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Márcio Laurini
(Marcio Laurini)

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. 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. 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.
    3. 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.
    4. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
    5. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.

  2. Marcio Laurini & Alberto Ohashi, 2014. "A Noisy Principal Component Analysis for Forward Rate Curves," Papers 1408.6279, arXiv.org.

    Cited by:

    1. Lapshin, Victor & Sohatskaya, Sofia, 2020. "Choosing the weighting coefficients for estimating the term structure from sovereign bonds," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 635-648.
    2. Lei Wang & Yan Yan & Xiaoteng Li & Xiaosong Chen, 2018. "General Component Analysis (GCA): A new approach to identify Chinese corporate bond market structures," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
    3. Charpentier, Arthur & Mussard, Stéphane & Ouraga, Téa, 2021. "Principal component analysis: A generalized Gini approach," European Journal of Operational Research, Elsevier, vol. 294(1), pages 236-249.
    4. Blomvall, Jörgen & Hagenbjörk, Johan, 2019. "A generic framework for monetary performance attribution," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 121-133.
    5. Blomvall, Jörgen, 2017. "Measurement of interest rates using a convex optimization model," European Journal of Operational Research, Elsevier, vol. 256(1), pages 308-316.
    6. Atkins, Philip J. & Cummins, Mark, 2023. "Improved scalability and risk factor proxying with a two-step principal component analysis for multi-curve modelling," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1331-1348.
    7. Cousin, Areski & Maatouk, Hassan & Rullière, Didier, 2016. "Kriging of financial term-structures," European Journal of Operational Research, Elsevier, vol. 255(2), pages 631-648.
    8. Emma Apps, 2020. "Application of the Absorption Ratio to Illustrate Financial Connectedness and Interlinkages," Working Papers 202022, University of Liverpool, Department of Economics.
    9. 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.
    10. Johan Hagenbjörk & Jörgen Blomvall, 2019. "Simulation and evaluation of the distribution of interest rate risk," Computational Management Science, Springer, vol. 16(1), pages 297-327, February.
    11. Caldana, Ruggero & Fusai, Gianluca & Roncoroni, Andrea, 2017. "Electricity forward curves with thin granularity: Theory and empirical evidence in the hourly EPEXspot market," European Journal of Operational Research, Elsevier, vol. 261(2), pages 715-734.

  3. Márcio Laurini, 2012. "A Hybrid Data Cloning Maximum Likelihood Estimator for Stochastic Volatility Models," IBMEC RJ Economics Discussion Papers 2012-02, Economics Research Group, IBMEC Business School - Rio de Janeiro.

    Cited by:

    1. Pedro Chaim & Márcio Poletti Laurini, 2022. "Data Cloning Estimation and Identification of a Medium-Scale DSGE Model," Stats, MDPI, vol. 6(1), pages 1-13, December.

  4. Márcio Laurini, 2012. "Dynamic Functional Data Analysis with Nonparametric State Space Models," IBMEC RJ Economics Discussion Papers 2012-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.

    Cited by:

    1. Daniel R. Kowal & David S. Matteson & David Ruppert, 2019. "Functional Autoregression for Sparsely Sampled Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 97-109, January.

  5. Márcio Laurini & Luiz Koodi Hotta, 2011. "Forecasting the Term Structure of Interest Rates Using Integrated Nested Laplace Approximations," IBMEC RJ Economics Discussion Papers 2011-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.

    Cited by:

    1. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    2. Márcio Poletti Laurini & Armênio Westin Neto, 2014. "Arbitrage in the Term Structure of Interest Rates: a Bayesian Approach," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 77-99, September.
    3. Márcio Poletti Laurini, 2017. "A continuous spatio-temporal model for house prices in the USA," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(1), pages 235-269, January.

  6. Laurini, Márcio Poletti & Westin, Armênio Dias Neto, 2010. "Arbitragem na Estrutura a Termo das Taxas de Juros: Uma Abordagem Bayesiana," Insper Working Papers wpe_201, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.

  7. Eduardo de Carvalho Andrade & Márcio Laurini, 2010. "New Evidence on the Role of Cognitive Skill in Economic Development," IBMEC RJ Economics Discussion Papers 2010-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.

    Cited by:

    1. Evans,David-000213993 & Popova,Anna, 2015. "What really works to improve learning in developing countries ? an analysis of divergent findings in systematic reviews," Policy Research Working Paper Series 7203, The World Bank.
    2. Masino, Serena & Niño-Zarazúa, Miguel, 2016. "What works to improve the quality of student learning in developing countries?," International Journal of Educational Development, Elsevier, vol. 48(C), pages 53-65.
    3. Umut Türk & John Östh & Marina Toger & Karima Kourtit, 2021. "Using Individualised HDI Measures for Predicting Educational Performance of Young Students—A Swedish Case Study," Sustainability, MDPI, vol. 13(11), pages 1-13, May.

  8. Márcio Laurini & Luiz Hotta, 2009. "Modelos de fatores latentes generalizados para curvas de juros em múltiplos mercados," Working Papers 09_03, Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto.

    Cited by:

    1. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.

  9. Furlani, Luiz G. C. & Portugal, Marcelo S. & Laurini, Márcio P., 2008. "Exchange Rate Movements and Monetary Policy In Brazil: Econometric and Simulation Evidence," Insper Working Papers wpe_124, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Luis Catão & Adrian Pagan, 2010. "The Credit Channel and Monetary Transmission in Brazil and Chile: A Structured VAR Approach," NCER Working Paper Series 53, National Centre for Econometric Research.
    2. Cortes, Gustavo S. & Paiva, Claudio A.C., 2017. "Deconstructing credibility: The breaking of monetary policy rules in Brazil," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 31-52.
    3. Gabriela Bezerra Medeiros & Marcelo Savino Portugal & Edilean Kleber da Silva Bejarano Aragón, 2017. "Endogeneity and nonlinearities in Central Bank of Brazil’s reaction functions: an inverse quantile regression approach," Empirical Economics, Springer, vol. 53(4), pages 1503-1527, December.
    4. Bui Trung Thanh & Gábor Kiss Dávid, 2021. "Measuring monetary policy by money supply and interest rate: evidence from emerging economies," Review of Economic Perspectives, Sciendo, vol. 21(3), pages 347-367, September.
    5. Mr. Marco Airaudo & Mr. Edward F Buffie & Luis-Felipe Zanna, 2016. "Inflation Targeting and Exchange Rate Management In Less Developed Countries," IMF Working Papers 2016/055, International Monetary Fund.
    6. Fernandes, Leonardo H.S. & Araújo, Fernando H.A. & Silva, Igor E.M. & Leite, Urbanno P.S. & de Lima, Neílson F. & Stosic, Tatijana & Ferreira, Tiago A.E., 2020. "Multifractal behavior in the dynamics of Brazilian inflation indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    7. Buffie, Edward F. & Airaudo, M. & Zanna, Felipe, 2018. "Inflation targeting and exchange rate management in less developed countries," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 159-184.
    8. Montes, Gabriel Caldas & Ferreira, Caio Ferrari, 2020. "Does monetary policy credibility mitigate the fear of floating?," Economic Modelling, Elsevier, vol. 84(C), pages 76-87.
    9. Ricardo Ramalhete MOREIRA, 2015. "Reviewing Taylor rules for Brazil: was there a turning-point?," Journal of Economics and Political Economy, KSP Journals, vol. 2(2), pages 276-289, June.
    10. Caldas Montes, Gabriel & Ferrari Ferreira, Caio, 2019. "Effect of monetary policy credibility on the fear of floating: Evidence from Brazil," Journal of Policy Modeling, Elsevier, vol. 41(5), pages 981-1004.
    11. Gabriela Bezerra De Medeiros & Marcelo Savino Portugal & Edilean Kleber Da Silva Bejarano Aragon, 2016. "Endogeneity And Nonlinearities In Central Bank Of Brazil’S Reaction Functions: An Inverse Quantile Regression Approach," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 061, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    12. Codruţa Mare & Cristian Litan, 2012. "Perspectives on Euro introduction in the Romanian economy," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 12(1), pages 23-40, July.
    13. Bui Thanh Trung, 2022. "Measuring Monetary Policy in Emerging Economy: The Role of Monetary Condition Index," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(6), pages 499-522, June.

