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Pablo Jose Campos de Carvalho

Personal Details

First Name:Pablo
Middle Name:Jose Campos
Last Name:de Carvalho
Suffix:
RePEc Short-ID:pde1112
[This author has chosen not to make the email address public]
Terminal Degree:2016 Lally School of Management and Technology; Rensselaer Polytechnic Institute (from RePEc Genealogy)

Affiliation

Banco Central do Brasil

Brasília, Brazil
http://www.bcb.gov.br/
RePEc:edi:bcbgvbr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Pablo Jose Campos de Carvalho & Aparna Gupta, 2018. "Multivariate Jump Diffusion Model with Markovian Contagion," Working Papers Series 482, Central Bank of Brazil, Research Department.
  2. José Renato Haas Ornelas & Pablo José Campos de Carvalho, 2015. "The Cost of Shorting, Asymmetric Performance Reaction and the Price Response to Economic Shocks," Working Papers Series 383, Central Bank of Brazil, Research Department.

Articles

  1. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.

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. Pablo Jose Campos de Carvalho & Aparna Gupta, 2018. "Multivariate Jump Diffusion Model with Markovian Contagion," Working Papers Series 482, Central Bank of Brazil, Research Department.

    Cited by:

    1. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.

Articles

  1. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.

    Cited by:

    1. Guorong Chen & Shiyi Fang & Qibo Chen & Yun Zhang, 2023. "Risk Spillovers and Network Connectedness between Clean Energy Stocks, Green Bonds, and Other Financial Assets: Evidence from China," Energies, MDPI, vol. 16(20), pages 1-21, October.
    2. Ma, Yan-Ran & Ji, Qiang & Wu, Fei & Pan, Jiaofeng, 2021. "Financialization, idiosyncratic information and commodity co-movements," Energy Economics, Elsevier, vol. 94(C).
    3. Shi, Huai-Long & Chen, Huayi, 2024. "Understanding co-movements based on heterogeneous information associations," International Review of Financial Analysis, Elsevier, vol. 94(C).
    4. Le, Chau & Dickinson, David & Le, Anh, 2022. "Sovereign risk spillovers: A network approach," Journal of Financial Stability, Elsevier, vol. 60(C).
    5. Shi, Huai-Long & Chen, Huayi, 2023. "Revisiting asset co-movement: Does network topology really matter?," Research in International Business and Finance, Elsevier, vol. 66(C).
    6. Chibane, Messaoud & Gabriel, Amadeus & Giménez Roche, Gabriel A., 2022. "Credit booms and crisis-emergent asset comovement: The problem of latent correlation," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 270-279.
    7. Xu Zhang & Xian Yang & Jianping Li & Jun Hao, 2023. "Contemporaneous and noncontemporaneous idiosyncratic risk spillovers in commodity futures markets: A novel network topology approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 705-733, June.
    8. Binqing Xiao & Honghai Yu & Libing Fang & Sifang Ding, 2020. "Estimating the connectedness of commodity futures using a network approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 598-616, April.
    9. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Zhu, You & Uddin, Gazi Salah, 2023. "Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
    10. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    11. Yuan, Ying & Wang, Haiying & Jin, Xiu, 2022. "Pandemic-driven financial contagion and investor behavior: Evidence from the COVID-19," International Review of Financial Analysis, Elsevier, vol. 83(C).
    12. Dayong Zhang & Qiang Ji & Wan-Li Zhao & Nicholas J Horsewood, 2021. "Regional housing price dependency in the UK: A dynamic network approach," Urban Studies, Urban Studies Journal Limited, vol. 58(5), pages 1014-1031, April.

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