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Rodrigo Herrera

Personal Details

First Name:Rodrigo
Middle Name:
Last Name:Herrera
Suffix:
RePEc Short-ID:phe650
http://www.r-herrera.com

Affiliation

Facultad de Economía y Negocios
Universidad de Talca

Talca, Chile
http://fen.utalca.cl/
RePEc:edi:fetalcl (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Gaete, Michael & Herrera, Rodrigo, 2022. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," MPRA Paper 115641, University Library of Munich, Germany.
  2. Marco Piña & Rodrigo Herrera, 2021. "Risk modeling with option-implied correlations and score-driven dynamics," Working Papers Central Bank of Chile 932, Central Bank of Chile.
  3. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.
  4. R Herrera & Adam Clements, 2015. "Point process models for extreme returns: Harnessing implied volatility," NCER Working Paper Series 104, National Centre for Econometric Research.
  5. Hautsch, Nikolaus & Herrera, Rodrigo, 2015. "Multivariate dynamic intensity peaks-over-threshold models," CFS Working Paper Series 516, Center for Financial Studies (CFS).
  6. Rodrigo Herrera & Bernhard Schipp, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers SFB649DP2011-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

Articles

  1. Alejandro Rodriguez & Gabriel Pino & Rodrigo Herrera, 2021. "A non-parametric statistic for testing conditional heteroscedasticity for unobserved component models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(3), pages 471-497, February.
  2. Fernanda Fuentes & Rodrigo Herrera, 2020. "Dynamics of Connectedness in Clean Energy Stocks," Energies, MDPI, vol. 13(14), pages 1-19, July.
  3. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
  4. Nikolaus Hautsch & Rodrigo Herrera, 2020. "Multivariate dynamic intensity peaks‐over‐threshold models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 248-272, March.
  5. Pino, Gabriel & Herrera, Rodrigo & Rodríguez, Alejandro, 2019. "Geographical spillovers on the relation between risk-taking and market power in the US banking sector," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 351-364.
  6. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2018. "Modeling extreme risks in commodities and commodity currencies," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 108-120.
  7. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.
  8. Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
  9. Moisan, Stella & Herrera, Rodrigo & Clements, Adam, 2018. "A dynamic multiple equation approach for forecasting PM2.5 pollution in Santiago, Chile," International Journal of Forecasting, Elsevier, vol. 34(4), pages 566-581.
  10. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
  11. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
  12. Herrera, Rodrigo & Schipp, Bernhard, 2014. "Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 218-238.
  13. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.
  14. Alexander Karmann & Rodrigo Herrera, 2014. "Volatility Contagion in the Asian Crisis: New Evidence of Volatility Tail Dependence," Review of Development Economics, Wiley Blackwell, vol. 18(2), pages 354-371, May.
  15. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.
  16. Herrera, Rodrigo, 2013. "Energy risk management through self-exciting marked point process," Energy Economics, Elsevier, vol. 38(C), pages 64-76.
  17. Herrera, R. & Eichler, S., 2011. "Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2916-2930, November.

Chapters

  1. Rodrigo Herrera & Jörg Kalcsics & Stefan Nickel, 2008. "Reliability Models for the Uncapacitated Facility Location Problem with User Preferences," Operations Research Proceedings, in: Jörg Kalcsics & Stefan Nickel (ed.), Operations Research Proceedings 2007, pages 135-140, Springer.

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. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.

    Cited by:

    1. Go, You-How & Lau, Wee-Yeap, 2021. "Extreme risk spillovers between crude palm oil prices and exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

  2. R Herrera & Adam Clements, 2015. "Point process models for extreme returns: Harnessing implied volatility," NCER Working Paper Series 104, National Centre for Econometric Research.

    Cited by:

    1. Lu Wang & Feng Ma & Guoshan Liu, 2020. "Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 797-810, August.
    2. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org.
    3. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    4. Xi, Yue & Zeng, Qing & Lu, Xinjie & Huynh, Toan L.D., 2022. "Oil and renewable energy stock markets: Unique role of extreme shocks," Energy Economics, Elsevier, vol. 109(C).
    5. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    6. Nishio, Kazuki & Hoshino, Takahiro, 2022. "Joint modeling of effects of customer tier program on customer purchase duration and purchase amount," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    7. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    8. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
    9. Wang, Lu & Ma, Feng & Niu, Tianjiao & He, Chengting, 2020. "Crude oil and BRICS stock markets under extreme shocks: New evidence," Economic Modelling, Elsevier, vol. 86(C), pages 54-68.
    10. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    11. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.