  10. Laurini, Márcio P. & Hotta, Luiz K., 2008. "Bayesian extensions to diebold-li term structure model," Insper Working Papers wpe_122, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    2. Márcio Laurini, 2012. "Dynamic Functional Data Analysis with Nonparametric State Space Models," IBMEC RJ Economics Discussion Papers 2012-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    3. Vahidin Jeleskovic & Anastasios Demertzidis, 2018. "Comparing different methods for the estimation of interbank intraday yield curves," MAGKS Papers on Economics 201839, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    4. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    5. Dang-Nguyen, Stéphane & Le Caillec, Jean-Marc & Hillion, Alain, 2014. "The deterministic shift extension and the affine dynamic Nelson–Siegel model," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 402-417.
    6. Victor A. Lapshin & Vadim Ya. Kaushanskiy, 2014. "A Nonparametric Method For Term Structure Fitting With Automatic Smoothing," HSE Working papers WP BRP 39/FE/2014, National Research University Higher School of Economics.
    7. Márcio Poletti Laurini & Armênio Westin Neto, 2014. "Arbitrage in the Term Structure of Interest Rates: a Bayesian Approach," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 77-99, September.
    8. Tunaru, Diana, 2017. "Gaussian estimation and forecasting of the U.K. yield curve with multi-factor continuous-time models," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 119-129.
    9. Daniel R. Kowal & Antonio Canale, 2021. "Semiparametric Functional Factor Models with Bayesian Rank Selection," Papers 2108.02151, arXiv.org, revised May 2022.
    10. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    11. Aryo Sasongko & Cynthia Afriani Utama & Buddi Wibowo & Zaäfri Ananto Husodo, 2019. "Modifying Hybrid Optimisation Algorithms to Construct Spot Term Structure of Interest Rates and Proposing a Standardised Assessment," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 957-1003, October.
    12. Sourish Das, 2018. "Modeling Nelson-Siegel Yield Curve using Bayesian Approach," Papers 1809.06077, arXiv.org, revised Oct 2018.
    13. Tunaru, Radu & Zheng, Teng, 2017. "Parameter estimation risk in asset pricing and risk management: A Bayesian approach," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 80-93.

  11. Laurini, Márcio P. & Furlani, Luiz G. C. & Portugual, Marcelo S., 2008. "Empirical Market Microstructure: An Analysis Of The Brl/Us$ Exchange Rate Market Using High-Frequency Data," Insper Working Papers wpe_103, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series," Cambridge Working Papers in Economics 1452, Faculty of Economics, University of Cambridge.
    2. Zheng, Yingfei & Shen, Anran & Li, Ruihai & Yang, Yuhong & Wang, Shengjin & Cheng, Lee-Young, 2023. "Spillover effects between internet financial industry and traditional financial industry: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).

  12. Laurini, Márcio P., 2007. "A note on the use of quantile regression in beta convergence analysis," Insper Working Papers wpe_95, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Túlio Cravo & Guilherme Resende, 2013. "Economic growth in Brazil: a spatial filtering approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(2), pages 555-575, April.
    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. Marta Simões & João Sousa Andrade & Adelaide Duarte, 2012. "Convergence and Growth: Portugal in the EU 1986-2010," GEMF Working Papers 2012-13, GEMF, Faculty of Economics, University of Coimbra.
    4. Takahashi, Kazushi, 2013. "Pro-poor growth or poverty trap? : estimating intergenerational income mobility in rural Philippines," IDE Discussion Papers 382, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    5. Bernardi, Mauro & Bottone, Marco & Petrella, Lea, 2018. "Bayesian quantile regression using the skew exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 92-111.
    6. João Sousa Andrade & Adelaide Duarte & Marta Simões, 2014. "A Quantile Regression Analysis of Growth and Convergence in the EU: Potential Implications for Portugal," Notas Económicas, Faculty of Economics, University of Coimbra, issue 39, pages 48-72, June.

  13. Laurini, Márcio P. & Hotta, Luiz K., 2007. "Extensões Bayesianas do Modelo de Estrutura a Termo de Diebold-Li," Insper Working Papers wpe_88, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Almeida, Caio & Gomes, Romeu & Leite, André & Vicente, José, 2008. "Movimentos da Estrutura a Termo e Critérios de Minimização do Erro de Previsão em um Modelo Paramétrico Exponencial," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 62(4), December.

  14. Laurini, Márcio P. & Valls Pereira, Pedro L., 2007. "Conditional Stochastic Kernel Estimation by Nonparametric Methods," Insper Working Papers wpe_90, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Márcio Poletti Laurini, 2017. "A spatial error model with continuous random effects and an application to growth convergence," Journal of Geographical Systems, Springer, vol. 19(4), pages 371-398, October.
    2. Lin, Yi-Chen, 2016. "The global distribution of the burden of road traffic injuries: Evolution and intra-distribution mobility," Journal of Transport Geography, Elsevier, vol. 56(C), pages 77-91.
    3. Peiró-Palomino, Jesús & Picazo-Tadeo, Andrés J. & Tortosa-Ausina, Emili, 2021. "Measuring well-being in Colombian departments. The role of geography and demography," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    4. Serge Rey & Olivier Peron, 2012. "Trade and Convergence of Per Capita Income in the Indian Ocean Zone, 1950-2008," Post-Print hal-01885296, HAL.
    5. Jesús Peiró-Palomino, 2016. "European regional convergence revisited: the role of intangible assets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(1), pages 165-194, July.
    6. Halkos, George & Tzeremes, Nickolaos, 2011. "Regional environmental efficiency and economic growth: NUTS2 evidence from Germany, France and the UK," MPRA Paper 33698, University Library of Munich, Germany.
    7. Jesús Peiró-Palomino, 2019. "Regional well-being in the OECD," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(2), pages 195-218, June.
    8. Halkos, George & Tzeremes, Nickolaos, 2011. "Measuring regional environmental efficiency: A directional distance function approach," MPRA Paper 32934, University Library of Munich, Germany.
    9. George Halkos & Nickolaos Tzeremes, 2012. "Measuring German regions’ environmental efficiency: a directional distance function approach," Letters in Spatial and Resource Sciences, Springer, vol. 5(1), pages 7-16, March.
    10. José Villaverde & Adolfo Maza & María Hierro, 2014. "Health care expenditure disparities in the European Union and underlying factors: a distribution dynamics approach," International Journal of Health Economics and Management, Springer, vol. 14(3), pages 251-268, September.
    11. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo & Emili Tortosa-Ausina, 2020. "The Geography of Well-being in Colombia," Working Papers 2020/03, Economics Department, Universitat Jaume I, Castellón (Spain).
    12. Jesús Peiró-Palomino, 2013. "European regional convergence revisited: The role of space and the intangible assets," Working Papers 2013/11, Economics Department, Universitat Jaume I, Castellón (Spain).

  15. Laurini, Márcio P. & Moura, Marcelo, 2007. "Constrained Smoothing Splines for the Term Structure of Interest Rates," Insper Working Papers wpe_100, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Márcio Laurini, 2012. "Dynamic Functional Data Analysis with Nonparametric State Space Models," IBMEC RJ Economics Discussion Papers 2012-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    2. Victor Lapshin, 2019. "A Nonparametric Approach to Bond Portfolio Immunization," Mathematics, MDPI, vol. 7(11), pages 1-12, November.
    3. Luo, Sirong & Kong, Xiao & Nie, Tingting, 2016. "Spline based survival model for credit risk modeling," European Journal of Operational Research, Elsevier, vol. 253(3), pages 869-879.
    4. Cousin, Areski & Maatouk, Hassan & Rullière, Didier, 2016. "Kriging of financial term-structures," European Journal of Operational Research, Elsevier, vol. 255(2), pages 631-648.
    5. Varga, Gyorgy, 2009. "Teste de Modelos Estatísticos para a Estrutura a Termo no Brasil [Test of Term Structure Models for Brazil]," MPRA Paper 20832, University Library of Munich, Germany.
    6. Yallup, Peter J., 2012. "Models of the yield curve and the curvature of the implied forward rate function," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 121-135.
    7. Fengler, Matthias R. & Hin, Lin-Yee, 2015. "A simple and general approach to fitting the discount curve under no-arbitrage constraints," Finance Research Letters, Elsevier, vol. 15(C), pages 78-84.
    8. Damir Filipović & Sander Willems, 2016. "Exact Smooth Term Structure Estimation," Swiss Finance Institute Research Paper Series 16-38, Swiss Finance Institute.
    9. Márcio Poletti Laurini & Armênio Westin Neto, 2014. "Arbitrage in the Term Structure of Interest Rates: a Bayesian Approach," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 77-99, September.
    10. Eduardo Mineo & Airlane Pereira Alencar & Marcelo Moura & Antonio Elias Fabris, 2020. "Forecasting the Term Structure of Interest Rates with Dynamic Constrained Smoothing B-Splines," JRFM, MDPI, vol. 13(4), pages 1-14, April.
    11. Varga, Gyorgy, 2009. "Teste de Modelos Estatísticos para a Estrutura a Termo no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 63(4), December.

