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Rodrigo Herrera

Personal Details

First Name:Rodrigo
Middle Name:
Last Name:Herrera
Suffix:
RePEc Short-ID:phe650
[This author has chosen not to make the email address public]
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. Hautsch, Nikolaus & Herrera, Rodrigo, 2015. "Multivariate dynamic intensity peaks-over-threshold models," CFS Working Paper Series 516, Center for Financial Studies (CFS).
  5. R Herrera & Adam Clements, 2015. "Point process models for extreme returns: Harnessing implied volatility," NCER Working Paper Series 104, National Centre for Econometric Research.
  6. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  7. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

Articles

  1. Herrera, Rodrigo & Piña, Marco, 2024. "Market risk modeling with option-implied covariances and score-driven dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  2. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
  3. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
  4. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
  5. 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.
  6. Fernanda Fuentes & Rodrigo Herrera, 2020. "Dynamics of Connectedness in Clean Energy Stocks," Energies, MDPI, vol. 13(14), pages 1-19, July.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. Alexander Karmann & Rodrigo Herrera, 2014. "Special Issue: Issues in Asia. Guest Editor: Laixun Zhao," Review of Development Economics, Wiley Blackwell, vol. 18(2), pages 354-371, May.
  19. 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.
  20. Herrera, Rodrigo, 2013. "Energy risk management through self-exciting marked point process," Energy Economics, Elsevier, vol. 38(C), pages 64-76.
  21. 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. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    2. Song, Shiyu, 2024. "The valuation of arithmetic Asian options with mean reversion and jump clustering," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    3. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    4. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    5. 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).
    6. Go, You-How & Lau, Wee-Yeap, 2024. "Terms of trade or market power? Further evidence from dynamic spillovers in return and volatility between Malaysian crude palm oil and foreign exchange markets," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).

  2. 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. Dissanayake, Pushpa & Flock, Teresa & Meier, Johanna & Sibbertsen, Philipp, 2021. "Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights," Hannover Economic Papers (HEP) dp-690, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    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. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    4. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.

