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Junye Li

Personal Details

First Name:Junye
Middle Name:
Last Name:Li
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RePEc Short-ID:pli421
http://junye.li.googlepages.com

Affiliation

Dipartimento di Economia "Ettore Bocconi"
Università Commerciale Luigi Bocconi

Milano, Italy
http://www.unibocconi.it/wps/wcm/connect/Bocconi/SitoPubblico_IT/Albero+di+navigazione/Home/Docenti+e+Ricerca/Dipartimenti/Economia+0.000000E+00ttore+Bocconi%24
RePEc:edi:debocit (more details at EDIRC)

Research output

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Jump to: Working papers Articles

Working papers

  1. Junye Li & Gabriele Zinna, 2014. "On bank credit risk: systemic or bank-specific? Evidence from the US and UK," Temi di discussione (Economic working papers) 951, Bank of Italy, Economic Research and International Relations Area.
  2. Andras Fulop & Junye Li & Jun Yu, 2012. "Investigating Impacts of Self-Exciting Jumps in Returns and Volatility: A Bayesian Learning Approach," Global COE Hi-Stat Discussion Paper Series gd12-264, Institute of Economic Research, Hitotsubashi University.

Articles

  1. Andras Fulop & Junye Li & Jun Yu, 2015. "Self-Exciting Jumps, Learning, and Asset Pricing Implications," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 876-912.
  2. Yin, Weiwei & Li, Junye, 2014. "Macroeconomic fundamentals and the exchange rate dynamics: A no-arbitrage macro-finance approach," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 46-64.
  3. Li, Junye & Zinna, Gabriele, 2014. "On Bank Credit Risk: Systemic or Bank Specific? Evidence for the United States and United Kingdom," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(5-6), pages 1403-1442, December.
  4. Li, Junye, 2012. "Option-implied volatility factors and the cross-section of market risk premia," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 249-260.

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. Junye Li & Gabriele Zinna, 2014. "On bank credit risk: systemic or bank-specific? Evidence from the US and UK," Temi di discussione (Economic working papers) 951, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Junye Li & Gabriele Zinna, 2014. "How much of bank credit risk is sovereign risk? Evidence from the eurozone," Temi di discussione (Economic working papers) 990, Bank of Italy, Economic Research and International Relations Area.
    2. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2021. "A Bayesian panel stochastic volatility measure of financial stability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5363-5384, October.
    3. Michele Bonollo & Irene Crimaldi & Andrea Flori & Fabio Pammolli & Massimo Riccaboni, 2014. "Systemic importance of financial institutions: regulations, research, open issues, proposals," Working Papers 2/2014, IMT School for Advanced Studies Lucca, revised Mar 2014.
    4. Iryna Kaminska & Gabriele Zinna, 2020. "Official Demand for U.S. Debt: Implications for U.S. Real Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(2-3), pages 323-364, March.
    5. Li, Junye & Sarno, Lucio & Zinna, Gabriele, 2024. "Risks and risk premia in the US Treasury market," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    6. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    7. Sara Cecchetti, 2019. "A Quantitative Analysis of Risk Premia in the Corporate Bond Market," JRFM, MDPI, vol. 13(1), pages 1-33, December.
    8. Junye Li & Gabriele Zinna, 2018. "How Much of Bank Credit Risk Is Sovereign Risk? Evidence from Europe," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1225-1269, September.
    9. Michele Bonollo & Irene Crimaldi & Andrea Flori & Fabio Pammolli & Massimo Riccaboni, 2014. "Systemic importance of financial institutions: from a global to a local perspective? A network theory approach," Working Papers 9/2014, IMT School for Advanced Studies Lucca, revised Sep 2014.
    10. Mamatzakis, Emmanuel C. & Ongena, Steven & Tsionas, Mike G., 2021. "Does alternative finance moderate bank fragility? Evidence from the euro area," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    11. Gabriele Zinna, 2014. "Price pressures in the UK index-linked market: an empirical investigation," Temi di discussione (Economic working papers) 968, Bank of Italy, Economic Research and International Relations Area.
    12. Sara Cecchetti, 2017. "A quantitative analysis of risk premia in the corporate bond market," Temi di discussione (Economic working papers) 1141, Bank of Italy, Economic Research and International Relations Area.