  16. Laurini, Márcio P., 2007. "Imposing No-Arbitrage Conditions In Implied Volatility Surfaces Using Constrained Smoothing Splines," Insper Working Papers wpe_89, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    2. Cristian Homescu, 2011. "Implied Volatility Surface: Construction Methodologies and Characteristics," Papers 1107.1834, arXiv.org.

  17. Márcio Laurini & Eduardo Andrade, 2004. "Income Convergence Clubs for Brazilian Municipalities: a Non-Parametric Analysis," Econometric Society 2004 Latin American Meetings 51, Econometric Society.

    Cited by:

    1. Márcio Poletti Laurini, 2017. "A spatial error model with continuous random effects and an application to growth convergence," Journal of Geographical Systems, Springer, vol. 19(4), pages 371-398, October.
    2. Guilherme Mendes Resende & Alexandre Xavier Ywata de Carvalho & Patrícia Alessandra Morita Sakowski, 2013. "Evaluating Multiple Spatial Dimensions of Economic Growth in Brazil Using Spatial Panel Data Models (1970 - 2000)," Discussion Papers 1830a, Instituto de Pesquisa Econômica Aplicada - IPEA.
    3. Túlio Cravo & Guilherme Resende, 2013. "Economic growth in Brazil: a spatial filtering approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(2), pages 555-575, April.
    4. Cravo, Túlio A., 2011. "Are small employers more cyclically sensitive? Evidence from Brazil," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 754-769.
    5. Túlio Cravo, 2011. "Regional Economic Growth and SMEs in Brazil: a Spatial Analysis (Submission for the Refereed Y-session Papers)," ERSA conference papers ersa10p508, European Regional Science Association.
    6. Guilherme Mendes Resende & Alexandre Xavier Ywata Carvalho & Patrícia Alessandra Morita Sakowski & Túlio Antonio Cravo, 2016. "Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 1-31, January.
    7. Aparna Lolayekar & Pranab Mukhopadhyay, 2017. "Growth Convergence and Regional Inequality in India (1981–2012)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(2), pages 307-328, June.
    8. Thomas Gries & Manfred Kraft & Christina Pieck, 2011. "Interregional migration, self-selection and the returns to education in Brazil," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(3), pages 707-732, June.
    9. Chhavi Tiwari & Sankalpa Bhattacharjee & Debkumar Chakrabarti, 2020. "Investigating Regional Inequalities in India: Are Indian Districts Converging?," Journal of International Development, John Wiley & Sons, Ltd., vol. 32(5), pages 684-716, July.
    10. Eduardo A. Haddad & Jesús P. Mena-Chalco, Otavio J. G. Sidone, 2015. "Scholarly Collaboration in Regional Science in Developing Countries: The Case of the Brazilian REAL Network," Working Papers, Department of Economics 2015_12, University of São Paulo (FEA-USP).
    11. Laurini, Márcio P., 2007. "A note on the use of quantile regression in beta convergence analysis," Insper Working Papers wpe_95, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    12. Guillermo E. Perry & Omar S. Arias & J. Humberto López & William F. Maloney & Luis Servén, 2006. "Poverty Reduction and Growth : Virtuous and Vicious Circles," World Bank Publications - Books, The World Bank Group, number 6997, December.
    13. Aparna P Lolayekar & Pranab Mukhopadhyay, 2020. "“Understanding growth convergence in India (1981–2010): Looking beyond the usual suspects”," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-17, June.
    14. Chenglin Qin & Xinyue Ye & Yingxia Liu, 2017. "Spatial Club Convergence of Regional Economic Growth in Inland China," Sustainability, MDPI, vol. 9(7), pages 1-14, July.
    15. Răileanu-Szeles, Monica & Albu, Lucian, 2015. "Nonlinearities and divergences in the process of European financial integration," Economic Modelling, Elsevier, vol. 46(C), pages 416-425.
    16. Michael Funke & Roberta Colavecchio & Declan Curran, 2011. "Drifting together of falling apart? The empirics of regional economic growth in post-unification Germany," Quantitative Macroeconomics Working Papers 21102, Hamburg University, Department of Economics.
    17. Túlio Cravo, 2011. "Are Small Firms more cyclically Sensitive than Large Ones? National, Regional and Sectoral Evidence from Brazil," ERSA conference papers ersa10p507, European Regional Science Association.
    18. Omid Ranjbar & Tsangyao Chang & Chien-Chiang Lee & Zahra Mila Elmi, 2018. "Catching-up process in the transition countries," Economic Change and Restructuring, Springer, vol. 51(3), pages 249-278, August.
    19. Túlio A. Cravo, 2010. "SMEs and economic growth in the Brazilian micro‐regions," Papers in Regional Science, Wiley Blackwell, vol. 89(4), pages 711-734, November.
    20. Eduardo A. Haddad & Jesús P. Mena-Chalco & Otávio J. G. Sidone, 2017. "Scholarly Collaboration in Regional Science in Developing Countries," International Regional Science Review, , vol. 40(5), pages 500-529, September.

  18. Laurini, M. P. & Portugal, M. S., 2003. "Markov Switching Based Nonlinear Tests for Market Efficiency Using the R$/US$ Exchange Rate," Finance Lab Working Papers flwp_51, Finance Lab, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Emekter, Riza & Jirasakuldech, Benjamas & Snaith, Sean M., 2009. "Nonlinear dynamics in foreign exchange excess returns: Tests of asymmetry," Journal of Multinational Financial Management, Elsevier, vol. 19(3), pages 179-192, July.
    2. Sergio Da Silva & Annibal Figueiredo & Iram Gleria & Raul Matsushita, 2007. "Hurst exponents, power laws, and efficiency in the Brazilian foreign exchange market," Economics Bulletin, AccessEcon, vol. 7(1), pages 1-11.

  19. Laurini, Márcio & Andrade, Eduardo & Pedro L. Valls Pereira, 2003. "Clubes de Convergência de Renda para os Municípios Brasileiros: Uma Análise Não-Paramétrica," Insper Working Papers wpe_41, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Maria Alice Móz Christofoletti & Humberto Francisco Silva Spolador, 2011. "Income convergence among Brazilian states after the economic openness in the 1990s," ERSA conference papers ersa10p172, European Regional Science Association.
    2. João Luis Brasil Gondim & Flávio Ataliba Barreto, 2004. "O Uso Do Núcleo Estocástico Para Identificação De Clubes De Convergência Entre Estados E Municípios Brasileiros," Anais do XXXII Encontro Nacional de Economia [Proceedings of the 32nd Brazilian Economics Meeting] 053, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    3. Penna, Christiano Modesto & Linhares, Fabricio Carneiro, 2013. "Há controvérsia entre análises de beta e sigma-convergência no Brasil?," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    4. Da Silva Catela, Eva Yamila & Porcile, Gabriel & Gonçalves, Flávio, 2010. "Brazilian municipalities: agglomeration economies and development levels in 1997 and 2007," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.

  20. Laurini, M. P. & Portugal, M. S., 2003. "Long Memory int the R$/US$ Exchange Rate: A Robust Analysis," Finance Lab Working Papers flwp_50, Finance Lab, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Sergio Da Silva & Annibal Figueiredo & Iram Gleria & Raul Matsushita, 2007. "Hurst exponents, power laws, and efficiency in the Brazilian foreign exchange market," Economics Bulletin, AccessEcon, vol. 7(1), pages 1-11.
    2. Chatziantoniou, Ioannis & Filis, George & Floros, Christos, 2015. "Asset prices regime-switching and the role of inflation targeting monetary policy," MPRA Paper 68666, University Library of Munich, Germany.
    3. Quinton Morris & Gary Van Vuuren & Paul Styger, 2009. "Further Evidence Of Long Memory In The South African Stock Market," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 81-101, March.

