Osvaldo Candido

Personal Details

First Name:	Osvaldo
Middle Name:
Last Name:	Candido
Suffix:
RePEc Short-ID:	pca1430
	[This author has chosen not to make the email address public]
	https://sites.google.com/view/candido-osvaldo/

Affiliation

Economia
Universidade Católica de Brasilia

Brasilia, Brazil
http://www.ucb.br/Cursos/128MestradoEmEconomia/
RePEc:edi:ecucbbr (more details at EDIRC)

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. Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
   • Tófoli Paula V. & Ziegelmann Flávio A. & Candido Osvaldo & Valls Pereira Pedro L., 2019. "Dynamic D-Vine Copula Model with Applications to Value-at-Risk (VaR)," Journal of Time Series Econometrics, De Gruyter, vol. 11(2), pages 1-34, July.

   Cited by:

   1. Sabino da Silva, Fernando A.B. & Ziegelmann, Flavio A. & Caldeira, João F., 2023. "A pairs trading strategy based on mixed copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 16-34.

Articles

1. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).

   Cited by:

   1. Yunus Santur, 2023. "A Novel Financial Forecasting Approach Using Deep Learning Framework," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1341-1392, October.
   2. David Ardia & Cl'ement Aymard & Tolga Cenesizoglu, 2023. "Fast and Furious: A High-Frequency Analysis of Robinhood Users' Trading Behavior," Papers 2307.11012, arXiv.org.

2. Paulo Roberto Guimarães & Osvaldo Candido & André Ronzani, 2021. "Regularization Methods For Estimating A Multi-Factor Corporate Bond Pricing Model: An Application For Brazil," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-20, March.

   Cited by:

3. Alberto Ronchi Neto & Osvaldo Candido, 2020. "Measuring the neutral real interest rate in Brazil: a semi-structural open economy framework," Empirical Economics, Springer, vol. 58(2), pages 651-667, February.

   Cited by:

   1. Valerie Grossman & Enrique Martínez García & Mark A. Wynne & Ren Zhang, 2019. "Ties That Bind: Estimating the Natural Rate of Interest for Small Open Economies," Globalization Institute Working Papers 359, Federal Reserve Bank of Dallas, revised 05 Mar 2021.
      • Zhang, Ren & Martínez-García, Enrique & Wynne, Mark A. & Grossman, Valerie, 2021. "Ties that bind: Estimating the natural rate of interest for small open economies," Journal of International Money and Finance, Elsevier, vol. 113(C).
   2. Enrique Martínez García, 2020. "Get the Lowdown: The International Side of the Fall in the U.S. Natural Rate of Interest," Globalization Institute Working Papers 403, Federal Reserve Bank of Dallas, revised 20 Feb 2021.
      • Martínez-García, Enrique, 2021. "Get the lowdown: The international side of the fall in the U.S. natural rate of interest," Economic Modelling, Elsevier, vol. 100(C).

4. Washington Martins Silva & Osvaldo Candido, 2020. "Assessing Brazilian electric power transmission auctions," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(1), pages 182-199, February.

   Cited by:

   1. Brandão, Lucas G.L. & Ehrl, Philipp, 2022. "The impact of transmission auctions on Brazilian electric power companies," Utilities Policy, Elsevier, vol. 78(C).

5. Tófoli Paula V. & Ziegelmann Flávio A. & Candido Osvaldo & Valls Pereira Pedro L., 2019. "Dynamic D-Vine Copula Model with Applications to Value-at-Risk (VaR)," Journal of Time Series Econometrics, De Gruyter, vol. 11(2), pages 1-34, July.
   • Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
   See citations under working paper version above.
6. Constantino, Michel & Candido, Osvaldo & Tabak, Benjamin M. & da Costa, Reginaldo Brito, 2017. "Modeling stochastic frontier based on vine copulas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 595-609.

