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Filippo Petroni

Personal Details

First Name:Filippo
Middle Name:
Last Name:Petroni
Suffix:
RePEc Short-ID:ppe725

Affiliation

Dipartimento di Scienze Economiche e Aziendali
Università degli Studi di Cagliari

Cagliari, Italy
http://dipartimenti.unica.it/scienzeeconomicheedaziendali/
RePEc:edi:drcagit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Chiara Corini & Guglielmo D'Amico & Filippo Petroni & Flavio Prattico & Raimondo Manca, 2015. "Tornadoes and related damage costs: statistical modeling with a semi-Markov approach," Papers 1503.05127, arXiv.org.
  2. Filippo Petroni & Maurizio Serva, 2015. "Observability of Market Daily Volatility," Papers 1503.08032, arXiv.org.
  3. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.
  4. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
  5. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.
  6. Guglielmo D'Amico & Filippo Petroni, 2011. "A semi-Markov model with memory for price changes," Papers 1109.4259, arXiv.org, revised Dec 2011.
  7. Guglielmo D'Amico & Filippo Petroni, 2011. "A semi-Markov model for price returns," Papers 1103.6143, arXiv.org.
  8. Filippo Petroni & Giulia Rotundo, 2007. "Effectiveness of Measures of Performance During Speculative Bubbles," Papers 0709.2423, arXiv.org.
  9. M. H. Jensen & A. Johansen & F. Petroni & I. Simonsen, 2004. "Inverse Statistics in the Foreign Exchange Market," Papers cond-mat/0402591, arXiv.org, revised Mar 2004.

Articles

  1. Paolo Mattana & Filippo Petroni & Stefania Patrizia Sonia Rossi, 2015. "A test for the too-big-to-fail hypothesis for European banks during the financial crisis," Applied Economics, Taylor & Francis Journals, vol. 47(4), pages 319-332, January.
  2. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.
  3. Guglielmo D'Amico & Filippo Petroni & Flavio Prattico, 2013. "Wind speed modeled as an indexed semi‐Markov process," Environmetrics, John Wiley & Sons, Ltd., vol. 24(6), pages 367-376, September.
  4. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2013. "First and second order semi-Markov chains for wind speed modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1194-1201.
  5. D’Amico, Guglielmo & Petroni, Filippo, 2012. "A semi-Markov model for price returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4867-4876.
  6. Petroni, Filippo & Serva, Maurizio, 2010. "Measures of lexical distance between languages," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(11), pages 2280-2283.
  7. Ausloos, M. & Petroni, F., 2009. "Statistical dynamics of religion evolutions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4438-4444.
  8. Petroni, Filippo & Rotundo, Giulia, 2008. "Effectiveness of measures of performance during speculative bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3942-3948.
  9. Petroni, Filippo & Ausloos, Marcel, 2008. "High frequency intrinsic modes in El Niño/Southern Oscillation Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5246-5254.
  10. Ausloos, M. & Petroni, F., 2007. "Tsallis non-extensive statistical mechanics of El Niño southern oscillation index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 721-736.
  11. Petroni, F. & Ausloos, M. & Rotundo, G., 2007. "Generating synthetic time series from Bak–Sneppen co-evolution model mixtures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 359-367.
  12. Serva, M. & Fulco, U.L. & Gléria, I.M. & Lyra, M.L. & Petroni, F. & Viswanathan, G.M., 2006. "A Markov model of financial returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 393-403.
  13. F. Petroni & M. Serva, 2006. "Investment strategies and hidden variables," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 51(4), pages 601-608, June.
  14. Petroni, Filippo & Serva, Maurizio, 2004. "Real prices from spot foreign exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 194-197.
  15. Jensen, M.H & Johansen, A & Petroni, F & Simonsen, I, 2004. "Inverse statistics in the foreign exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(4), pages 678-684.
  16. F. Petroni & M. Serva, 2003. "Spot foreign exchange market and time series," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 34(4), pages 495-500, August.