  21. Andrade, Eduardo. & Laurini, Márcio & Pedro L. Valls Pereira & Madalozzo, Regina., 2003. "Convergence Clubs Among Brazilian Municipalities," Insper Working Papers wpe_36, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Márcio Poletti Laurini, 2017. "A spatial error model with continuous random effects and an application to growth convergence," Journal of Geographical Systems, Springer, vol. 19(4), pages 371-398, October.
    2. Bird, Julia & Straub, Stephane, 2014. "The Brasilia experiment : road access and the spatial pattern of long-term local development in Brazil," Policy Research Working Paper Series 6964, The World Bank.
    3. Guilherme Mendes Resende & Alexandre Xavier Ywata de Carvalho & Patrícia Alessandra Morita Sakowski, 2013. "Evaluating Multiple Spatial Dimensions of Economic Growth in Brazil Using Spatial Panel Data Models (1970 - 2000)," Discussion Papers 1830a, Instituto de Pesquisa Econômica Aplicada - IPEA.
    4. Juessen Falko, 2005. "A distribution dynamics approach to regional GDP convergence in reunified Germany," Urban/Regional 0506008, University Library of Munich, Germany.
    5. Túlio Cravo & Guilherme Resende, 2013. "Economic growth in Brazil: a spatial filtering approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(2), pages 555-575, April.
    6. Kounetas, Konstantinos Elias, 2018. "Energy consumption and CO2 emissions convergence in European Union member countries. A tonneau des Danaides?," Energy Economics, Elsevier, vol. 69(C), pages 111-127.
    7. Guilherme Mendes Resende & Alexandre Xavier Ywata Carvalho & Patrícia Alessandra Morita Sakowski & Túlio Antonio Cravo, 2016. "Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 1-31, January.
    8. Falko Juessen, 2005. "A distribution dynamics approach to regional income convergence in reunified Germany," ERSA conference papers ersa05p411, European Regional Science Association.
    9. Bandyopadhyay, Sanghamitra, 2012. "Convergence clubs in incomes across Indian states: Is there evidence of a neighbours’ effect?," Economics Letters, Elsevier, vol. 116(3), pages 565-570.
    10. Sarah J. Carrington & Pablo Jiménez‐Ayora, 2021. "Shedding light on the convergence debate: Using luminosity data to investigate economic convergence in Ecuador," Review of Development Economics, Wiley Blackwell, vol. 25(1), pages 200-227, February.
    11. , Aisdl, 2021. "Factors Determining the Development of Minimum Comparable Areas and Spatial Interaction," OSF Preprints 9e7xz, Center for Open Science.
    12. Laurini, Márcio P., 2007. "A note on the use of quantile regression in beta convergence analysis," Insper Working Papers wpe_95, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    13. Christiano M. Penna & Fabricio Linhares, 2011. "Convergênciae Formação de Clubes no Brasil sob aHipótese de Heterogeneidade no DesenvolvimentoTecnológico," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 87, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    14. Manso, Carlos Alberto & Barreto, Flávio Ataliba & de França, João Mário, 2010. "Retornos da Educação e o Desequilíbrio Regional no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 64(2), June.
    15. Tulio Antonio Cravo & Elias Soukiazis, 2009. "Educational Thresholds and Economic Growth: Empirical Evidence from Brazilian States," Working Papers 2009.1, International Network for Economic Research - INFER.
    16. Philippe De Vreyer & Gilles Spielvogel, 2005. "Spatial externalities between Brazilian municipios and their neighbours," Working Papers DT/2005/11, DIAL (Développement, Institutions et Mondialisation).
    17. Keunkwan Ryu & Yong Yoon, 2020. "Convergence or confusion? A study of world economic growth," Economics Bulletin, AccessEcon, vol. 40(4), pages 2819-2827.
    18. Eckey, Hans-Friedrich & Kosfeld, Reinhold & Türck, Matthias, 2004. "Regionale Produktionsfunktionen mit Spillover-Effekten für Deutschland," Volkswirtschaftliche Diskussionsbeiträge 64, University of Kassel, Faculty of Economics and Management.
    19. Eduardo de Carvalho Andrade & Márcio Laurini, 2010. "New Evidence on the Role of Cognitive Skill in Economic Development," IBMEC RJ Economics Discussion Papers 2010-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    20. Sabyasachi Kar & Debajit Jha & Alpana Kateja, 2011. "Club‐convergence and polarization of states," Indian Growth and Development Review, Emerald Group Publishing Limited, vol. 4(1), pages 53-72, April.
    21. Mendez-Guerra, Carlos, 2017. "Heterogeneous Growth and Regional (Di)Convergence in Bolivia: A Distribution Dynamics Approach," MPRA Paper 81060, University Library of Munich, Germany.
    22. Philippe De Vreyer & Sandrine Mesplé-Somps & Gilles Spielvogel, 2005. "Spatial externalities between Brazilian municipios and their neighbours," ERSA conference papers ersa05p573, European Regional Science Association.
    23. Fotopoulos, Georgios, 2006. "Nonparametric analysis of regional income dynamics: The case of Greece," Economics Letters, Elsevier, vol. 91(3), pages 450-457, June.

  22. Andrade, Eduardo & Laurini, Márcio & Madalozzo, Regina & Pedro L. Valls Pereira, 2002. "Testing Convergence Across Municipalities in Brazil Using Quantile Regression," Insper Working Papers wpe_25, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Tamas Dusek, 2006. "Regional Income Differences in Hungary - A Multi-Level Spatio-Temporal Analysis," ERSA conference papers ersa06p284, European Regional Science Association.
    2. Laurini, Márcio P., 2007. "A note on the use of quantile regression in beta convergence analysis," Insper Working Papers wpe_95, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    3. Guilherme Mendes Resende & Lízia de Figueiredo, 2008. "Economic Growth Of Minas Gerais: A Quantile Regression Approach Between 1980 And 2000," Anais do XIII Semin·rio sobre a Economia Mineira [Proceedings of the 13th Seminar on the Economy of Minas Gerais], in: Anais do XIII Seminário sobre a Economia Mineira [Proceedings of the 13th Seminar on the Economy of Minas Gerais], Cedeplar, Universidade Federal de Minas Gerais.

Articles

  1. William Y. N. Suzuki & Marcio P. Laurini & Luciano Nakabashi, 2022. "Spatial heterogeneities, institutions, and income: Evidence for Brazil," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 537-571, June.

    Cited by:

    1. Luciano Nakabashi & Ana Elisa Pereira, 2023. "Factors of production, productivity, institutions, and development: Evidence from Brazil," Review of Development Economics, Wiley Blackwell, vol. 27(2), pages 1034-1055, May.
    2. Charpe, Matthieu, 2022. "Convergence Heterogeneity at the Local Level in Sub-Saharan Africa," MPRA Paper 114860, University Library of Munich, Germany.

  2. 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. 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. 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).
    3. Max Resende & Alexandre Ferreira, 2021. "A machine learning approach to risk disclosure reporting," Economics Bulletin, AccessEcon, vol. 41(2), pages 234-251.

  3. Chaim, Pedro & Laurini, Márcio P., 2019. "Is Bitcoin a bubble?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 222-232.