   Cited by:

   1. Silva, Thiago Christiano & Tabak, Benjamin Miranda & Cajueiro, Daniel Oliveira & Dias, Marina Villas Boas, 2018. "Adequacy of deterministic and parametric frontiers to analyze the efficiency of Indian commercial banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1016-1025.
      • Benjamin M. Tabak & Daniel O. Cajueiro & Marina V. B. Dias, 2014. "The Adequacy of Deterministic and Parametric Frontiers to Analyze the Efficiency of Indian Commercial Banks," Working Papers Series 350, Central Bank of Brazil, Research Department.

7. André Ricardo de Pinho Ronzani & Osvaldo Candido & Wilfredo Fernando Leiva Maldonado, 2017. "Goodness-of-Fit versus Significance: A CAPM Selection with Dynamic Betas Applied to the Brazilian Stock Market," IJFS, MDPI, vol. 5(4), pages 1-21, December.

   Cited by:

   1. Jian Huang & Huazhang Liu, 2019. "Examination and Modification of Multi-Factor Model in Explaining Stock Excess Return with Hybrid Approach in Empirical Study of Chinese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-30, May.
   2. Muhammad Adnan Arshad & Saira Munir & Bashir Ahmad & Muhammad Waseem, 2019. "Do factors matter for predicting high-risk stock returns? Comparison of single-, three- and five-factor CAPM," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 1-16, June.

8. Osvaldo Candido Silva Filho & Flavio Augusto Ziegelmann, 2014. "Assessing some stylized facts about financial market indexes: a Markov copula approach," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(2), pages 253-271, March.

   Cited by:

   1. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
   2. Julio Cesar Araujo da Silva Junior, 2017. "An S-Shaped Crude Oil Price Return-Implied Volatility Relation: Parametric and Nonparametric Estimations," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(12), pages 54-70, December.
   3. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.

9. Osvaldo C. Silva Filho & Flavio A. Ziegelmann & Michael J. Dueker, 2014. "Assessing dependence between financial market indexes using conditional time-varying copulas: applications to Value at Risk (VaR)," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2155-2170, December.

   Cited by:

   1. Cui, Yan & Feng, Yun, 2020. "Composite hedge and utility maximization for optimal futures hedging," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 15-32.
   2. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
   3. Han, Yingying & Gong, Pu & Zhou, Xiang, 2016. "Correlations and risk contagion between mixed assets and mixed-asset portfolio VaR measurements in a dynamic view: An application based on time varying copula models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 940-953.
   4. Shirazi, Masoud, 2022. "Assessing energy trilemma-related policies: The world's large energy user evidence," Energy Policy, Elsevier, vol. 167(C).
   5. Bai, Xiwen & Lam, Jasmine Siu Lee, 2019. "A copula-GARCH approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate, product price arbitrage and crude oil price," Energy Economics, Elsevier, vol. 78(C), pages 412-427.
   6. Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," CEEP-BIT Working Papers 102, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
      • Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 929-939, February.
   7. Wafa Miled & Zied Ftiti & Jean-Michel Sahut, 2022. "Spatial contagion between financial markets: new evidence of asymmetric measures," Annals of Operations Research, Springer, vol. 313(2), pages 1183-1220, June.
   8. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
   9. Müller, Fernanda Maria & Santos, Samuel Solgon & Righi, Marcelo Brutti, 2023. "A description of the COVID-19 outbreak role in financial risk forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
   10. Emmanuel Afuecheta & Saralees Nadarajah & Stephen Chan, 2021. "A Statistical Analysis of Global Economies Using Time Varying Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1167-1194, December.
   11. Ki-Hong Choi & Insin Kim, 2021. "Co-Movement between Tourist Arrivals of Inbound Tourism Markets in South Korea: Applying the Dynamic Copula Method Using Secondary Time Series Data," Sustainability, MDPI, vol. 13(3), pages 1-13, January.
   12. He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
   13. Thijs Markwat, 2014. "The rise of global stock market crash probabilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 557-571, April.
   14. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
   15. Marcela de Marillac Carvalho & Luiz Otávio de Oliveira Pala & Gabriel Rodrigo Gomes Pessanha & Thelma Sáfadi, 2021. "Asymmetric dependence of intraday frequency components in the Brazilian stock market," SN Business & Economics, Springer, vol. 1(6), pages 1-18, June.
   16. Peng, Wei & Hu, Shichao & Chen, Wang & Zeng, Yu-feng & Yang, Lu, 2019. "Modeling the joint dynamic value at risk of the volatility index, oil price, and exchange rate," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 137-149.
   17. Sabino da Silva, Fernando A.B. & Ziegelmann, Flavio A. & Caldeira, João F., 2023. "A pairs trading strategy based on mixed copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 16-34.

