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Roberto Baltieri Mauad

Personal Details

First Name:Roberto
Middle Name:Baltieri
Last Name:Mauad
Suffix:
RePEc Short-ID:pma2425
[This author has chosen not to make the email address public]

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. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2019. "Implied Volatility Term Structure and Exchange Rate Predictability," Working Papers Series 492, Central Bank of Brazil, Research Department.
  2. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2017. "Volatility risk premia and future commodities returns," BIS Working Papers 619, Bank for International Settlements.
  3. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2017. "Volatility Risk Premia and Future Commodity Returns," Working Papers Series 455, Central Bank of Brazil, Research Department.
  4. 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.

Articles

  1. Laurini, Márcio Poletti & Mauad, Roberto Baltieri & Aiube, Fernando Antônio Lucena, 2020. "The impact of co-jumps in the oil sector," Research in International Business and Finance, Elsevier, vol. 52(C).
  2. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Volatility risk premia and future commodity returns," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 341-360.
  3. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Implied volatility term structure and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1800-1813.
  4. Laurini, Márcio Poletti & Mauad, Roberto Baltieri, 2015. "A common jump factor stochastic volatility model," Finance Research Letters, Elsevier, vol. 12(C), pages 2-10.
  5. Márcio P. Laurini & Roberto B. Mauad, 2014. "The stochastic volatility model with random jumps and its application to BRL/USD exchange rate," Economics Bulletin, AccessEcon, vol. 34(2), pages 1002-1011.
  6. Laurini, Márcio Poletti & Mauad, Roberto Baltieri, 2012. "Non-Parametric Pricing of Interest Rates Options," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 32(2), April.

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. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2019. "Implied Volatility Term Structure and Exchange Rate Predictability," Working Papers Series 492, Central Bank of Brazil, Research Department.

    Cited by:

    1. Yu, Xing & Li, Yanyan & Gong, Xue & Zhang, Nan, 2022. "Evaluating the performance of futures hedging using factors-driven realized volatility," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Haas Ornelas, José Renato, 2019. "Expected currency returns and volatility risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 206-234.
    3. Matthew Greenwood-Nimmo & Daan Steenkamp & Rossouw van Jaarsveld, 2022. "CaninformationonthedistributionofZARreturnsbeusedtoimproveSARBsZARforecasts," Working Papers 11035, South African Reserve Bank.
    4. Sobhesh Kumar Agarwalla & Jayanth R. Varma & Vineet Virmani, 2021. "Rational repricing of risk during COVID‐19: Evidence from Indian single stock options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1498-1519, October.
    5. Adam Clements & Yin Liao & Yusui Tang, 2022. "Moving beyond Volatility Index (VIX): HARnessing the term structure of implied volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 86-99, January.
    6. Kwas, Marek & Beckmann, Joscha & Rubaszek, Michał, 2024. "Are consensus FX forecasts valuable for investors?," International Journal of Forecasting, Elsevier, vol. 40(1), pages 268-284.
    7. Zuzana Rowland & George Lazaroiu & Ivana Podhorská, 2020. "Use of Neural Networks to Accommodate Seasonal Fluctuations When Equalizing Time Series for the CZK/RMB Exchange Rate," Risks, MDPI, vol. 9(1), pages 1-21, December.

  2. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2017. "Volatility risk premia and future commodities returns," BIS Working Papers 619, Bank for International Settlements.

    Cited by:

    1. Kathi Schlepper & Heiko Hofer & Ryan Riordan & Andreas Schrimpf, 2017. "Scarcity effects of QE: A transaction-level analysis in the Bund market," BIS Working Papers 625, Bank for International Settlements.
    2. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2019. "Implied Volatility Term Structure and Exchange Rate Predictability," Working Papers Series 492, Central Bank of Brazil, Research Department.
    3. Haas Ornelas, José Renato, 2019. "Expected currency returns and volatility risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 206-234.
    4. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2021. "Cross-stock market spillovers through variance risk premiums and equity flows," Journal of International Money and Finance, Elsevier, vol. 119(C).
    5. Finta, Marinela Adriana & Ornelas, José Renato Haas, 2022. "Commodity return predictability: Evidence from implied variance, skewness, and their risk premia☆☆," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    6. Xu, Wei & Šević, Aleksandar & Šević, Željko, 2022. "Implied volatility surface construction for commodity futures options traded in China," Research in International Business and Finance, Elsevier, vol. 61(C).
    7. Prokopczuk, Marcel & Stancu, Andrei & Symeonidis, Lazaros, 2019. "The economic drivers of commodity market volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    8. Marinela Adriana Finta & José Renato Haas Ornelas, 2018. "Commodity Return Predictability: evidence from implied variance, skewness and their risk premia and their risk premia," Working Papers Series 479, Central Bank of Brazil, Research Department.

  3. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2017. "Volatility Risk Premia and Future Commodity Returns," Working Papers Series 455, Central Bank of Brazil, Research Department.