  3. Hautsch, Nikolaus & Herrera, Rodrigo, 2015. "Multivariate dynamic intensity peaks-over-threshold models," CFS Working Paper Series 516, Center for Financial Studies (CFS).

    Cited by:

    1. Pushpa Dissanayake & Teresa Flock & Johanna Meier & Philipp Sibbertsen, 2021. "Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights," Mathematics, MDPI, vol. 9(21), pages 1-33, November.
    2. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.
    3. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.

  4. Rodrigo Herrera & Bernhard Schipp, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers SFB649DP2011-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.
    2. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    4. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Russ Moro & Wolfgang Härdle & Saeideh Aliakbari & Linda Hoffmann, 2011. "Forecasting Corporate Distress in the Asian and Pacific Region," SFB 649 Discussion Papers SFB649DP2011-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    12. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    18. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," SFB 649 Discussion Papers SFB649DP2011-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Nicole Wiebach & Jana L. Diels, 2011. "The impact of context and promotion on consumer responses and preferences in out-of-stock situations," SFB 649 Discussion Papers SFB649DP2011-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "We develop a sequential trade model of Iceberg order execution in a limit order book. The Iceberg-trader has the freedom to expose his trading intentions or (partially) shield the true order size agai," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    27. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    28. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    33. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.

Articles

  1. Fernanda Fuentes & Rodrigo Herrera, 2020. "Dynamics of Connectedness in Clean Energy Stocks," Energies, MDPI, vol. 13(14), pages 1-19, July.

    Cited by:

    1. K. Abhaya Kumar & Prakash Pinto & Iqbal Thonse Hawaldar & Saheem Shaikh & Shravan Bhagav & B. Padmanabha, 2022. "Investigating the Nexus between Crude Oil Price and Stock Prices of Oil Exploration Companies," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 40-47, July.
    2. Çelik, İsmail & Sak, Ahmet Furkan & Höl, Arife Özdemir & Vergili, Gizem, 2022. "The dynamic connectedness and hedging opportunities of implied and realized volatility: Evidence from clean energy ETFs," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    3. Kuang, Wei, 2021. "Which clean energy sectors are attractive? A portfolio diversification perspective," Energy Economics, Elsevier, vol. 104(C).
    4. Kocaarslan, Baris & Soytas, Ugur, 2021. "Reserve currency and the volatility of clean energy stocks: The role of uncertainty," Energy Economics, Elsevier, vol. 104(C).

  2. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.

    Cited by:

    1. Fadugba, Sunday Emmanuel, 2020. "Homotopy analysis method and its applications in the valuation of European call options with time-fractional Black-Scholes equation," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).

  3. Nikolaus Hautsch & Rodrigo Herrera, 2020. "Multivariate dynamic intensity peaks‐over‐threshold models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 248-272, March.
    See citations under working paper version above.
  4. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2018. "Modeling extreme risks in commodities and commodity currencies," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 108-120.
    See citations under working paper version above.
  5. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.

    Cited by:

    1. Guo, Ranran & Ye, Wuyi, 2021. "A model of dynamic tail dependence between crude oil prices and exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    2. Hong Qiu & Genhua Hu & Yuhong Yang & Jeffrey Zhang & Ting Zhang, 2020. "Modeling the Risk of Extreme Value Dependence in Chinese Regional Carbon Emission Markets," Sustainability, MDPI, vol. 12(19), pages 1-15, September.

  6. Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
    See citations under working paper version above.
  7. Moisan, Stella & Herrera, Rodrigo & Clements, Adam, 2018. "A dynamic multiple equation approach for forecasting PM2.5 pollution in Santiago, Chile," International Journal of Forecasting, Elsevier, vol. 34(4), pages 566-581.

