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Osvaldo Candido

Personal Details

First Name:Osvaldo
Middle Name:
Last Name:Candido
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RePEc Short-ID:pca1430

Affiliation

Economia
Universidade Católica de Brasilia

Brasilia, Brazil
http://www.ucb.br/Cursos/128MestradoEmEconomia/

+55(61)3448-7127
+55(61)3447-4797
SGAN 916, Av. W5 Norte, Asa Norte, CEP: 70.70190-160 - Brasília - DF
RePEc:edi:ecucbbr (more details at EDIRC)

Research output

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Jump to: Working papers Articles

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).
  2. Osvaldo Cândido da Silva Filho & Bruno Ferreira Frascaroli & Sinézio Fernandes Maia, 2005. "Transmissão De Preços No Mercado Internacional Da Soja: Uma Abordagem Pelos Modelos Armax E Var," Anais do XXXIII Encontro Nacional de Economia [Proceedings of the 33rd Brazilian Economics Meeting] 145, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

Articles

  1. 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.
  2. Washington Martins Silva & Osvaldo Candido, 2020. "Assessing Brazilian electric power transmission auctions: A copula-based sample selection model," Journal of Economic Studies, Emerald Group Publishing, vol. 47(1), pages 182-199, February.
  3. Wilfredo L. Maldonado & Osvaldo Candido & Luis Felipe V. N. Pereira, 2019. "Accuracy of policy function approximations for strongly concave recursive problems," International Journal of Economic Theory, The International Society for Economic Theory, vol. 15(3), pages 249-267, September.
  4. 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.
  5. Jose Antonio de Franca & Osvaldo Candido da Silva Filho & Wilfredo Sosa Sandoval, 2019. "Marginal Effect of Direct Tax on Profits: A Study on the Taxation of the Finance Industry in Brazil," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(3), pages 1-11, March.
  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.
  7. Pedro Paulo Carbone & Tito Belchior Silva Moreira & Osvaldo Candido, 2017. "Assessing the Human Capital Emergence, Performance and Effectiveness in a Brazilian Retail Bank," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(12), pages 134-152, December.
  8. Osvaldo Candido & Jose Angelo Divino, 2017. "Inflation, interest rate and output gap in the US economy: a vine copula modeling," Journal of Economic Studies, Emerald Group Publishing, vol. 44(3), pages 412-430, August.
  9. 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," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 5(4), pages 1-21, December.
  10. 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.
  11. Alberto Ronchi Neto & Osvaldo Candido, 2015. "Evaluating interest rate term-structure using extensions of the Diebold and Li three factors model," Brazilian Review of Finance, Brazilian Society of Finance, vol. 13(2), pages 251-287.
  12. 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, vol. 41(2), pages 253-271, March.
  13. 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.
  14. 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.
  15. Maldonado, Wilfredo L. & Marques, Isabel M. & Filho, Osvaldo C. da Silva, 2012. "A dynamic model of education level choice: Application to brazilian states," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 66(2), June.
  16. Bruno Ferreira Frascaroli & Luciano da Costa Silva & Osvaldo Cândido da Silva Filho, 2009. "Ratings of Sovereign Risk and the Macroeconomics Fundamentals of the countries: a Study Using Artificial Neural Networks," Brazilian Review of Finance, Brazilian Society of Finance, vol. 7(1), pages 73-106.

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

    Sorry, no citations of working papers recorded.

Articles

  1. 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. Enrique Martinez-Garcia, 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.
    2. Valerie Grossman & Enrique Martinez-Garcia & 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.

  2. 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. 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.

  3. 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," International Journal of Financial Studies, MDPI, Open Access Journal, 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," Journal of Risk and Financial Management, MDPI, Open Access Journal, 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.

  4. 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, vol. 41(2), pages 253-271, March.

    Cited by:

    1. 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.
    2. 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.

  5. 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. 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. 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.
    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. 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.
    5. 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.
    6. 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.
    7. Thijs Markwat, 2014. "The rise of global stock market crash probabilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 557-571, April.
    8. 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.
    9. 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, Open Access Journal, vol. 13(3), pages 1-13, January.
    10. 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.

  6. 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. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. 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.
    18. Tan Le & Franck Martin & Duc Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Working Papers hal-01806733, HAL.
    19. Thijs Markwat, 2014. "The rise of global stock market crash probabilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 557-571, April.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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).
    27. 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).
    28. 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.
    29. 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).

More information

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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 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-RMG: Risk Management (1) 2016-07-09

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