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. Chiara Corini & Guglielmo D'Amico & Filippo Petroni & Flavio Prattico & Raimondo Manca, 2015. "Tornadoes and related damage costs: statistical modeling with a semi-Markov approach," Papers 1503.05127, arXiv.org.

    Cited by:

    1. Brecht Verbeken & Marie-Anne Guerry, 2021. "Discrete Time Hybrid Semi-Markov Models in Manpower Planning," Mathematics, MDPI, vol. 9(14), pages 1-13, July.

  2. Filippo Petroni & Maurizio Serva, 2015. "Observability of Market Daily Volatility," Papers 1503.08032, arXiv.org.

    Cited by:

    1. D’Amico, Guglielmo & Gismondi, Fulvio & Petroni, Filippo & Prattico, Flavio, 2019. "Stock market daily volatility and information measures of predictability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 22-29.
    2. Pan, Zhiyuan & Liu, Li, 2018. "Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 168-180.
    3. Zhu, Sha & Liu, Qiuhong & Wang, Yan & Wei, Yu & Wei, Guiwu, 2019. "Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    4. Guglielmo D'Amico & Filippo Petroni, 2020. "A micro-to-macro approach to returns, volumes and waiting times," Papers 2007.06262, arXiv.org.

  3. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.

    Cited by:

    1. Guglielmo D'Amico & Filippo Petroni, 2017. "A new approach to the modeling of financial volumes," Papers 1709.05823, arXiv.org.
    2. Guglielmo D’Amico & Fulvio Gismondi & Filippo Petroni, 2020. "Insurance Contracts for Hedging Wind Power Uncertainty," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    3. Guglielmo D'Amico & Ada Lika & Filippo Petroni, 2018. "Indexed Markov Chains for financial data: testing for the number of states of the index process," Papers 1802.01540, arXiv.org.
    4. Guglielmo D'Amico & Filippo Petroni, 2020. "A micro-to-macro approach to returns, volumes and waiting times," Papers 2007.06262, arXiv.org.
    5. Guglielmo D’Amico & Ada Lika & Filippo Petroni, 2019. "Change point dynamics for financial data: an indexed Markov chain approach," Annals of Finance, Springer, vol. 15(2), pages 247-266, June.

  4. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.

    Cited by:

    1. Brecht Verbeken & Marie-Anne Guerry, 2021. "Discrete Time Hybrid Semi-Markov Models in Manpower Planning," Mathematics, MDPI, vol. 9(14), pages 1-13, July.

  5. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.

    Cited by:

    1. Guglielmo D'Amico & Filippo Petroni, 2017. "A new approach to the modeling of financial volumes," Papers 1709.05823, arXiv.org.
    2. Guglielmo D'Amico, 2016. "Generalized semi-Markovian dividend discount model: risk and return," Papers 1605.02472, arXiv.org.
    3. Giovanni Masala & Filippo Petroni, 2023. "Drawdown risk measures for asset portfolios with high frequency data," Annals of Finance, Springer, vol. 19(2), pages 265-289, June.
    4. Petroni, Filippo & Serva, Maurizio, 2016. "Observability of market daily volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 838-842.
    5. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    6. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
    7. Guglielmo D'Amico & Ada Lika & Filippo Petroni, 2018. "Indexed Markov Chains for financial data: testing for the number of states of the index process," Papers 1802.01540, arXiv.org.
    8. D’Amico, Guglielmo & Petroni, Filippo, 2023. "ROCOF of higher order for semi-Markov processes," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    9. Guglielmo D’Amico & Giovanni Masala & Filippo Petroni & Robert Adam Sobolewski, 2020. "Managing Wind Power Generation via Indexed Semi-Markov Model and Copula," Energies, MDPI, vol. 13(16), pages 1-21, August.
    10. Guglielmo D'Amico & Montserrat Guillen & Raimondo Manca & Filippo Petroni, 2017. "Multi-state models for evaluating conversion options in life insurance," Papers 1707.01028, arXiv.org.
    11. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2013. "First and second order semi-Markov chains for wind speed modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1194-1201.
    12. Filippo Petroni & Maurizio Serva, 2015. "Observability of Market Daily Volatility," Papers 1503.08032, arXiv.org.
    13. Jo~ao Pedro Rodrigues do Carmo, 2018. "Modeling stock markets through the reconstruction of market processes," Papers 1803.06653, arXiv.org.
    14. Guglielmo D'Amico & Filippo Petroni, 2020. "A micro-to-macro approach to returns, volumes and waiting times," Papers 2007.06262, arXiv.org.
    15. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.
    16. Guglielmo D’Amico & Ada Lika & Filippo Petroni, 2019. "Change point dynamics for financial data: an indexed Markov chain approach," Annals of Finance, Springer, vol. 15(2), pages 247-266, June.
    17. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2017. "Insuring wind energy production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 542-553.
    18. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.