    Cited by:

    1. Hu, Yang & Hou, Yang (Greg) & Oxley, Les & Corbet, Shaen, 2021. "Does blockchain patent-development influence Bitcoin risk?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    2. Andr'es Garc'ia-Medina & Toan Luu Duc Huynh3, 2021. "What drives bitcoin? An approach from continuous local transfer entropy and deep learning classification models," Papers 2109.01214, arXiv.org.
    3. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    4. Muhammad Athar Nadeem & Zhiying Liu & Abdul Hameed Pitafi & Amna Younis & Yi Xu, 2021. "Investigating the Adoption Factors of Cryptocurrencies—A Case of Bitcoin: Empirical Evidence From China," SAGE Open, , vol. 11(1), pages 21582440219, March.
    5. Anastasiou, Dimitrios & Ballis, Antonis & Drakos, Konstantinos, 2021. "Cryptocurrencies’ Price Crash Risk and Crisis Sentiment," Finance Research Letters, Elsevier, vol. 42(C).
    6. Cretarola, Alessandra & Figà-Talamanca, Gianna, 2020. "Bubble regime identification in an attention-based model for Bitcoin and Ethereum price dynamics," Economics Letters, Elsevier, vol. 191(C).
    7. Kang, Sang Hoon & McIver, Ron P. & Hernandez, Jose Arreola, 2019. "Co-movements between Bitcoin and Gold: A wavelet coherence analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    8. C. R. da Cunha & R. da Silva, 2019. "Relevant Stylized Facts About Bitcoin: Fluctuations, First Return Probability, and Natural Phenomena," Papers 1905.03211, arXiv.org.
    9. Nedved, Martin & Kristoufek, Ladislav, 2023. "Safe havens for Bitcoin," Finance Research Letters, Elsevier, vol. 51(C).
    10. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    11. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    12. Samia Nasreen & Aviral Kumar Tiwari & Seong-Min Yoon, 2021. "Dynamic Connectedness and Portfolio Diversification during the Coronavirus Disease 2019 Pandemic: Evidence from the Cryptocurrency Market," Sustainability, MDPI, vol. 13(14), pages 1-14, July.
    13. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    14. Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
    15. Wolfgang Karl Härdle & Campbell R Harvey & Raphael C G Reule, 2020. "Understanding Cryptocurrencies," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 181-208.
    16. Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
    17. Andrew Phiri, 2022. "Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 373-386, September.
    18. Chu, Jeffrey & Chan, Stephen & Zhang, Yuanyuan, 2021. "Bitcoin versus high-performance technology stocks in diversifying against global stock market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    19. Michael Demmler & Amilcar Orlian Fernández Domínguez, 2021. "Bitcoin and the South Sea Company: A comparative analysis," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 13(1), pages 197-224, March.
    20. Davide Provenzano & Rodolfo Baggio, 2021. "Complexity traits and synchrony of cryptocurrencies price dynamics," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 941-955, December.
    21. Shuyu Zhang & Walter Aerts & Dunli Zhang & Zishan Chen, 2022. "Positive tone and initial coin offering," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(2), pages 2237-2266, June.
    22. Beatriz Vaz de Melo Mendes & André Fluminense Carneiro, 2020. "A Comprehensive Statistical Analysis of the Six Major Crypto-Currencies from August 2015 through June 2020," JRFM, MDPI, vol. 13(9), pages 1-21, August.
    23. Márcio P. Laurini & Pedro Chaim, 2021. "Brazilian stock market bubble in the 2010s," SN Business & Economics, Springer, vol. 1(1), pages 1-19, January.
    24. Dulani Jayasuriya Daluwathumullagamage & Alexandra Sims, 2021. "Fantastic Beasts: Blockchain Based Banking," JRFM, MDPI, vol. 14(4), pages 1-43, April.
    25. Kalyvas, Antonios & Papakyriakou, Panayiotis & Sakkas, Athanasios & Urquhart, Andrew, 2020. "What drives Bitcoin’s price crash risk?," Economics Letters, Elsevier, vol. 191(C).
    26. Dwita Mariana, Christy & Ekaputra, Irwan Adi & Husodo, Zaäfri Ananto, 2021. "Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 38(C).
    27. Ma, Yu & Luan, Zhiqian, 2022. "Ethereum synchronicity, upside volatility and Bitcoin crash risk," Finance Research Letters, Elsevier, vol. 46(PA).
    28. Moussa, Wajdi & Mgadmi, Nidhal & Béjaoui, Azza & Regaieg, Rym, 2021. "Exploring the dynamic relationship between Bitcoin and commodities: New insights through STECM model," Resources Policy, Elsevier, vol. 74(C).
    29. da Cunha, C.R. & da Silva, R., 2020. "Relevant stylized facts about bitcoin: Fluctuations, first return probability, and natural phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    30. Ozkan Haykir & Ibrahim Yagli, 2022. "Speculative bubbles and herding in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-33, December.
    31. Pedro L. P. Chaim & Márcio P. Laurini, 2019. "Foreign Exchange Expectation Errors and Filtration Enlargements," Stats, MDPI, vol. 2(2), pages 1-16, April.
    32. Adel Benhamed & Ahlem Selma Messai & Ghassen El Montasser, 2023. "On the Determinants of Bitcoin Returns and Volatility: What We Get from Gets?," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    33. Anupam Dutta & Elie Bouri, 2022. "Outliers and Time-Varying Jumps in the Cryptocurrency Markets," JRFM, MDPI, vol. 15(3), pages 1-7, March.
    34. Wolfgang Karl Hardle & Campbell R. Harvey & Raphael C. G. Reule, 2020. "Editorial: Understanding Cryptocurrencies," Papers 2007.14702, arXiv.org.
    35. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    36. Kinateder, Harald & Papavassiliou, Vassilios G., 2021. "Calendar effects in Bitcoin returns and volatility," Finance Research Letters, Elsevier, vol. 38(C).
    37. Aysan, Ahmet Faruk & Polat, Ali Yavuz & Tekin, Hasan & Tunali, Ahmet Semih, 2021. "Bitcoin-specific fear sentiment and bitcoin returns in the COVID-19 outbreak," MPRA Paper 110013, University Library of Munich, Germany.
    38. Pho, Kim Hung & Ly, Sel & Lu, Richard & Hoang, Thi Hong Van & Wong, Wing-Keung, 2021. "Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    39. Muhammad Abubakr Naeem & Mudassar Hasan & Muhammad Arif & Syed Jawad Hussain Shahzad, 2020. "Can Bitcoin Glitter More Than Gold for Investment Styles?," SAGE Open, , vol. 10(2), pages 21582440209, May.
    40. Paulo Ferreira & Éder Pereira, 2019. "Contagion Effect in Cryptocurrency Market," JRFM, MDPI, vol. 12(3), pages 1-8, July.
    41. Konstantin Gorgen & Jonas Meirer & Melanie Schienle, 2022. "Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests," Papers 2203.08224, arXiv.org, revised Jun 2022.
    42. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    43. Theodosios Perifanis, 2019. "Detecting West Texas Intermediate (WTI) Prices’ Bubble Periods," Energies, MDPI, vol. 12(14), pages 1-16, July.
    44. R. K. Jana & Indranil Ghosh & Debojyoti Das, 2021. "A differential evolution-based regression framework for forecasting Bitcoin price," Annals of Operations Research, Springer, vol. 306(1), pages 295-320, November.
    45. Alessandra Cretarola & Gianna Figà-Talamanca, 2021. "Detecting bubbles in Bitcoin price dynamics via market exuberance," Annals of Operations Research, Springer, vol. 299(1), pages 459-479, April.
    46. Qian Wang & Yu Wei & Yifeng Zhang & Yuntong Liu, 2023. "Evaluating the Safe-Haven Abilities of Bitcoin and Gold for Crude Oil Market: Evidence During the COVID-19 Pandemic," Evaluation Review, , vol. 47(3), pages 391-432, June.

  4. M. P. Laurini, 2019. "A spatio‐temporal approach to estimate patterns of climate change," Environmetrics, John Wiley & Sons, Ltd., vol. 30(1), February.

    Cited by:

    1. Fernanda Valente & Márcio Laurini, 2020. "Tornado Occurrences in the United States: A Spatio-Temporal Point Process Approach," Econometrics, MDPI, vol. 8(2), pages 1-26, June.

  5. 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.