    Cited by:

    1. Behm, Svenia & Haupt, Harry, 2020. "Predictability of hourly nitrogen dioxide concentration," Ecological Modelling, Elsevier, vol. 428(C).
    2. Clements, Adam & Hurn, Stan & Volkov, Vladimir, 2021. "A simple linear alternative to multiplicative error models with an application to trading volume," Working Papers 2021-06, University of Tasmania, Tasmanian School of Business and Economics.
    3. Pei Du & Jianzhou Wang & Wendong Yang & Tong Niu, 2022. "A novel hybrid fine particulate matter (PM2.5) forecasting and its further application system: Case studies in China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 64-85, January.
    4. Ying Wang & Jianzhou Wang & Hongmin Li & Hufang Yang & Zhiwu Li, 2022. "Multi‐step air quality index forecasting via data preprocessing, sequence reconstruction, and improved multi‐objective optimization algorithm," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1483-1511, November.
    5. Xiang Xu, 2020. "Forecasting air pollution PM2.5 in Beijing using weather data and multiple kernel learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 117-125, March.
    6. Zhongfei Li & Kai Gan & Shaolong Sun & Shouyang Wang, 2023. "A new PM2.5 concentration forecasting system based on AdaBoost‐ensemble system with deep learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 154-175, January.
    7. Du, Ruijin & Li, Jingjing & Dong, Gaogao & Tian, Lixin & Qing, Ting & Fang, Guochang & Dong, Yujuan, 2020. "Percolation analysis of urban air quality: A case in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).

  8. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.

    Cited by:

    1. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2021. "A Markov-Switching VSTOXX Trading Algorithm for Enhancing EUR Stock Portfolio Performance," Mathematics, MDPI, vol. 9(9), pages 1-28, May.
    2. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    3. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    4. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Zhi-Qiang Jiang & Wei-Xing Zhou, 2018. "Multifractal characteristics and return predictability in the Chinese stock markets," Papers 1806.07604, arXiv.org.
    5. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M., 2020. "The (in)efficiency of NYMEX energy futures: A multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    6. Li, Dongxin & Hong, Yanran & Wang, Lu & Xu, Pengfei & Pan, Zhigang, 2022. "Extreme risk transmission among bitcoin and crude oil markets," Resources Policy, Elsevier, vol. 77(C).
    7. Xi, Yue & Zeng, Qing & Lu, Xinjie & Huynh, Toan L.D., 2022. "Oil and renewable energy stock markets: Unique role of extreme shocks," Energy Economics, Elsevier, vol. 109(C).
    8. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    9. Wang, Lu & Ma, Feng & Niu, Tianjiao & He, Chengting, 2020. "Crude oil and BRICS stock markets under extreme shocks: New evidence," Economic Modelling, Elsevier, vol. 86(C), pages 54-68.
    10. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
    11. Oscar V. De la Torre-Torres & Dora Aguilasocho-Montoya & María de la Cruz del Río-Rama, 2020. "A Two-Regime Markov-Switching GARCH Active Trading Algorithm for Coffee, Cocoa, and Sugar Futures," Mathematics, MDPI, vol. 8(6), pages 1-19, June.
    12. Guo, Xiaozhu & Huang, Yisu & Liang, Chao & Umar, Muhammad, 2022. "Forecasting volatility of EUA futures: New evidence," Energy Economics, Elsevier, vol. 110(C).
    13. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).

  9. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.

    Cited by:

    1. Maryniak, Paweł & Trück, Stefan & Weron, Rafał, 2019. "Carbon pricing and electricity markets — The case of the Australian Clean Energy Bill," Energy Economics, Elsevier, vol. 79(C), pages 45-58.
    2. Lu, Xin & Qiu, Jing & Lei, Gang & Zhu, Jianguo, 2022. "Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia," Applied Energy, Elsevier, vol. 308(C).
    3. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.
    4. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    5. Yan, Guan & Trück, Stefan, 2020. "A dynamic network analysis of spot electricity prices in the Australian national electricity market," Energy Economics, Elsevier, vol. 92(C).
    6. Marwan, Marwan, 2020. "The impact of probability of electricity price spike and outside temperature to define total expected cost for air conditioning," Energy, Elsevier, vol. 195(C).
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Wong, Jin Boon & Zhang, Qin, 2022. "Impact of carbon tax on electricity prices and behaviour," Finance Research Letters, Elsevier, vol. 44(C).
    9. Liu, Luyao & Bai, Feifei & Su, Chenyu & Ma, Cuiping & Yan, Ruifeng & Li, Hailong & Sun, Qie & Wennersten, Ronald, 2022. "Forecasting the occurrence of extreme electricity prices using a multivariate logistic regression model," Energy, Elsevier, vol. 247(C).
    10. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    11. Horst, Ulrich & Xu, Wei, 2021. "Functional limit theorems for marked Hawkes point measures," Stochastic Processes and their Applications, Elsevier, vol. 134(C), pages 94-131.
    12. Nishio, Kazuki & Hoshino, Takahiro, 2022. "Joint modeling of effects of customer tier program on customer purchase duration and purchase amount," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    13. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian national electricity market: A higher moment analysis," CAMA Working Papers 2020-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    15. Philip Protter & Qianfan Wu & Shihao Yang, 2021. "Order Book Queue Hawkes-Markovian Modeling," Papers 2107.09629, arXiv.org, revised Jan 2022.
    16. Cavaliere, Giuseppe & Lu,Ye & Rahbek, Anders & Staerk-Ostergaard, J, 2021. "Bootstrap Inference For Hawkes And General Point Processes," Working Papers 2021-05, University of Sydney, School of Economics.
    17. Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," CQE Working Papers 6117, Center for Quantitative Economics (CQE), University of Muenster.
    18. Ulrich Horst & Wei Xu, 2019. "Functional Limit Theorems for Marked Hawkes Point Measures ," Working Papers hal-02443841, HAL.
    19. Pawel Maryniak & Stefan Trueck & Rafal Weron, 2016. "Carbon pricing, forward risk premiums and pass-through rates in Australian electricity futures markets," HSC Research Reports HSC/16/10, Hugo Steinhaus Center, Wroclaw University of Technology.
    20. Godin, Frédéric & Ibrahim, Zinatu, 2021. "An analysis of electricity congestion price patterns in North America," Energy Economics, Elsevier, vol. 102(C).
    21. Nadja Klein & Michael Stanley Smith & David J. Nott, 2020. "Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices," Papers 2010.01844, arXiv.org, revised May 2021.
    22. Wierzbowski, Michal & Filipiak, Izabela, 2017. "Enhanced operational reserve as a tool for development of optimal energy mix," Energy Policy, Elsevier, vol. 102(C), pages 602-615.
    23. Bigerna, Simona & Bollino, Carlo Andrea & Ciferri, Davide & Polinori, Paolo, 2017. "Renewables diffusion and contagion effect in Italian regional electricity markets: Assessment and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 199-211.
    24. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Value-at-risk methodologies for effective energy portfolio risk management," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 197-212.
    25. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    26. Nazifi, Fatemeh & Trück, Stefan & Zhu, Liangxu, 2021. "Carbon pass-through rates on spot electricity prices in Australia," Energy Economics, Elsevier, vol. 96(C).

  10. Herrera, Rodrigo & Schipp, Bernhard, 2014. "Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 218-238.

    Cited by:

    1. Pushpa Dissanayake & Teresa Flock & Johanna Meier & Philipp Sibbertsen, 2021. "Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights," Mathematics, MDPI, vol. 9(21), pages 1-33, November.
    2. Hautsch, Nikolaus & Herrera, Rodrigo, 2015. "Multivariate dynamic intensity peaks-over-threshold models," CFS Working Paper Series 516, Center for Financial Studies (CFS).
    3. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.
    4. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2017. "Risk quantification in turmoil markets," Risk Management, Palgrave Macmillan, vol. 19(3), pages 202-224, August.
    5. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    6. Ahmad, Wasim & Kutan, Ali M. & Chahal, Rishman Jot Kaur & Kattumuri, Ruth, 2021. "COVID-19 Pandemic and firm-level dynamics in the USA, UK, Europe, and Japan," International Review of Financial Analysis, Elsevier, vol. 78(C).
    7. Jing, Bo & Li, Shenghong & Ma, Yong, 2021. "Consistent pricing of VIX options with the Hawkes jump-diffusion model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

  11. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.