  6. Guglielmo D'Amico & Filippo Petroni, 2011. "A semi-Markov model with memory for price changes," Papers 1109.4259, arXiv.org, revised Dec 2011.

    Cited by:

    1. Guglielmo D'Amico & Filippo Petroni, 2017. "A new approach to the modeling of financial volumes," Papers 1709.05823, arXiv.org.
    2. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.
    3. Guglielmo D'Amico, 2016. "Generalized semi-Markovian dividend discount model: risk and return," Papers 1605.02472, arXiv.org.
    4. Giovanni Masala & Filippo Petroni, 2023. "Drawdown risk measures for asset portfolios with high frequency data," Annals of Finance, Springer, vol. 19(2), pages 265-289, June.
    5. Petroni, Filippo & Serva, Maurizio, 2016. "Observability of market daily volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 838-842.
    6. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    7. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
    8. Guglielmo D'Amico & Ada Lika & Filippo Petroni, 2018. "Indexed Markov Chains for financial data: testing for the number of states of the index process," Papers 1802.01540, arXiv.org.
    9. D’Amico, Guglielmo & Petroni, Filippo, 2023. "ROCOF of higher order for semi-Markov processes," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    10. Guglielmo D’Amico & Giovanni Masala & Filippo Petroni & Robert Adam Sobolewski, 2020. "Managing Wind Power Generation via Indexed Semi-Markov Model and Copula," Energies, MDPI, vol. 13(16), pages 1-21, August.
    11. Guglielmo D'Amico & Montserrat Guillen & Raimondo Manca & Filippo Petroni, 2017. "Multi-state models for evaluating conversion options in life insurance," Papers 1707.01028, arXiv.org.
    12. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2013. "First and second order semi-Markov chains for wind speed modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1194-1201.
    13. Filippo Petroni & Maurizio Serva, 2015. "Observability of Market Daily Volatility," Papers 1503.08032, arXiv.org.
    14. Guglielmo D'Amico & Filippo Petroni, 2020. "A micro-to-macro approach to returns, volumes and waiting times," Papers 2007.06262, arXiv.org.
    15. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.
    16. Guglielmo D’Amico & Ada Lika & Filippo Petroni, 2019. "Change point dynamics for financial data: an indexed Markov chain approach," Annals of Finance, Springer, vol. 15(2), pages 247-266, June.
    17. D׳Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Reliability measures for indexed semi-Markov chains applied to wind energy production," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 170-177.
    18. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2017. "Insuring wind energy production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 542-553.
    19. Riccardo De Blasis, 2023. "Weighted-indexed semi-Markov model: calibration and application to financial modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    20. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.

