. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    5. Xu, Fang & Bouri, Elie & Cepni, Oguzhan, 2022. "Blockchain and crypto-exposed US companies and major cryptocurrencies: The role of jumps and co-jumps," Finance Research Letters, Elsevier, vol. 50(C).
    6. Chen, Yan & Zhang, Lei & Bouri, Elie, 2024. "Can a self-exciting jump structure better capture the jump behavior of cryptocurrencies? A comparative analysis with the S&P 500," Research in International Business and Finance, Elsevier, vol. 69(C).
    7. Anupam Dutta & Debojyoti Das, 2022. "Forecasting realized volatility: New evidence from time‐varying jumps in VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2165-2189, December.
    8. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.
    9. Fan, Lina & Yang, Hao & Zhai, Jia & Zhang, Xiaotao, 2023. "Forecasting stock volatility during the stock market crash period: The role of Hawkes process," Finance Research Letters, Elsevier, vol. 55(PA).
    10. Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2020. "Do Bitcoin and other cryptocurrencies jump together?," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 396-409.
    11. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    12. Ran Xiao, 2019. "Essays on Price Discovery and Volatility Dynamics in Emerging Market Currencies," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2019, January-A.
    13. Song, Shijia & Li, Handong, 2023. "Is a co-jump in prices a sparse jump?," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    14. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    15. Guo, Yangli & Li, Pan & Wu, Hanlin, 2023. "Jumps in the Chinese crude oil futures volatility forecasting: New evidence," Energy Economics, Elsevier, vol. 126(C).
    16. Maria Čuljak & Josip Arnerić & Ante Žigman, 2022. "Is Jump Robust Two Times Scaled Estimator Superior among Realized Volatility Competitors?," Mathematics, MDPI, vol. 10(12), pages 1-11, June.
    17. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
    18. Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
    19. Nicolás Magner Pulgar & Esteban José Antonio Terán Sánchez & Vicente Alfonso Guzmán Muñoz, 2022. "Stock Market Synchronization and Stock Volatility: The Case of an Emerging Market," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 17(3), pages 1-22, Julio - S.
    20. Zeng, Qing & Lu, Xinjie & Li, Tao & Wu, Lan, 2022. "Jumps and stock market variance during the COVID-19 pandemic: Evidence from international stock markets," Finance Research Letters, Elsevier, vol. 48(C).
    21. Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
    22. Elie Bouri, 2019. "The Effect of Jumps in the Crude Oil Market on the Sovereign Risks of Major Oil Exporters," Risks, MDPI, vol. 7(4), pages 1-15, December.
    23. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    24. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.

  2. Yin Liao & John Stachurski, 2015. "Simulation-Based Density Estimation for Time Series Using Covariate Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 595-606, October.

    Cited by:

    1. Li, Shuo & Tu, Yundong, 2016. "n-consistent density estimation in semiparametric regression models," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 91-109.

  3. Bu, Di & Liao, Yin, 2014. "Corporate credit risk prediction under stochastic volatility and jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 263-281.

    Cited by:

    1. Pascal Damel & Hoai An Le Thi & Nadège Peltre, 2016. "The challenge in managing new financial risks: adopting an heuristic or theoretical approach," Annals of Operations Research, Springer, vol. 247(2), pages 581-598, December.
    2. Xiao, Weilin & Zhang, Xili, 2016. "Pricing equity warrants with a promised lowest price in Merton’s jump–diffusion model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 219-238.
    3. Turalay Kenc & Emrah Ismail Cevik, 2021. "Estimating volatility clustering and variance risk premium effects on bank default indicators," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1373-1392, November.
    4. Haixiang Yao & Xun Li & Zhifeng Hao & Yong Li, 2016. "Dynamic asset–liability management in a Markov market with stochastic cash flows," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1575-1597, October.

  4. Arslanalp, Serkan & Liao, Yin, 2014. "Banking sector contingent liabilities and sovereign risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 316-330.

    Cited by:

    1. Du Jianguo & Rauf Ibrahim & Peter Lartey Yao & Rupa Jaladi Santosh & Amponsah Clinton Kwabena, 2019. "The Effectiveness of Internal Controls in Rural Community Banks: Evidence from Ghana," Business Management and Strategy, Macrothink Institute, vol. 10(1), pages 202-218, December.
    2. Serhan Cevik & Belma Öztürkkal, 2021. "Contagion of fear: Is the impact of COVID‐19 on sovereign risk really indiscriminate?," International Finance, Wiley Blackwell, vol. 24(2), pages 134-154, August.
    3. Claudio Borio & Marco Jacopo Lombardi & Fabrizio Zampolli, 2016. "Fiscal sustainability and the financial cycle," BIS Working Papers 552, Bank for International Settlements.
    4. Yixuan Duan & Min Guo & Yixuan Huang, 2022. "Leverage of Local State-Owned Enterprises, Implicit Contingent Liabilities of Government and Economic Growth," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    5. Fiordelisi, Franco & Girardone, Claudia & Minnucci, Federica & Ricci, Ornella, 2020. "On the nexus between sovereign risk and banking crises," Journal of Corporate Finance, Elsevier, vol. 65(C).
    6. Diana Žigraiová & Aitor Erce & Xu Jiang, 2020. "Quantifying risks to sovereign market access: Methods and challenges," Working Papers 42, European Stability Mechanism.
    7. Manish K. Singh & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2019. "“Increasing contingent guarantees: The asymmetrical effect on sovereign risk of different government interventions"," IREA Working Papers 201914, University of Barcelona, Research Institute of Applied Economics, revised Sep 2019.
    8. Mr. Serkan Arslanalp & Yin Liao, 2015. "Contingent Liabilities from Banks: How to Track Them?," IMF Working Papers 2015/255, International Monetary Fund.
    9. Keddad, Benjamin & Schalck, Christophe, 2020. "Evaluating sovereign risk spillovers on domestic banks during the European debt crisis," Economic Modelling, Elsevier, vol. 88(C), pages 356-375.
    10. Mohammadreza Janvisloo Alizadeh & Reza Sherafatian-Jahromi, 2017. "Merton Model and Capital Measurement in Commercial Banks: A Case Study of Selected Emerging Countries in Southeast Asia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 169-191, September.
    11. Yu, Sherry, 2017. "Sovereign and bank Interdependencies—Evidence from the CDS market," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 68-84.
    12. Rho, Caterina & Saenz, Manrique, 2021. "Financial stress and the probability of sovereign default," Journal of International Money and Finance, Elsevier, vol. 110(C).

  5. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.

    Cited by:

    1. Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    2. Vortelinos, Dimitrios I., 2016. "Incremental information of stock indicators," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 79-97.
    3. Liao, Yin & Anderson, Heather M., 2019. "Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
    4. Rangan Gupta & Chi Keng Marco Lau & Ruipeng Liu & Hardik A. Marfatia, 2017. "Price Jumps in Developed Stock Markets: The Role of Monetary Policy Committee Meetings," Working Papers 201727, University of Pretoria, Department of Economics.
    5. Song, Yuping & Huang, Jiefei & Zhang, Qichao & Xu, Yang, 2024. "Heterogeneity effect of positive and negative jumps on the realized volatility: Evidence from China," Economic Modelling, Elsevier, vol. 136(C).
    6. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    7. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    8. Li, Jie & Li, Guangzhong & Zhou, Yinggang, 2015. "Do securitized real estate markets jump? International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 31(C), pages 13-35.
    9. Chan, Kam Fong & Powell, John G. & Treepongkaruna, Sirimon, 2014. "Currency jumps and crises: Do developed and emerging market currencies jump together?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 132-157.
    10. Wang, Hao & Yue, Mengqi & Zhao, Hua, 2015. "Cojumps in China's spot and stock index futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 541-557.
    11. Linnenluecke, Martina K. & Chen, Xiaoyan & Ling, Xin & Smith, Tom & Zhu, Yushu, 2016. "Emerging trends in Asia-Pacific finance research: A review of recent influential publications and a research agenda," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 66-76.
    12. Cong-Duc Tran & Minh-Tuan Phung & Fu-Ju Yang & Yi-Hsien Wang, 2020. "The Role of Gender Diversity in Downside Risk: Empirical Evidence from Vietnamese Listed Firms," Mathematics, MDPI, vol. 8(6), pages 1-22, June.
    13. Wang, Li-Hsun & Lin, Chu-Hsiung & Fung, Hung-Gay & Chen, Hsien-Ming, 2015. "Governance mechanisms and downside risk," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 485-498.

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 10 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 (5) 2010-05-15 2010-05-22 2011-08-29 2011-10-22 2013-11-02. Author is listed
  2. NEP-ETS: Econometric Time Series (3) 2010-05-15 2011-08-29 2013-09-28
  3. NEP-FOR: Forecasting (3) 2010-05-15 2010-05-22 2014-06-28
  4. NEP-MST: Market Microstructure (3) 2010-05-15 2011-08-29 2014-06-28
  5. NEP-ORE: Operations Research (2) 2013-09-28 2013-11-02
  6. NEP-RMG: Risk Management (2) 2012-07-08 2013-11-02
  7. NEP-BAN: Banking (1) 2013-11-02
  8. NEP-CBA: Central Banking (1) 2013-07-28
  9. NEP-CIS: Confederation of Independent States (1) 2011-10-22
  10. NEP-EEC: European Economics (1) 2013-07-28
  11. NEP-NET: Network Economics (1) 2016-05-21

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