  3. 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. 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).
    2. 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).
    3. 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).
    4. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    5. Lu Wang & Feng Ma & Guoshan Liu & Qiaoqi Lang, 2023. "Do extreme shocks help forecast oil price volatility? The augmented GARCH‐MIDAS approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2056-2073, April.
    6. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    7. 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.
    8. 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).
    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. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.
    11. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    12. Hong, Yanran & Li, Pan & Wang, Lu & Zhang, Yaojie, 2023. "New evidence of extreme risk transmission between financial stress and international crude oil markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    13. 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.
    14. 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.
    15. 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. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. 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.
    2. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric estimation with generated covariates," SFB 649 Discussion Papers 2011-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Fiocco, Raffaele & Gilli, Mario, 2011. "Bargaining and collusion in a regulatory model," SFB 649 Discussion Papers 2011-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2011. "Rollover risk, network structure and systemic financial crises," SFB 649 Discussion Papers 2011-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Aurélie Bertrand & Christian Hafner, 2014. "On heterogeneous latent class models with applications to the analysis of rating scores," Computational Statistics, Springer, vol. 29(1), pages 307-330, February.
    7. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Scheffel, Juliane, 2011. "Compensation of unusual working schedules," SFB 649 Discussion Papers 2011-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution Permits, Strategic Trading and Dynamic Technology Adoption," CESifo Working Paper Series 3399, CESifo.
    11. Kappus, Johanna & Reiß, Markus, 2010. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers 2010-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Naujokat, Felix & Horst, Ulrich, 2011. "When to cross the spread: Curve following with singular control," SFB 649 Discussion Papers 2011-053, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Moro, Russ & Härdle, Wolfgang Karl & Aliakbari, Saeideh & Hoffmann, Linda, 2011. "Forecasting corporate distress in the Asian and Pacific region," SFB 649 Discussion Papers 2011-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    15. Kratz, Peter & Schöneborn, Torsten, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers 2011-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Härdle, Wolfgang Karl & Osipenko, Maria, 2011. "Pricing Chinese rain: A multisite mulit-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers 2011-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Bindseil, Ulrich & König, Philipp Johann, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers 2011-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang Karl, 2011. "TVICA - time varying independent component analysis and its application to financial data," SFB 649 Discussion Papers 2011-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. 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.
    23. Stahlschmidt, Stephan & Tausendteufel, Helmut & Härdle, Wolfgang Karl, 2011. "Bayesian Networks and sex-related homicides," SFB 649 Discussion Papers 2011-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    24. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    25. Fiocco, Raffaele & Scarpa, Carlo, 2011. "The regulation of interdependent markets," SFB 649 Discussion Papers 2011-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    26. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    27. Moreno-Bromberg, Santiago & Pirvu, Traian A. & Réveillac, Anthony, 2011. "CRRA utility maximization under risk constraints," SFB 649 Discussion Papers 2011-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    28. Cebiroğlu, Gökhan & Horst, Ulrich, 2011. "Optimal display of Iceberg orders," SFB 649 Discussion Papers 2011-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    29. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    30. Reiß, Markus & Rozenholc, Yves & Cuenod, Charles A., 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers 2011-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    31. Bibinger, Markus, 2011. "Asymptotics of asynchronicity," SFB 649 Discussion Papers 2011-033, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    32. Bibinger, Markus, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers 2011-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    33. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    34. Meyer-Gohde, Alexander, 2011. "Monetary policy, determinacy, and the natural rate hypothesis," SFB 649 Discussion Papers 2011-049, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    35. 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.
    36. Wiebach, Nicole & Diels, Jana L., 2011. "The impact of context and promotion on consumer responses and preferences in out-of-stock situations," SFB 649 Discussion Papers 2011-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  5. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. 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.
    2. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric estimation with generated covariates," SFB 649 Discussion Papers 2011-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Fiocco, Raffaele & Gilli, Mario, 2011. "Bargaining and collusion in a regulatory model," SFB 649 Discussion Papers 2011-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2011. "Rollover risk, network structure and systemic financial crises," SFB 649 Discussion Papers 2011-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Aurélie Bertrand & Christian Hafner, 2014. "On heterogeneous latent class models with applications to the analysis of rating scores," Computational Statistics, Springer, vol. 29(1), pages 307-330, February.
    7. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Scheffel, Juliane, 2011. "Compensation of unusual working schedules," SFB 649 Discussion Papers 2011-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution Permits, Strategic Trading and Dynamic Technology Adoption," CESifo Working Paper Series 3399, CESifo.
    11. Kappus, Johanna & Reiß, Markus, 2010. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers 2010-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Naujokat, Felix & Horst, Ulrich, 2011. "When to cross the spread: Curve following with singular control," SFB 649 Discussion Papers 2011-053, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Moro, Russ & Härdle, Wolfgang Karl & Aliakbari, Saeideh & Hoffmann, Linda, 2011. "Forecasting corporate distress in the Asian and Pacific region," SFB 649 Discussion Papers 2011-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    14. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    15. Kratz, Peter & Schöneborn, Torsten, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers 2011-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Härdle, Wolfgang Karl & Osipenko, Maria, 2011. "Pricing Chinese rain: A multisite mulit-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers 2011-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Bindseil, Ulrich & König, Philipp Johann, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers 2011-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    21. Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang Karl, 2011. "TVICA - time varying independent component analysis and its application to financial data," SFB 649 Discussion Papers 2011-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. 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.
    23. Stahlschmidt, Stephan & Tausendteufel, Helmut & Härdle, Wolfgang Karl, 2011. "Bayesian Networks and sex-related homicides," SFB 649 Discussion Papers 2011-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    24. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    25. Fiocco, Raffaele & Scarpa, Carlo, 2011. "The regulation of interdependent markets," SFB 649 Discussion Papers 2011-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    26. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    27. Moreno-Bromberg, Santiago & Pirvu, Traian A. & Réveillac, Anthony, 2011. "CRRA utility maximization under risk constraints," SFB 649 Discussion Papers 2011-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    28. Cebiroğlu, Gökhan & Horst, Ulrich, 2011. "Optimal display of Iceberg orders," SFB 649 Discussion Papers 2011-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    29. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    30. Reiß, Markus & Rozenholc, Yves & Cuenod, Charles A., 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers 2011-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    31. Bibinger, Markus, 2011. "Asymptotics of asynchronicity," SFB 649 Discussion Papers 2011-033, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    32. Bibinger, Markus, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers 2011-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    33. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    34. Meyer-Gohde, Alexander, 2011. "Monetary policy, determinacy, and the natural rate hypothesis," SFB 649 Discussion Papers 2011-049, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    35. 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.
    36. Wiebach, Nicole & Diels, Jana L., 2011. "The impact of context and promotion on consumer responses and preferences in out-of-stock situations," SFB 649 Discussion Papers 2011-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

Articles

  1. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.

    Cited by:

    1. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    2. Federico Gatta & Fabrizio Lillo & Piero Mazzarisi, 2024. "CAESar: Conditional Autoregressive Expected Shortfall," Papers 2407.06619, arXiv.org.

  2. 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.

    Cited by:

    1. Stavros Kalogiannidis & Stamatis Kontsas & Dimitrios Kalfas & Fotios Chatzitheodoridis, 2024. "Operational risk management in managerial accounting: a comprehensive examination of strategies and implementation in medium size organizations," Operational Research, Springer, vol. 24(3), pages 1-27, September.