  7. Guglielmo D'Amico & Filippo Petroni, 2011. "A semi-Markov model for price returns," Papers 1103.6143, arXiv.org.

    Cited by:

    1. Guglielmo D'Amico & Filippo Petroni, 2017. "A new approach to the modeling of financial volumes," Papers 1709.05823, arXiv.org.
    2. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.
    3. Petroni, Filippo & Serva, Maurizio, 2016. "Observability of market daily volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 838-842.
    4. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    5. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
    6. Guglielmo D'Amico & Ada Lika & Filippo Petroni, 2018. "Indexed Markov Chains for financial data: testing for the number of states of the index process," Papers 1802.01540, arXiv.org.
    7. Dmitrii Silvestrov & Raimondo Manca, 2017. "Reward Algorithms for Semi-Markov Processes," Methodology and Computing in Applied Probability, Springer, vol. 19(4), pages 1191-1209, December.
    8. Guglielmo D’Amico & Filippo Petroni & Flavio Prattico, 2015. "Performance Analysis of Second Order Semi-Markov Chains: An Application to Wind Energy Production," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 781-794, September.
    9. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2013. "First and second order semi-Markov chains for wind speed modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1194-1201.
    10. Giner, Javier & Zakamulin, Valeriy, 2023. "A regime-switching model of stock returns with momentum and mean reversion," Economic Modelling, Elsevier, vol. 122(C).
    11. Filippo Petroni & Maurizio Serva, 2015. "Observability of Market Daily Volatility," Papers 1503.08032, arXiv.org.
    12. Guglielmo D'Amico & Filippo Petroni, 2020. "A micro-to-macro approach to returns, volumes and waiting times," Papers 2007.06262, arXiv.org.
    13. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.
    14. Guglielmo D’Amico & Ada Lika & Filippo Petroni, 2019. "Change point dynamics for financial data: an indexed Markov chain approach," Annals of Finance, Springer, vol. 15(2), pages 247-266, June.
    15. D׳Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Reliability measures for indexed semi-Markov chains applied to wind energy production," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 170-177.

  8. Filippo Petroni & Giulia Rotundo, 2007. "Effectiveness of Measures of Performance During Speculative Bubbles," Papers 0709.2423, arXiv.org.

    Cited by:

    1. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2311-2318, September.

  9. M. H. Jensen & A. Johansen & F. Petroni & I. Simonsen, 2004. "Inverse Statistics in the Foreign Exchange Market," Papers cond-mat/0402591, arXiv.org, revised Mar 2004.

    Cited by:

    1. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.
    2. Michele Caraglio & Fulvio Baldovin & Attilio L. Stella, 2021. "How Fast Does the Clock of Finance Run?—A Time-Definition Enforcing Stationarity and Quantifying Overnight Duration," JRFM, MDPI, vol. 14(8), pages 1-15, August.
    3. Zou, Yongjie & Li, Honggang, 2014. "Time spans between price maxima and price minima in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 303-309.
    4. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
    5. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "The stylized facts of prediction markets: Analysis of price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 159-170.
    6. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.
    7. Wei-Xing Zhou & Wei-Kang Yuan, 2004. "Inverse statistics in stock markets: Universality and idiosyncracy," Papers cond-mat/0410225, arXiv.org, revised Oct 2004.

Articles

  1. Paolo Mattana & Filippo Petroni & Stefania Patrizia Sonia Rossi, 2015. "A test for the too-big-to-fail hypothesis for European banks during the financial crisis," Applied Economics, Taylor & Francis Journals, vol. 47(4), pages 319-332, January.

    Cited by:

    1. Ibrahim, Mansor H. & Rizvi, Syed Aun R., 2017. "Do we need bigger Islamic banks? An assessment of bank stability," Journal of Multinational Financial Management, Elsevier, vol. 40(C), pages 77-91.
    2. Boris Cournède & Oliver Denk & Peter Hoeller, 2015. "Finance and Inclusive Growth," OECD Economic Policy Papers 14, OECD Publishing.
    3. De Vos, Ignace & Everaert, Gerdie & Sarafidis, Vasilis, 2021. "A method for evaluating the rank condition for CCE estimators," MPRA Paper 112305, University Library of Munich, Germany, revised 09 Mar 2022.
    4. Fiordelisi, Franco & Minnucci, Federica & Previati, Daniele & Ricci, Ornella, 2020. "Bail-in regulation and stock market reaction," Economics Letters, Elsevier, vol. 186(C).