10. Silva Filho, Osvaldo Candido da & Ziegelmann, Flavio Augusto & Dueker, Michael J., 2012. "Modeling dependence dynamics through copulas with regime switching," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 346-356.

    Cited by:

    1. Yao, Can-Zhong & Sun, Bo-Yi, 2018. "The study on the tail dependence structure between the economic policy uncertainty and several financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 245-265.
    2. Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017. "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 66-87.
    3. Shoukun Jiao & Wuyi Ye, 2022. "Dependence and Systemic Risk Analysis Between S&P 500 Index and Sector Indexes: A Conditional Value-at-Risk Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1203-1229, March.
    4. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
       • Andrieş, Alin Marius & Ongena, Steven & Sprincean, Nicu & Tunaru, Radu, 2022. "Risk spillovers and interconnectedness between systemically important institutions," Journal of Financial Stability, Elsevier, vol. 58(C).
    5. Fousekis, Panos & Grigoriadis, Vasilis, 2017. "Price co-movement and the crack spread in the US futures markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 57-71.
    6. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
    7. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Le, TN-Lan & Leyva-de la Hiz, Dante I., 2021. "Markov-switching dependence between artificial intelligence and carbon price: The role of policy uncertainty in the era of the 4th industrial revolution and the effect of COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    8. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
    9. Aristeidis, Samitas & Elias, Kampouris, 2018. "Empirical analysis of market reactions to the UK’s referendum results – How strong will Brexit be?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 263-286.
    10. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.
        • Semih Emre Cekin & Ashis Kumar Pradhan & Aviral Kumar Tiwari & Rangan Gupta, 2018. "Measuring Co-Dependencies of Economic Policy Uncertainty in Latin American Countries using Vine Copulas," Working Papers 201867, University of Pretoria, Department of Economics.
    11. Guoxiang Xu & Wangfeng Gao, 2019. "Financial Risk Contagion in Stock Markets: Causality and Measurement Aspects," Sustainability, MDPI, vol. 11(5), pages 1-20, March.
    12. Aviral Kumar Tiwari & Goodness C. Aye & Rangan Gupta & Konstantinos Gkillas, 2019. "Gold-Oil Dependence Dynamics and the Role of Geopolitical Risks: Evidence from a Markov-Switching Time-Varying Copula Model," Working Papers 201918, University of Pretoria, Department of Economics.
        • Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    13. Oliveira, André Barbosa & Pereira, Pedro L. Valls, 2018. "Uncertainty times for portfolio selection at financial market," Textos para discussão 473, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    14. Gozgor, Giray & Tiwari, Aviral & Khraief, Naceur & Shahbaz, Muhammad, 2019. "Dependence Structure between Business Cycles and CO2 Emissions in the U.S.: Evidence from the Time-Varying Markov-Switching Copula Models," MPRA Paper 95971, University Library of Munich, Germany, revised 09 Sep 2019.
        • Gozgor, Giray & Tiwari, Aviral Kumar & Khraief, Naceur & Shahbaz, Muhammad, 2019. "Dependence structure between business cycles and CO2 emissions in the U.S.: Evidence from the time-varying Markov-Switching Copula models," Energy, Elsevier, vol. 188(C).
    15. Jayech, Selma, 2016. "The contagion channels of July–August-2011 stock market crash: A DAG-copula based approach," European Journal of Operational Research, Elsevier, vol. 249(2), pages 631-646.
    16. Anna Czapkiewicz & Pawel Jamer & Joanna Landmesser, 2018. "Effects of Macroeconomic Indicators on the Financial Markets Interrelations," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(3), pages 268-293, July.
    17. Jiang, Cuixia & Ding, Xiaoyi & Xu, Qifa & Tong, Yongbo, 2020. "A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    18. Paula V. Tofoli & Flavio A. Ziegelmann & Osvaldo Candido, 2017. "A Comparison Study of Copula Models for Europea Financial Index Returns," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(10), pages 155-178, October.
    19. Fousekis, Panos, 2017. "Price co-movement and the hedger's value-at-risk in the futures markets for coffee," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 1), January.