    Cited by:

    1. OlaOluwa S. Yaya & Ahamuefula E. Ogbonna & Robert Mudida & Nuruddeen Abu, 2021. "Market efficiency and volatility persistence of cryptocurrency during pre‐ and post‐crash periods of Bitcoin: Evidence based on fractional integration," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1318-1335, January.
    2. Syed Jawad Hussain Shahzad & Elie Bouri & Sang Hoon Kang & Tareq Saeed, 2021. "Regime specific spillover across cryptocurrencies and the role of COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    3. Jens Klose, 2022. "Comparing cryptocurrencies and gold - a system-GARCH-approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 653-679, December.
    4. Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
    5. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Alessandra Cretarola & Gianna Figà-Talamanca & Cyril Grunspan, 2021. "Blockchain and cryptocurrencies: economic and financial research," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 781-787, December.
    7. Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    8. González, Maria de la O. & Jareño, Francisco & Skinner, Frank S., 2021. "Asymmetric interdependencies between large capital cryptocurrency and Gold returns during the COVID-19 pandemic crisis," International Review of Financial Analysis, Elsevier, vol. 76(C).
    9. Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
    10. Paola Stolfi & Mauro Bernardi & Davide Vergni, 2022. "Robust estimation of time-dependent precision matrix with application to the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    11. Qiao, Xingzhi & Zhu, Huiming & Hau, Liya, 2020. "Time-frequency co-movement of cryptocurrency return and volatility: Evidence from wavelet coherence analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    12. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    13. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
    14. 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.
    15. Lamia Kalai, 2022. "Time Varying Dependence in the Cryptocurrency Market and COVID 19 Panic Index: An Empirical Investigation," International Journal of Economics and Financial Issues, Econjournals, vol. 12(2), pages 37-51, March.
    16. Piyachart Phiromswad & Pattanaporn Chatjuthamard & Sirimon Treepongkaruna & Sabin Srivannaboon, 2021. "Jumps and Cojumps analyses of major and minor cryptocurrencies," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-9, February.
    17. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    18. Lahmiri, Salim & Bekiros, Stelios, 2020. "Big data analytics using multi-fractal wavelet leaders in high-frequency Bitcoin markets," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    19. Iqbal, Najaf & Fareed, Zeeshan & Wan, Guangcai & Shahzad, Farrukh, 2021. "Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 73(C).
    20. López-Martín, Carmen & Arguedas-Sanz, Raquel & Muela, Sonia Benito, 2022. "A cryptocurrency empirical study focused on evaluating their distribution functions," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 387-407.
    21. Mokni, Khaled, 2021. "When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 65-73.
    22. Pho, Kim Hung & Ly, Sel & Lu, Richard & Hoang, Thi Hong Van & Wong, Wing-Keung, 2021. "Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    23. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    24. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
    25. Fang, Sheng & Cao, Guangxi & Egan, Paul, 2023. "Forecasting and backtesting systemic risk in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 54(C).
    26. Jens Klose, 2021. "Cryptocurrencies and Gold - Similarities and Differences," MAGKS Papers on Economics 202128, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

  6. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.

    Cited by:

    1. OlaOluwa S. Yaya & Ahamuefula E. Ogbonna & Robert Mudida & Nuruddeen Abu, 2021. "Market efficiency and volatility persistence of cryptocurrency during pre‐ and post‐crash periods of Bitcoin: Evidence based on fractional integration," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1318-1335, January.
    2. Nguyen, Linh Hoang & Chevapatrakul, Thanaset & Yao, Kai, 2020. "Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 333-355.
    3. Elie Bouri & Rangan Gupta & Xuan Vinh Vo, 2022. "Jumps in Geopolitical Risk and the Cryptocurrency Market: The Singularity of Bitcoin," Defence and Peace Economics, Taylor & Francis Journals, vol. 33(2), pages 150-161, February.
    4. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    5. Akyildirim, Erdinç & Corbet, Shaen & Cumming, Douglas & Lucey, Brian & Sensoy, Ahmet, 2020. "Riding the Wave of Crypto-Exuberance: The Potential Misusage of Corporate Blockchain Announcements," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    6. Jens Klose, 2022. "Comparing cryptocurrencies and gold - a system-GARCH-approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 653-679, December.
    7. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben & Chevallier, Julien, 2020. "Asymmetric volatility in cryptocurrency markets: New evidence from smooth transition GARCH models," Finance Research Letters, Elsevier, vol. 35(C).
    8. Dehua Shen & Andrew Urquhart & Pengfei Wang, 2020. "Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks," European Financial Management, European Financial Management Association, vol. 26(5), pages 1294-1323, November.
    9. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2019. "Non-Linearities, Cyber Attacks and Cryptocurrencies," CESifo Working Paper Series 7692, CESifo.
    10. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    11. 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).
    12. Turattia, Douglas Eduardo & Mendes, Fernando Henrique P.S. & Caldeira, João Frois, 2020. "Testing for mean reversion in Bitcoin returns with Gibbs-sampling-augmented randomization," Finance Research Letters, Elsevier, vol. 34(C).
    13. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    14. 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.
    15. Hu, Yitong & Li, Xiao & Shen, Dehua, 2020. "Attention allocation and international stock return comovement: Evidence from the Bitcoin market," Research in International Business and Finance, Elsevier, vol. 54(C).
    16. Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
    17. Jihed Majdoub & Salim Ben Sassi & Azza Bejaoui, 2021. "Can fiat currencies really hedge Bitcoin? Evidence from dynamic short-term perspective," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 789-816, December.
    18. Tzouvanas, Panagiotis & Kizys, Renatas & Tsend-Ayush, Bayasgalan, 2020. "Momentum trading in cryptocurrencies: Short-term returns and diversification benefits," Economics Letters, Elsevier, vol. 191(C).
    19. Aktham Maghyereh & Hussein Abdoh, 2022. "COVID-19 and the volatility interlinkage between bitcoin and financial assets," Empirical Economics, Springer, vol. 63(6), pages 2875-2901, December.
    20. Cássio R. A. Alves & Márcio P. Laurini, 2022. "Measuring inflation persistence under time-varying inflation target and stochastic volatility with jumps," Economics Bulletin, AccessEcon, vol. 42(2), pages 342-349.
    21. Kaya, Orçun & Mostowfi, Mehdi, 2022. "Low-volatility strategies for highly liquid cryptocurrencies," Finance Research Letters, Elsevier, vol. 46(PB).
    22. Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
    23. Kurosaki, Tetsuo & Kim, Young Shin, 2022. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Finance Research Letters, Elsevier, vol. 45(C).
    24. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    25. Yin, Libo & Nie, Jing & Han, Liyan, 2021. "Understanding cryptocurrency volatility: The role of oil market shocks," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 233-253.
    26. Kong, Xiaolin & Ma, Chaoqun & Ren, Yi-Shuai & Narayan, Seema & Nguyen, Thong Trung & Baltas, Konstantinos, 2023. "Changes in the market structure and risk management of Bitcoin and its forked coins," Research in International Business and Finance, Elsevier, vol. 65(C).
    27. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    28. Mensi, Walid & Lee, Yun-Jung & Al-Yahyaee, Khamis Hamed & Sensoy, Ahmet & Yoon, Seong-Min, 2019. "Intraday downward/upward multifractality and long memory in Bitcoin and Ethereum markets: An asymmetric multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 31(C), pages 19-25.
    29. Feng Ma & Chao Liang & Yuanhui Ma & M.I.M. Wahab, 2020. "Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1277-1290, December.
    30. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
    31. Yuzhi Cai & Thanaset Chevapatrakul & Danilo V. Mascia, 2021. "How is price explosivity triggered in the cryptocurrency markets?," Annals of Operations Research, Springer, vol. 307(1), pages 37-51, December.
    32. Sarkodie, Samuel Asumadu & Ahmed, Maruf Yakubu & Leirvik, Thomas, 2022. "Trade volume affects bitcoin energy consumption and carbon footprint," Finance Research Letters, Elsevier, vol. 48(C).
    33. Piyachart Phiromswad & Pattanaporn Chatjuthamard & Sirimon Treepongkaruna & Sabin Srivannaboon, 2021. "Jumps and Cojumps analyses of major and minor cryptocurrencies," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-9, February.
    34. Zhang, Chuanhai & Chen, Haicui & Peng, Zhe, 2022. "Does Bitcoin futures trading reduce the normal and jump volatility in the spot market? Evidence from GARCH-jump models," Finance Research Letters, Elsevier, vol. 47(PB).
    35. Xu, Fang & Bouri, Elie & Cepni, Oguzhan, 2022. "Blockchain and crypto-exposed US companies and major cryptocurrencies: The role of jumps and co-jumps," Finance Research Letters, Elsevier, vol. 50(C).
    36. 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.
    37. Khanh Hoang & Cuong C. Nguyen & Kongchheng Poch & Thang X. Nguyen, 2020. "Does Bitcoin Hedge Commodity Uncertainty?," JRFM, MDPI, vol. 13(6), pages 1-14, June.
    38. Fajardo, José, 2019. "Bitcoin's return behaviour: What do We know so far?," MPRA Paper 93353, University Library of Munich, Germany, revised 16 Apr 2019.
    39. Lahmiri, Salim & Bekiros, Stelios, 2020. "Big data analytics using multi-fractal wavelet leaders in high-frequency Bitcoin markets," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    40. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    41. Tetsuo Kurosaki & Young Shin Kim, 2020. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Papers 2010.08900, arXiv.org.
    42. Gunay, Samet & Kaskaloglu, Kerem, 2022. "Does utilizing smart contracts induce a financial connectedness between Ethereum and non-fungible tokens?," Research in International Business and Finance, Elsevier, vol. 63(C).
    43. Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2020. "Do Bitcoin and other cryptocurrencies jump together?," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 396-409.
    44. Nidhal Mgadmi & Azza Béjaoui & Wajdi Moussa, 2023. "Disentangling the Nonlinearity Effect in Cryptocurrency Markets During the Covid-19 Pandemic: Evidence from a Regime-Switching Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(3), pages 457-473, September.
    45. Zhang, Chuanhai & Ma, Huan & Liao, Xiaosai, 2023. "Futures trading activity and the jump risk of spot market: Evidence from the bitcoin market," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    46. Chaim, Pedro & Laurini, Márcio P., 2019. "Is Bitcoin a bubble?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 222-232.
    47. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    48. Platanakis, Emmanouil & Urquhart, Andrew, 2019. "Portfolio management with cryptocurrencies: The role of estimation risk," Economics Letters, Elsevier, vol. 177(C), pages 76-80.
    49. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    50. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Post-Print hal-03794543, HAL.
    51. Anupam Dutta & Elie Bouri, 2022. "Outliers and Time-Varying Jumps in the Cryptocurrency Markets," JRFM, MDPI, vol. 15(3), pages 1-7, March.
    52. Aslanidis, Nektarios & Bariviera, Aurelio F. & López, Óscar G., 2022. "The link between cryptocurrencies and Google Trends attention," Finance Research Letters, Elsevier, vol. 47(PA).
    53. Zhiyong Cheng & Jun Deng & Tianyi Wang & Mei Yu, 2021. "Liquidation, leverage and optimal margin in bitcoin futures markets," Applied Economics, Taylor & Francis Journals, vol. 53(47), pages 5415-5428, October.
    54. Benjamin M. Blau & Ryan J. Whitby, 2019. "The Introduction of Bitcoin Futures: An Examination of Volatility and Potential Spillover Effects," Economics Bulletin, AccessEcon, vol. 39(2), pages 1030-1038.
    55. López-Martín, Carmen & Arguedas-Sanz, Raquel & Muela, Sonia Benito, 2022. "A cryptocurrency empirical study focused on evaluating their distribution functions," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 387-407.
    56. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    57. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models," Papers 2011.03741, arXiv.org, revised Dec 2020.
    58. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    59. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis & Corbet, Shaen, 2021. "Herding behaviour and price convergence clubs in cryptocurrencies during bull and bear markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    60. Syed Riaz Mahmood Ali, 2022. "Herding in different states and terms: evidence from the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 322-336, July.
    61. Sadaqat, Mohsin & Butt, Hilal Anwar, 2023. "Stop-loss rules and momentum payoffs in cryptocurrencies," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    62. Melanie Cao & Batur Celik, 2021. "Valuation of bitcoin options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1007-1026, July.
    63. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach," Future Internet, MDPI, vol. 12(3), pages 1-19, March.
    64. Tiago E. Pratas & Filipe R. Ramos & Lihki Rubio, 2023. "Forecasting bitcoin volatility: exploring the potential of deep learning," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 285-305, June.
    65. Apergis, Nicholas & Koutmos, Dimitrios & Payne, James E., 2021. "Convergence in cryptocurrency prices? the role of market microstructure," Finance Research Letters, Elsevier, vol. 40(C).
    66. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
    67. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    68. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
    69. Kumar Kulbhaskar, Anamika & Subramaniam, Sowmya, 2023. "Breaking news headlines: Impact on trading activity in the cryptocurrency market," Economic Modelling, Elsevier, vol. 126(C).
    70. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    71. Akyildirim, Erdinc & Corbet, Shaen & Sensoy, Ahmet & Yarovaya, Larisa, 2020. "The impact of blockchain related name changes on corporate performance," Journal of Corporate Finance, Elsevier, vol. 65(C).
    72. Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    73. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    74. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    75. Suardi, Sandy & Rasel, Atiqur Rahman & Liu, Bin, 2022. "On the predictive power of tweet sentiments and attention on bitcoin," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 289-301.
    76. Jens Klose, 2021. "Cryptocurrencies and Gold - Similarities and Differences," MAGKS Papers on Economics 202128, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