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

    Cited by:

    1. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    2. Kuang, Wei, 2021. "Which clean energy sectors are attractive? A portfolio diversification perspective," Energy Economics, Elsevier, vol. 104(C).
    3. Chuliá, Helena & Muñoz-Mendoza, Jorge A. & Uribe, Jorge M., 2023. "Energy firms in emerging markets: Systemic risk and diversification opportunities," Emerging Markets Review, Elsevier, vol. 56(C).
    4. 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).
    5. Guangxi Cao & Fei Xie, 2024. "Extreme risk spillovers across energy and carbon markets: Evidence from the quantile extended joint connectedness approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2155-2175, April.
    6. 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.
    7. Kocaarslan, Baris & Soytas, Ugur, 2021. "Reserve currency and the volatility of clean energy stocks: The role of uncertainty," Energy Economics, Elsevier, vol. 104(C).
    8. Talat S. Genc & Stephen Kosempel, 2023. "Energy Transition and the Economy: A Review Article," Energies, MDPI, vol. 16(7), pages 1-26, March.
    9. Guangxi Cao & Fei Xie & Meijun Ling, 2022. "Spillover effects in Chinese carbon, energy and financial markets," International Finance, Wiley Blackwell, vol. 25(3), pages 416-434, December.
    10. Ibrahim D. Raheem & Oluyele Akinkugbe & Agboola H. Yusuf & Mahdi Ghaemi Asl, 2023. "Hedging strategies among financial markets: the case of green and brown assets," Empirical Economics, Springer, vol. 65(2), pages 831-873, August.
    11. Rui Dias & Nicole Horta & Mariana Chambino, 2023. "Clean Energy Action Index Efficiency: An Analysis in Global Uncertainty Contexts," Energies, MDPI, vol. 16(9), pages 1-18, May.

  4. 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. Stindl, Tom, 2023. "Forecasting intraday market risk: A marked self-exciting point process with exogenous renewals," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 182-198.
    2. 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. James, Robert & Leung, Henry & Leung, Jessica Wai Yin & Prokhorov, Artem, 2023. "Forecasting tail risk measures for financial time series: An extreme value approach with covariates," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 29-50.

  5. 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.
  6. 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.

    Cited by:

    1. Amanda, Citra, 2023. "Rural banking spatial competition and stability," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 492-504.

  7. 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.
  8. 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. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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.

  9. 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.
  10. 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.

  11. 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. 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).
    2. Song, Shiyu, 2024. "The valuation of arithmetic Asian options with mean reversion and jump clustering," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    3. 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.
    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. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    6. 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).
    7. 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.
    8. 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.
    9. 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).
    10. James, Robert & Leung, Henry & Leung, Jessica Wai Yin & Prokhorov, Artem, 2023. "Forecasting tail risk measures for financial time series: An extreme value approach with covariates," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 29-50.
    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. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
    13. 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.
    14. 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.
    15. 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).
    16. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    17. Muğaloğlu, Erhan & Kuşkaya, Sevda & Aldieri, Luigi & Alnour, Mohammed & Hoque, Mohammad Enamul & Magazzino, Cosimo & Bilgili, Faik, 2023. "Dynamic regime differences in the market behavior of primary natural resources in response to geopolitical risk and economic policy uncertainty," Resources Policy, Elsevier, vol. 87(PB).
    18. Guo, Xiaozhu & Huang, Yisu & Liang, Chao & Umar, Muhammad, 2022. "Forecasting volatility of EUA futures: New evidence," Energy Economics, Elsevier, vol. 110(C).