    Cited by:

    1. Kathi Schlepper & Heiko Hofer & Ryan Riordan & Andreas Schrimpf, 2017. "Scarcity effects of QE: A transaction-level analysis in the Bund market," BIS Working Papers 625, Bank for International Settlements.
    2. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2019. "Implied Volatility Term Structure and Exchange Rate Predictability," Working Papers Series 492, Central Bank of Brazil, Research Department.
    3. Haas Ornelas, José Renato, 2019. "Expected currency returns and volatility risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 206-234.
    4. Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
    5. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin, 2020. "Revising the impact of global commodity prices and global stock market volatility shocks: effects across countries," Working Papers 2020-10, University of Tasmania, Tasmanian School of Business and Economics.
    6. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin, 2020. "Global commodity prices and global stock market volatility shocks: Effects across countries," Journal of Asian Economics, Elsevier, vol. 71(C).
    7. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2021. "Cross-stock market spillovers through variance risk premiums and equity flows," Journal of International Money and Finance, Elsevier, vol. 119(C).
    8. Finta, Marinela Adriana & Ornelas, José Renato Haas, 2022. "Commodity return predictability: Evidence from implied variance, skewness, and their risk premia☆☆," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    9. Wang, Jiashun & Wang, Jiqian & Ma, Feng, 2024. "International commodity market and stock volatility predictability: Evidence from G7 countries," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 62-71.
    10. Xu, Wei & Šević, Aleksandar & Šević, Željko, 2022. "Implied volatility surface construction for commodity futures options traded in China," Research in International Business and Finance, Elsevier, vol. 61(C).
    11. Prokopczuk, Marcel & Stancu, Andrei & Symeonidis, Lazaros, 2019. "The economic drivers of commodity market volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    12. Marinela Adriana Finta & José Renato Haas Ornelas, 2018. "Commodity Return Predictability: evidence from implied variance, skewness and their risk premia and their risk premia," Working Papers Series 479, Central Bank of Brazil, Research Department.

  4. 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.

    Cited by:

    1. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    2. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    3. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.
    4. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.
    5. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.

Articles

  1. Laurini, Márcio Poletti & Mauad, Roberto Baltieri & Aiube, Fernando Antônio Lucena, 2020. "The impact of co-jumps in the oil sector," Research in International Business and Finance, Elsevier, vol. 52(C).

    Cited by:

    1. Oladosu, Gbadebo, 2022. "Bubbles in US gasoline prices: Assessing the role of hurricanes and anti–price gouging laws," Journal of Commodity Markets, Elsevier, vol. 27(C).
    2. Max Resende & Alexandre Ferreira, 2021. "A machine learning approach to risk disclosure reporting," Economics Bulletin, AccessEcon, vol. 41(2), pages 234-251.
    3. Cui, Jinxin & Alshater, Muneer M. & Mensi, Walid, 2023. "Higher-order moment risk spillovers and optimal portfolio strategies in global oil markets," Resources Policy, Elsevier, vol. 86(PA).
    4. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).

  2. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Volatility risk premia and future commodity returns," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 341-360.
    See citations under working paper version above.
  3. Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019. "Implied volatility term structure and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1800-1813.
    See citations under working paper version above.
  4. Laurini, Márcio Poletti & Mauad, Roberto Baltieri, 2015. "A common jump factor stochastic volatility model," Finance Research Letters, Elsevier, vol. 12(C), pages 2-10.

    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. Branger, Nicole & Muck, Matthias & Seifried, Frank Thomas & Weisheit, Stefan, 2017. "Optimal portfolios when variances and covariances can jump," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 59-89.
    3. Laurini, Márcio Poletti & Mauad, Roberto Baltieri & Aiube, Fernando Antônio Lucena, 2020. "The impact of co-jumps in the oil sector," Research in International Business and Finance, Elsevier, vol. 52(C).
    4. Everaert, Gerdie & Iseringhausen, Martin, 2018. "Measuring the international dimension of output volatility," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 20-39.
    5. Li, Chenxing & Maheu, John M, 2020. "A Multivariate GARCH-Jump Mixture Model," MPRA Paper 104770, University Library of Munich, Germany.
    6. Fernando Antonio Lucena Aiube & Ariel Levy, 2019. "Recent movement of oil prices and future scenarios [Movimentos recentes dos preços do petróleo e os cenários futuros]," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 29(1), pages 223-248, January-A.

  5. Márcio P. Laurini & Roberto B. Mauad, 2014. "The stochastic volatility model with random jumps and its application to BRL/USD exchange rate," Economics Bulletin, AccessEcon, vol. 34(2), pages 1002-1011.

    Cited by:

    1. Chang, Hao-Wen & Lin, Chinho, 2023. "Currency portfolio behavior in seven major Asian markets," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 540-559.
    2. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.

More information

Research fields, statistics, top rankings, if available.

Statistics

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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 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-RMG: Risk Management (3) 2017-04-16 2017-04-30 2019-03-18
  2. NEP-FMK: Financial Markets (2) 2017-04-16 2017-04-30
  3. NEP-UPT: Utility Models and Prospect Theory (2) 2017-04-16 2017-04-30
  4. NEP-IFN: International Finance (1) 2019-03-18

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