  2. Andras Fulop & Junye Li & Jun Yu, 2012. "Investigating Impacts of Self-Exciting Jumps in Returns and Volatility: A Bayesian Learning Approach," Global COE Hi-Stat Discussion Paper Series gd12-264, Institute of Economic Research, Hitotsubashi University.

    Cited by:

    1. 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.

Articles

  1. Andras Fulop & Junye Li & Jun Yu, 2015. "Self-Exciting Jumps, Learning, and Asset Pricing Implications," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 876-912.

    Cited by:

    1. Juan M. Londono & Nancy R. Xu, 2021. "The Global Determinants of International Equity Risk Premiums," International Finance Discussion Papers 1318, Board of Governors of the Federal Reserve System (U.S.).
    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. Wu, Bin & Chen, Pengzhan & Ye, Wuyi, 2024. "Variance swaps with mean reversion and multi-factor variance," European Journal of Operational Research, Elsevier, vol. 315(1), pages 191-212.
    4. Jin, Xing & Hong, Yi, 2023. "Jump-diffusion volatility models for variance swaps: An empirical performance analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
    5. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    6. Aysan, Ahmet Faruk & Caporin, Massimiliano & Cepni, Oguzhan, 2024. "Not all words are equal: Sentiment and jumps in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    7. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    8. Wan, Runqing & Fulop, Andras & Li, Junye, 2022. "Real-time Bayesian learning and bond return predictability," Journal of Econometrics, Elsevier, vol. 230(1), pages 114-130.
    9. Yan Qu & Angelos Dassios & Hongbiao Zhao, 2023. "Shot-noise cojumps: Exact simulation and option pricing," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(3), pages 647-665, March.
    10. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    11. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    12. Hainaut, Donatien & Moraux, Franck, 2019. "A switching self-exciting jump diffusion process for stock prices," LIDAM Reprints ISBA 2019017, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Carverhill, Andrew & Luo, Dan, 2023. "A Bayesian analysis of time-varying jump risk in S&P 500 returns and options," Journal of Financial Markets, Elsevier, vol. 64(C).
    14. 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).
    15. Hong, Yi & Jin, Xing, 2022. "Pricing of variance swap rates and investment decisions of variance swaps: Evidence from a three-factor model," European Journal of Operational Research, Elsevier, vol. 303(2), pages 975-985.
    16. Riccardo Brignone & Carlo Sgarra, 2020. "Asian options pricing in Hawkes-type jump-diffusion models," Annals of Finance, Springer, vol. 16(1), pages 101-119, March.
    17. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2023. "Shot-noise cojumps: exact simulation and option pricing," LSE Research Online Documents on Economics 111537, London School of Economics and Political Science, LSE Library.
    18. Brignone, Riccardo & Gonzato, Luca & Lütkebohmert, Eva, 2023. "Efficient Quasi-Bayesian Estimation of Affine Option Pricing Models Using Risk-Neutral Cumulants," Journal of Banking & Finance, Elsevier, vol. 148(C).
    19. Gonzato, Luca & Sgarra, Carlo, 2021. "Self-exciting jumps in the oil market: Bayesian estimation and dynamic hedging," Energy Economics, Elsevier, vol. 99(C).
    20. Feng, Guanhao & He, Jingyu, 2022. "Factor investing: A Bayesian hierarchical approach," Journal of Econometrics, Elsevier, vol. 230(1), pages 183-200.
    21. Jing, Bo & Li, Shenghong & Ma, Yong, 2021. "Consistent pricing of VIX options with the Hawkes jump-diffusion model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    22. Milan Fičura & Jiří Witzany, 2018. "Use of Adapted Particle Filters in SVJD Models," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2018(3), pages 5-20.
    23. Ulrich Horst & Wei Xu, 2019. "The Microstructure of Stochastic Volatility Models with Self-Exciting Jump Dynamics," Papers 1911.12969, arXiv.org.
    24. David S. Bates, 2016. "How Crashes Develop: Intradaily Volatility and Crash Evolution," NBER Working Papers 22028, National Bureau of Economic Research, Inc.
    25. Fulop, Andras & Li, Junye, 2019. "Bayesian estimation of dynamic asset pricing models with informative observations," Journal of Econometrics, Elsevier, vol. 209(1), pages 114-138.

  2. Yin, Weiwei & Li, Junye, 2014. "Macroeconomic fundamentals and the exchange rate dynamics: A no-arbitrage macro-finance approach," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 46-64.