  7. Márcio Poletti Laurini, 2017. "A spatial error model with continuous random effects and an application to growth convergence," Journal of Geographical Systems, Springer, vol. 19(4), pages 371-398, October.

    Cited by:

    1. Tamás Krisztin & Philipp Piribauer, 2021. "A Bayesian Spatial Autoregressive Logit Model With An Empirical Application to European Regional FDI Flows," WIFO Working Papers 586, WIFO.
    2. Piribauer, Philipp & Glocker, Christian & Krisztin, Tamás, 2023. "Beyond distance: The spatial relationships of European regional economic growth," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    3. Michael Pfarrhofer & Philipp Piribauer, 2018. "Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models," Papers 1805.10822, arXiv.org.

  8. Laurini, Márcio Poletti, 2017. "The spatio-temporal dynamics of ethanol/gasoline price ratio in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1-12.

    Cited by:

    1. Antonina Kalinichenko & Valerii Havrysh & Igor Atamanyuk, 2019. "The Acceptable Alternative Vehicle Fuel Price," Energies, MDPI, vol. 12(20), pages 1-20, October.
    2. Yusri, I.M. & Mamat, R. & Najafi, G. & Razman, A. & Awad, Omar I. & Azmi, W.H. & Ishak, W.F.W. & Shaiful, A.I.M., 2017. "Alcohol based automotive fuels from first four alcohol family in compression and spark ignition engine: A review on engine performance and exhaust emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 169-181.
    3. Derick David Quintino & Heloisa Lee Burnquist & Paulo Ferreira, 2022. "Relative Prices of Ethanol-Gasoline in the Major Brazilian Capitals: An Analysis to Support Public Policies," Energies, MDPI, vol. 15(13), pages 1-23, June.
    4. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    5. Biswal, Abinash & Kale, Rakesh & Balusamy, Saravanan & Banerjee, Raja & Kolhe, Pankaj, 2019. "Lemon peel oil as an alternative fuel for GDI engines: A spray characterization perspective," Renewable Energy, Elsevier, vol. 142(C), pages 249-263.

  9. Márcio Poletti Laurini, 2017. "A continuous spatio-temporal model for house prices in the USA," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(1), pages 235-269, January.

    Cited by:

    1. S. R. Johnson & S. E. Heaps & K. J. Wilson & D. J. Wilkinson, 2023. "A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.

  10. Lucas Argentieri Mariani & Márcio Poletti Laurini, 2017. "Implicit Inflation and Risk Premiums in the Brazilian Fixed Income Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(8), pages 1836-1853, August.

    Cited by:

    1. Samargandi, Nahla & Kutan, Ali M. & Sohag, Kazi & Alqahtani, Faisal, 2020. "Equity market and money supply spillovers and economic growth in BRICS economies: A global vector autoregressive approach," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    2. Helder Ferreira de Mendonça & Pedro Mendes Garcia & José Valentim Machado Vicente, 2021. "Rationality and anchoring of inflation expectations: An assessment from survey‐based and market‐based measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1027-1053, September.

  11. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.

    Cited by:

    1. Stona, Filipe & Caldeira, João F., 2019. "Do U.S. factors impact the Brazilian yield curve? Evidence from a dynamic factor model," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 76-89.
    2. Polat, Onur & Ozkan, Ibrahim, 2019. "Transmission mechanisms of financial stress into economic activity in Turkey," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 395-415.

  12. Erik Figueiredo & Márcio P. Laurini, 2016. "Poverty Elasticity: A Note on a New Empirical Approach," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(2), pages 394-401, June.

    Cited by:

    1. Edgar J. Wilson & Kankesu Jayanthakumaran & Reetu Verma, 2022. "Urban poverty, growth, and inequality: A needed paradigm shift?," Review of Development Economics, Wiley Blackwell, vol. 26(2), pages 941-961, May.
    2. Harmáček, Jaromír & Syrovátka, Miroslav & Dušková, Lenka, 2017. "Pro-poor growth in East Africa," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 82-93.