    Cited by:

    1. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    2. Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Giorgia Callegaro & Andrea Mazzoran & Carlo Sgarra, 2019. "A Self-Exciting Modelling Framework for Forward Prices in Power Markets," Papers 1910.13286, arXiv.org.
    5. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    6. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
    7. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    8. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    9. Auerbach, Jonathan & Wan, Phyllis, 2020. "Forecasting the urban skyline with extreme value theory," International Journal of Forecasting, Elsevier, vol. 36(3), pages 814-828.
    10. Thomas Deschatre & Olivier F'eron & Pierre Gruet, 2021. "A survey of electricity spot and futures price models for risk management applications," Papers 2103.16918, arXiv.org, revised Jul 2021.
    11. Jiao, Ying & Ma, Chunhua & Scotti, Simone & Sgarra, Carlo, 2019. "A branching process approach to power markets," Energy Economics, Elsevier, vol. 79(C), pages 144-156.
    12. Bigerna, Simona & Bollino, Carlo Andrea & Ciferri, Davide & Polinori, Paolo, 2017. "Renewables diffusion and contagion effect in Italian regional electricity markets: Assessment and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 199-211.
    13. Stephen Chan & Saralees Nadarajah, 2015. "Extreme value analysis of electricity demand in the UK," Applied Economics Letters, Taylor & Francis Journals, vol. 22(15), pages 1246-1251, October.

  12. Alexander Karmann & Rodrigo Herrera, 2014. "Volatility Contagion in the Asian Crisis: New Evidence of Volatility Tail Dependence," Review of Development Economics, Wiley Blackwell, vol. 18(2), pages 354-371, May.

    Cited by:

    1. Chen, Muzi & Li, Nan & Zheng, Lifen & Huang, Difang & Wu, Boyao, 2022. "Dynamic correlation of market connectivity, risk spillover and abnormal volatility in stock price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).

  13. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.

    Cited by:

    1. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.
    2. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.
    3. Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
    4. Li, Dongxin & Hong, Yanran & Wang, Lu & Xu, Pengfei & Pan, Zhigang, 2022. "Extreme risk transmission among bitcoin and crude oil markets," Resources Policy, Elsevier, vol. 77(C).
    5. Herrera, Rodrigo & Schipp, Bernhard, 2014. "Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 218-238.
    6. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    7. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    8. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    9. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    10. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    11. Buccioli, Alice & Kokholm, Thomas & Nicolosi, Marco, 2019. "Expected shortfall and portfolio management in contagious markets," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 100-115.
    12. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.

  14. Herrera, Rodrigo, 2013. "Energy risk management through self-exciting marked point process," Energy Economics, Elsevier, vol. 38(C), pages 64-76.

    Cited by:

    1. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.
    2. Herrera, R. & Clements, A.E., 2018. "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 161-175.
    3. Herrera, Rodrigo & González, Sergio & Clements, Adam, 2018. "Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 70-88.
    4. Herrera, Rodrigo & Schipp, Bernhard, 2014. "Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 218-238.
    5. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
    6. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    7. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2019. "Quantifying Risk in Traditional Energy and Sustainable Investments," Sustainability, MDPI, vol. 11(3), pages 1-22, January.

  15. Herrera, R. & Eichler, S., 2011. "Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2916-2930, November.

    Cited by:

    1. Stefan Eichler, 2012. "The impact of banking and sovereign debt crisis risk in the eurozone on the euro/US dollar exchange rate," Applied Financial Economics, Taylor & Francis Journals, vol. 22(15), pages 1215-1232, August.
    2. Michael A. Goldstein & Joseph McCarthy & Alexei G. Orlov, 2019. "The Core, Periphery, and Beyond: Stock Market Comovements among EU and Non‐EU Countries," The Financial Review, Eastern Finance Association, vol. 54(1), pages 5-56, February.

Chapters

  1. Rodrigo Herrera & Jörg Kalcsics & Stefan Nickel, 2008. "Reliability Models for the Uncapacitated Facility Location Problem with User Preferences," Operations Research Proceedings, in: Jörg Kalcsics & Stefan Nickel (ed.), Operations Research Proceedings 2007, pages 135-140, Springer.

    Cited by:

    1. Fu Wang & Manqing Ye & Hongbin Zhu & Dengjun Gu, 2022. "Optimization Method for Conventional Bus Stop Placement and the Bus Line Network Based on the Voronoi Diagram," Sustainability, MDPI, vol. 14(13), pages 1-20, June.

More information

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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) 2015-10-04 2016-05-21 2022-09-05
  2. NEP-ECM: Econometrics (2) 2015-10-04 2022-09-05
  3. NEP-FOR: Forecasting (2) 2015-10-04 2016-05-21

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