    Cited by:

    1. Deven Bathia & Riza Demirer & Rangan Gupta & Kevin Kotze, 2020. "Unemployment Fluctuations and Currency Returns in the United Kingdom: Evidence from Over One and a Half Century of Data," Working Papers 202083, University of Pretoria, Department of Economics.
    2. Ebrahim Hadian; & Najmeh Sajedianfard, 2018. "Monetary Fundamental-Based Exchange Rate Model in Iran: Applying a MS-TVTP Approach," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 22(2), pages 557-578, Spring.
    3. Taoufik Bouraoui, 2019. "External debts, current account balance and exchange rates in emerging countries," Post-Print hal-02329321, HAL.
    4. Works, Richard Floyd, 2016. "Econometric modeling of exchange rate determinants by market classification: An empirical analysis of Japan and South Korea using the sticky-price monetary theory," MPRA Paper 76382, University Library of Munich, Germany.
    5. Brignone, Riccardo & Gonzato, Luca & Lütkebohmert, Eva, 2023. "Efficient Quasi-Bayesian Estimation of Affine Option Pricing Models Using Risk-Neutral Cumulants," Journal of Banking & Finance, Elsevier, vol. 148(C).
    6. Shashank Gupta & Shalini Gupta, 2017. "Modeling economic system using fuzzy cognitive maps," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1472-1486, November.
    7. Luke Lin & Chun I Lee, 2017. "Unmasking the Relationships Between Exchange Rate Exposure and Its Determinants: A More Complete Picture from Quantile Regressions," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-28, December.
    8. Du, Ding & Hu, Ou & Wu, Hong, 2014. "Emerging market currency exposure: Taiwan," Journal of Multinational Financial Management, Elsevier, vol. 28(C), pages 47-61.

  3. Li, Junye & Zinna, Gabriele, 2014. "On Bank Credit Risk: Systemic or Bank Specific? Evidence for the United States and United Kingdom," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(5-6), pages 1403-1442, December.

    Cited by:

    1. Han-Hsing Lee & Kuanyu Shih & Kehluh Wang, 2016. "Measuring sovereign credit risk using a structural model approach," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1097-1128, November.
    2. Iryna Kaminska & Gabriele Zinna, 2020. "Official Demand for U.S. Debt: Implications for U.S. Real Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(2-3), pages 323-364, March.
    3. Li, Junye & Sarno, Lucio & Zinna, Gabriele, 2024. "Risks and risk premia in the US Treasury market," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    4. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    5. Das, Sanjiv R. & Kalimipalli, Madhu & Nayak, Subhankar, 2022. "Banking networks, systemic risk, and the credit cycle in emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    6. Junye Li & Gabriele Zinna, 2018. "How Much of Bank Credit Risk Is Sovereign Risk? Evidence from Europe," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1225-1269, September.
    7. Silva, Felipe Bastos Gurgel, 2021. "Fiscal Deficits, Bank Credit Risk, and Loan-Loss Provisions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(5), pages 1537-1589, August.
    8. Sara Cecchetti, 2017. "A quantitative analysis of risk premia in the corporate bond market," Temi di discussione (Economic working papers) 1141, Bank of Italy, Economic Research and International Relations Area.

  4. Li, Junye, 2012. "Option-implied volatility factors and the cross-section of market risk premia," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 249-260.

    Cited by:

    1. Chiang, Shu Ling & Tsai, Ming Shann, 2023. "Analyses for the effects of investor sentiment on the price adjustment behaviors for stock market and REIT market," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 425-439.
    2. Fang, Libing & Yu, Honghai & Huang, Yingbo, 2018. "The role of investor sentiment in the long-term correlation between U.S. stock and bond markets," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 127-139.
    3. Christian Gouriéroux & Joann Jasiak & Peng Xu, 2013. "Non-tradable S&P 500 Index and the Pricing of Its Traded Derivatives," Working Papers 2013-05, Center for Research in Economics and Statistics.
    4. Goodell, John W. & Vähämaa, Sami, 2013. "US presidential elections and implied volatility: The role of political uncertainty," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1108-1117.
    5. Slim, Skander, 2016. "On the source of stochastic volatility: Evidence from CAC40 index options during the subprime crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 63-76.

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 1 paper 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-BAN: Banking (1) 2014-03-08
  2. NEP-CBA: Central Banking (1) 2014-03-08
  3. NEP-RMG: Risk Management (1) 2014-03-08

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