  13. Laurini, Márcio Poletti & Ohashi, Alberto, 2015. "A noisy principal component analysis for forward rate curves," European Journal of Operational Research, Elsevier, vol. 246(1), pages 140-153.
    See citations under working paper version above.
  14. 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. Gerdie Everaert & Martin Iseringhausen, 2017. "Measuring The International Dimension Of Output Volatility," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 17/928, Ghent University, Faculty of Economics and Business Administration.
    2. Li, Chenxing & Maheu, John M, 2020. "A Multivariate GARCH-Jump Mixture Model," MPRA Paper 104770, University Library of Munich, Germany.
    3. 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.
    4. 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.
    5. 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.
    6. 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).

  15. MÁrcio Poletti Laurini & Luiz Koodi Hotta, 2014. "Forecasting the Term Structure of Interest Rates Using Integrated Nested Laplace Approximations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(3), pages 214-230, April.
    See citations under working paper version above.
  16. M�rcio Poletti Laurini, 2014. "Dynamic functional data analysis with non-parametric state space models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(1), pages 142-163, January.
    See citations under working paper version above.
  17. 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. 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.
    2. 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.

  18. Laurini Márcio Poletti, 2013. "A Hybrid Data Cloning Maximum Likelihood Estimator for Stochastic Volatility Models," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 193-229, May.
    See citations under working paper version above.
  19. Márcio Laurini, 2013. "A Dynamic Econometric Model for Inflationary Inertia In Brazil," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 2(2), pages 1-6.

    Cited by:

    1. Cássio R. A. Alves & Márcio P. Laurini, 2022. "Measuring inflation persistence under time-varying inflation target and stochastic volatility with jumps," Economics Bulletin, AccessEcon, vol. 42(2), pages 342-349.
    2. Ji, Qiang & Fan, Ying, 2016. "Modelling the joint dynamics of oil prices and investor fear gauge," Research in International Business and Finance, Elsevier, vol. 37(C), pages 242-251.

  20. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2013. "Indirect Inference in fractional short-term interest rate diffusions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 109-126.

    Cited by:

    1. Xu, Dinghua & He, Yangao & Yu, Yue & Zhang, Qifeng, 2018. "Multiple parameter determination in textile material design:A Bayesian inference approach based on simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 151(C), pages 1-14.
    2. Richard A. Davis & Thiago do Rêgo Sousa & Claudia Klüppelberg, 2021. "Indirect inference for time series using the empirical characteristic function and control variates," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 653-684, September.

  21. Laurini, Márcio Poletti & de Carvalho Andrade, Eduardo, 2012. "New evidence on the role of cognitive skill in economic development," Economics Letters, Elsevier, vol. 117(1), pages 123-126.
    See citations under working paper version above.
  22. Márcio Poletti Laurini, 2011. "Imposing no‐arbitrage conditions in implied volatilities using constrained smoothing splines," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(6), pages 649-659, November.

    Cited by:

    1. Beer, Simone & Braun, Alexander, 2022. "Market-consistent valuation of natural catastrophe risk," Journal of Banking & Finance, Elsevier, vol. 134(C).
    2. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    3. Fengler, Matthias R. & Hin, Lin-Yee, 2015. "Semi-nonparametric estimation of the call-option price surface under strike and time-to-expiry no-arbitrage constraints," Journal of Econometrics, Elsevier, vol. 184(2), pages 242-261.
    4. Bender Christian & Thiel Matthias, 2020. "Arbitrage-free interpolation of call option prices," Statistics & Risk Modeling, De Gruyter, vol. 37(1-2), pages 55-78, January.

  23. Furlani, Luiz Gustavo Cassilatti & Portugal, Marcelo Savino & Laurini, Márcio Poletti, 2010. "Exchange rate movements and monetary policy in Brazil: Econometric and simulation evidence," Economic Modelling, Elsevier, vol. 27(1), pages 284-295, January.
    See citations under working paper version above.
  24. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.

    Cited by:

    1. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
    2. Márcio Laurini & João Frois Caldeira, 2012. "Some Comments on a Macro-Finance Model with Stochastic Volatility," IBMEC RJ Economics Discussion Papers 2012-04, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    3. Aryo Sasongko & Cynthia Afriani Utama & Buddi Wibowo & Zaäfri Ananto Husodo, 2019. "Modifying Hybrid Optimisation Algorithms to Construct Spot Term Structure of Interest Rates and Proposing a Standardised Assessment," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 957-1003, October.

  25. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2010. "Bayesian extensions to Diebold-Li term structure model," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 342-350, December.
    See citations under working paper version above.
  26. Chihmao Hsieh & Sérgio Giovanetti Lazzarini & Jackson A. Nickerson & Marcio Laurini, 2010. "Does Ownership Affect the Variability of the Production Process? Evidence from International Courier Services," Organization Science, INFORMS, vol. 21(4), pages 892-912, August.

    Cited by:

    1. Heather Berry & Aseem Kaul, 2015. "Global Sourcing and Foreign Knowledge Seeking," Management Science, INFORMS, vol. 61(5), pages 1052-1071, May.
    2. Lamar Pierce & Michael W. Toffel, 2013. "The Role of Organizational Scope and Governance in Strengthening Private Monitoring," Organization Science, INFORMS, vol. 24(5), pages 1558-1584, October.
    3. Anna-Liesa Lange & Philipp Otto, 2016. "Bayes’sche Statistik in der Dienstleistungsforschung [Bayesian statistics in service research]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(4), pages 247-267, December.
    4. Farhad Sadeh & Manish Kacker, 2018. "Quality signaling through ex-ante voluntary information disclosure in entrepreneurial networks: evidence from franchising," Small Business Economics, Springer, vol. 50(4), pages 729-748, April.
    5. Lamar Pierce & Michael W. Toffel, 2010. "The Role of Organizational Scope and Governance in Strengthening Private Monitoring," Harvard Business School Working Papers 11-004, Harvard Business School, revised Feb 2012.
    6. Yue Chen & Sai-Ho Chung & Shu Guo, 2020. "Franchising contracts in fashion supply chain operations: models, practices, and real case study," Annals of Operations Research, Springer, vol. 291(1), pages 83-128, August.

  27. Poletti Laurini, Márcio & Moura, Marcelo, 2010. "Constrained smoothing B-splines for the term structure of interest rates," Insurance: Mathematics and Economics, Elsevier, vol. 46(2), pages 339-350, April.
    See citations under working paper version above.
  28. Poletti Laurini, Márcio & Valls Pereira, Pedro L., 2009. "Conditional stochastic kernel estimation by nonparametric methods," Economics Letters, Elsevier, vol. 105(3), pages 234-238, December.
    See citations under working paper version above.
  29. Laurini, Márcio Poletti & Furlani, Luiz Gustavo Cassilatti & Portugal, Marcelo Savino, 2008. "Empirical market microstructure: An analysis of the BRL/US$ exchange rate market," Emerging Markets Review, Elsevier, vol. 9(4), pages 247-265, December.

    Cited by:

    1. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series," Cambridge Working Papers in Economics 1452, Faculty of Economics, University of Cambridge.
    2. Zheng, Yingfei & Shen, Anran & Li, Ruihai & Yang, Yuhong & Wang, Shengjin & Cheng, Lee-Young, 2023. "Spillover effects between internet financial industry and traditional financial industry: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).

  30. Marcio Laurini, 2007. "A note on the use of quantile regression in beta convergence analysis," Economics Bulletin, AccessEcon, vol. 3(52), pages 1-8.
    See citations under working paper version above.
  31. Marcio Laurini & Eduardo Andrade & Pedro L. Valls Pereira, 2005. "Income convergence clubs for Brazilian Municipalities: a non-parametric analysis," Applied Economics, Taylor & Francis Journals, vol. 37(18), pages 2099-2118.
    See citations under working paper version above.
  32. Laurini, Márcio Poletti & Portugal, Marcelo Savino, 2004. "Long memory in the R$ / US$ exchange rate: A robust analysis," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 24(1), May.
    See citations under working paper version above.
  33. Andrade, Eduardo & Laurini, Marcio & Madalozzo, Regina & Valls Pereira, Pedro L., 2004. "Convergence clubs among Brazilian municipalities," Economics Letters, Elsevier, vol. 83(2), pages 179-184, May.
    See citations under working paper version above.
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