    20. Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar & Alagidede, Imhotep Paul & Gil-Alana, Luis Alberiko, 2022. "Re-examination of risk-return dynamics in international equity markets and the role of policy uncertainty, geopolitical risk and VIX: Evidence using Markov-switching copulas," Finance Research Letters, Elsevier, vol. 47(PA).
    21. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    22. Tófoli Paula V. & Ziegelmann Flávio A. & Candido Osvaldo & Valls Pereira Pedro L., 2019. "Dynamic D-Vine Copula Model with Applications to Value-at-Risk (VaR)," Journal of Time Series Econometrics, De Gruyter, vol. 11(2), pages 1-34, July.
        • Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    23. Tiwari, Aviral Kumar & Adewuyi, Adeolu O. & Albulescu, Claudiu T. & Wohar, Mark E., 2020. "Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    24. Ji, Qiang & Liu, Bing-Yue & Cunado, Juncal & Gupta, Rangan, 2020. "Risk spillover between the US and the remaining G7 stock markets using time-varying copulas with Markov switching: Evidence from over a century of data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
        • Qiang Ji & Bing-Yue Liu & Juncal Cunado & Rangan Gupta, 2017. "Risk Spillover between the US and the Remaining G7 Stock Markets Using Time-Varying Copulas with Markov Switching: Evidence from Over a Century of Data," Working Papers 201759, University of Pretoria, Department of Economics.
    25. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    26. Woraphon Yamaka & Paravee Maneejuk, 2020. "Analyzing the Causality and Dependence between Gold Shocks and Asian Emerging Stock Markets: A Smooth Transition Copula Approach," Mathematics, MDPI, vol. 8(1), pages 1-27, January.
    27. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "Time-varying dependence dynamics between international commodity prices and Australian industry stock returns: a Perspective for portfolio diversification," Energy Economics, Elsevier, vol. 108(C).
    28. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    29. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
        • Tan Le & Franck Martin & Duc Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Working Papers hal-01806733, HAL.
    30. Govindan, Rajesh & Al-Ansari, Tareq, 2019. "Computational decision framework for enhancing resilience of the energy, water and food nexus in risky environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 653-668.
    31. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    32. Thijs Markwat, 2014. "The rise of global stock market crash probabilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 557-571, April.
    33. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.
    34. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    35. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.
    36. Chang, Kuang-Liang, 2020. "An investigation on mixed housing-cycle structures and asymmetric tail dependences," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    37. Kira Henshaw & Waleed Hana & Corina Constantinescu & Dalia Khalil, 2023. "Dependence Modelling of Lifetimes in Egyptian Families," Risks, MDPI, vol. 11(1), pages 1-25, January.
    38. Li, Xiafei & Wei, Yu, 2018. "The dependence and risk spillover between crude oil market and China stock market: New evidence from a variational mode decomposition-based copula method," Energy Economics, Elsevier, vol. 74(C), pages 565-581.
    39. Constantino, Michel & Candido, Osvaldo & Tabak, Benjamin M. & da Costa, Reginaldo Brito, 2017. "Modeling stochastic frontier based on vine copulas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 595-609.
    40. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.
    41. Sanjay Sehgal & Piyush Pandey & Florent Deisting, 2018. "Stock Market Integration Dynamics and its Determinants in the East Asian Economic Community Region," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 389-425, June.
    42. Chang, Kuang-Liang, 2017. "Does REIT index hedge inflation risk? New evidence from the tail quantile dependences of the Markov-switching GRG copula," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 56-67.

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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 3 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-FIN: Finance (1) 2005-12-01
2. NEP-ORE: Operations Research (1) 2021-03-22
3. NEP-RMG: Risk Management (1) 2016-07-09

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