  12. 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. 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.
    3. 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).
    4. 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).
    5. Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data," Working Papers 201739, University of Pretoria, Department of Economics.
    6. Galarneau-Vincent, Rémi & Gauthier, Geneviève & Godin, Frédéric, 2023. "Foreseeing the worst: Forecasting electricity DART spikes," Energy Economics, Elsevier, vol. 119(C).
    7. 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. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.
    9. Nazifi, Fatemeh & Trück, Stefan & Zhu, Liangxu, 2021. "Carbon pass-through rates on spot electricity prices in Australia," Energy Economics, Elsevier, vol. 96(C).
    10. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian National Electricity Market: A Higher‐Moment Analysis," The Economic Record, The Economic Society of Australia, vol. 96(315), pages 450-469, December.
    11. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    12. 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).
    13. 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 Science and Technology.
    14. 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.
    15. Ming, Wei & Nazifi, Fatemeh & Trück, Stefan, 2024. "Emission intensities in the Australian National Electricity Market – An econometric analysis," Energy Economics, Elsevier, vol. 129(C).
    16. 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.
    17. 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.
    18. Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).
    19. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
    20. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    21. Tselika, Kyriaki & Tselika, Maria & Demetriades, Elias, 2024. "Quantifying the short-term asymmetric effects of renewable energy on the electricity merit-order curve," Energy Economics, Elsevier, vol. 132(C).
    22. Godin, Frédéric & Ibrahim, Zinatu, 2021. "An analysis of electricity congestion price patterns in North America," Energy Economics, Elsevier, vol. 102(C).
    23. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    24. 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.
    25. 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.
    26. Philip Protter & Qianfan Wu & Shihao Yang, 2021. "Order Book Queue Hawkes-Markovian Modeling," Papers 2107.09629, arXiv.org, revised Jan 2022.
    27. Sirin, Selahattin Murat & Camadan, Ercument & Erten, Ibrahim Etem & Zhang, Alex Hongliang, 2023. "Market failure or politics? Understanding the motives behind regulatory actions to address surging electricity prices," Energy Policy, Elsevier, vol. 180(C).
    28. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    29. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    30. Wong, Jin Boon & Zhang, Qin, 2022. "Impact of carbon tax on electricity prices and behaviour," Finance Research Letters, Elsevier, vol. 44(C).
    31. 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.
    32. Nadja Klein & Michael Stanley Smith & David J. Nott, 2023. "Deep distributional time series models and the probabilistic forecasting of intraday electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 493-511, June.
    33. 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).
    34. Ulrich Horst & Wei Xu, 2019. "Functional Limit Theorems for Marked Hawkes Point Measures ," Working Papers hal-02443841, HAL.
    35. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    36. 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).

  13. 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. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    2. Dissanayake, Pushpa & Flock, Teresa & Meier, Johanna & Sibbertsen, Philipp, 2021. "Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights," Hannover Economic Papers (HEP) dp-690, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    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. 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," LSE Research Online Documents on Economics 112454, London School of Economics and Political Science, LSE Library.
    5. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    6. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(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).
    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. 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.
    10. 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.

  14. 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. R Herrera & Adam Clements, 2015. "Point process models for extreme returns: Harnessing implied volatility," NCER Working Paper Series 104, National Centre for Econometric Research.
    2. 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.
    3. Galarneau-Vincent, Rémi & Gauthier, Geneviève & Godin, Frédéric, 2023. "Foreseeing the worst: Forecasting electricity DART spikes," Energy Economics, Elsevier, vol. 119(C).
    4. Song, Shiyu, 2024. "The valuation of arithmetic Asian options with mean reversion and jump clustering," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    5. 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.
    6. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    7. 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).
    8. 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.
    9. 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.
    10. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
    11. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    12. 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.
    13. 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.
    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. Auerbach, Jonathan & Wan, Phyllis, 2020. "Forecasting the urban skyline with extreme value theory," International Journal of Forecasting, Elsevier, vol. 36(3), pages 814-828.
    16. Giorgia Callegaro & Andrea Mazzoran & Carlo Sgarra, 2019. "A Self-Exciting Modelling Framework for Forward Prices in Power Markets," Papers 1910.13286, arXiv.org.
    17. 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.

  15. Alexander Karmann & Rodrigo Herrera, 2014. "Special Issue: Issues in Asia. Guest Editor: Laixun Zhao," 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).
    2. Muzi Chen & Nan Li & Lifen Zheng & Difang Huang & Boyao Wu, 2024. "Dynamic Correlation of Market Connectivity, Risk Spillover and Abnormal Volatility in Stock Price," Papers 2403.19363, arXiv.org.

  16. 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. 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).
    2. 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.
    3. Stindl, Tom, 2023. "Forecasting intraday market risk: A marked self-exciting point process with exogenous renewals," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 182-198.
    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. 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).
    6. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    7. 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.
    8. 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.
    9. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    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. 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.
    12. 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.
    13. Hong, Yanran & Li, Pan & Wang, Lu & Zhang, Yaojie, 2023. "New evidence of extreme risk transmission between financial stress and international crude oil markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    14. Hamidreza Arian & Hossein Poorvasei & Azin Sharifi & Shiva Zamani, 2020. "The Uncertain Shape of Grey Swans: Extreme Value Theory with Uncertain Threshold," Papers 2011.06693, arXiv.org.
    15. 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.
    16. 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.

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

    Cited by:

    1. 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.
    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.
    3. 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.
    4. Song, Shiyu, 2024. "The valuation of arithmetic Asian options with mean reversion and jump clustering," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    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.
    6. Alfonso Novales & Laura Garcia-Jorcano, 2019. "Backtesting Extreme Value Theory models of expected shortfall," Documentos de Trabajo del ICAE 2019-24, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    7. 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.
    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. 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.

  18. 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. 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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