  2. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.

    Cited by:

    1. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Economic performance indicators of wind energy based on wind speed stochastic modeling," Applied Energy, Elsevier, vol. 154(C), pages 290-297.
    2. Muhammad Yasir & Sitara Afzal & Khalid Latif & Ghulam Mujtaba Chaudhary & Nazish Yameen Malik & Farhan Shahzad & Oh-young Song, 2020. "An Efficient Deep Learning Based Model to Predict Interest Rate Using Twitter Sentiment," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    3. Lazić, Lazar & Pejanović, Goran & Živković, Momčilo & Ilić, Luka, 2014. "Improved wind forecasts for wind power generation using the Eta model and MOS (Model Output Statistics) method," Energy, Elsevier, vol. 73(C), pages 567-574.
    4. Guglielmo D’Amico & Filippo Petroni & Salvatore Vergine, 2022. "Ramp Rate Limitation of Wind Power: An Overview," Energies, MDPI, vol. 15(16), pages 1-15, August.
    5. Riccardo De Blasis & Giovanni Batista Masala & Filippo Petroni, 2021. "A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm," Energies, MDPI, vol. 14(2), pages 1-16, January.
    6. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    7. Guglielmo D’Amico & Fulvio Gismondi & Filippo Petroni, 2020. "Insurance Contracts for Hedging Wind Power Uncertainty," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    8. Kapica, Jacek & Pawlak, Halina & Ścibisz, Marek, 2015. "Carbon dioxide emission reduction by heating poultry houses from renewable energy sources in Central Europe," Agricultural Systems, Elsevier, vol. 139(C), pages 238-249.
    9. Lahmiri, Salim, 2016. "Interest rate next-day variation prediction based on hybrid feedforward neural network, particle swarm optimization, and multiresolution techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 388-396.
    10. Coelho, Vitor N. & Coelho, Igor M. & Coelho, Bruno N. & Reis, Agnaldo J.R. & Enayatifar, Rasul & Souza, Marcone J.F. & Guimarães, Frederico G., 2016. "A self-adaptive evolutionary fuzzy model for load forecasting problems on smart grid environment," Applied Energy, Elsevier, vol. 169(C), pages 567-584.
    11. D׳Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Reliability measures for indexed semi-Markov chains applied to wind energy production," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 170-177.
    12. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2017. "Insuring wind energy production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 542-553.
    13. Çevik, Hasan Hüseyin & Çunkaş, Mehmet & Polat, Kemal, 2019. "A new multistage short-term wind power forecast model using decomposition and artificial intelligence methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).

  3. Guglielmo D'Amico & Filippo Petroni & Flavio Prattico, 2013. "Wind speed modeled as an indexed semi‐Markov process," Environmetrics, John Wiley & Sons, Ltd., vol. 24(6), pages 367-376, September.

    Cited by:

    1. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Economic performance indicators of wind energy based on wind speed stochastic modeling," Applied Energy, Elsevier, vol. 154(C), pages 290-297.
    2. Ambach, Daniel & Schmid, Wolfgang, 2015. "Periodic and long range dependent models for high frequency wind speed data," Energy, Elsevier, vol. 82(C), pages 277-293.
    3. Mohamed Chaouch, 2023. "Probabilistic Wind Speed Forecasting for Wind Turbine Allocation in the Power Grid," Energies, MDPI, vol. 16(22), pages 1-15, November.
    4. Guglielmo D’Amico & Fulvio Gismondi & Filippo Petroni, 2020. "Insurance Contracts for Hedging Wind Power Uncertainty," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    5. Brecht Verbeken & Marie-Anne Guerry, 2021. "Discrete Time Hybrid Semi-Markov Models in Manpower Planning," Mathematics, MDPI, vol. 9(14), pages 1-13, July.
    6. Tang, Jie & Brouste, Alexandre & Tsui, Kwok Leung, 2015. "Some improvements of wind speed Markov chain modeling," Renewable Energy, Elsevier, vol. 81(C), pages 52-56.
    7. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
    8. Guglielmo D’Amico & Giovanni Masala & Filippo Petroni & Robert Adam Sobolewski, 2020. "Managing Wind Power Generation via Indexed Semi-Markov Model and Copula," Energies, MDPI, vol. 13(16), pages 1-21, August.
    9. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.
    10. D׳Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Reliability measures for indexed semi-Markov chains applied to wind energy production," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 170-177.
    11. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2017. "Insuring wind energy production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 542-553.
    12. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.

  4. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2013. "First and second order semi-Markov chains for wind speed modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1194-1201.

    Cited by:

    1. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Economic performance indicators of wind energy based on wind speed stochastic modeling," Applied Energy, Elsevier, vol. 154(C), pages 290-297.
    2. Muhammad Yasir & Sitara Afzal & Khalid Latif & Ghulam Mujtaba Chaudhary & Nazish Yameen Malik & Farhan Shahzad & Oh-young Song, 2020. "An Efficient Deep Learning Based Model to Predict Interest Rate Using Twitter Sentiment," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    3. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.
    4. Maegebier, Alexander, 2013. "Valuation and risk assessment of disability insurance using a discrete time trivariate Markov renewal reward process," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 802-811.
    5. Chia-Hung Wang & Qigen Zhao & Rong Tian, 2023. "Short-Term Wind Power Prediction Based on a Hybrid Markov-Based PSO-BP Neural Network," Energies, MDPI, vol. 16(11), pages 1-24, May.
    6. Wang, Zhongliang & Zhu, Hongyu & Zhang, Dongdong & Goh, Hui Hwang & Dong, Yunxuan & Wu, Thomas, 2023. "Modelling of wind and photovoltaic power output considering dynamic spatio-temporal correlation," Applied Energy, Elsevier, vol. 352(C).
    7. Amanda S. Hering & Karen Kazor & William Kleiber, 2015. "A Markov-Switching Vector Autoregressive Stochastic Wind Generator for Multiple Spatial and Temporal Scales," Resources, MDPI, vol. 4(1), pages 1-23, February.
    8. Tang, Jie & Brouste, Alexandre & Tsui, Kwok Leung, 2015. "Some improvements of wind speed Markov chain modeling," Renewable Energy, Elsevier, vol. 81(C), pages 52-56.
    9. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
    10. Dmitrii Silvestrov & Raimondo Manca, 2017. "Reward Algorithms for Semi-Markov Processes," Methodology and Computing in Applied Probability, Springer, vol. 19(4), pages 1191-1209, December.
    11. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    12. Li, Yanting & Wu, Zhenyu, 2020. "A condition monitoring approach of multi-turbine based on VAR model at farm level," Renewable Energy, Elsevier, vol. 166(C), pages 66-80.
    13. Ma, Jinrui & Fouladirad, Mitra & Grall, Antoine, 2018. "Flexible wind speed generation model: Markov chain with an embedded diffusion process," Energy, Elsevier, vol. 164(C), pages 316-328.
    14. Lahmiri, Salim, 2016. "Interest rate next-day variation prediction based on hybrid feedforward neural network, particle swarm optimization, and multiresolution techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 388-396.
    15. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.
    16. Hui Hwang Goh & Gumeng Peng & Dongdong Zhang & Wei Dai & Tonni Agustiono Kurniawan & Kai Chen Goh & Chin Leei Cham, 2022. "A New Wind Speed Scenario Generation Method Based on Principal Component and R-Vine Copula Theories," Energies, MDPI, vol. 15(7), pages 1-21, April.
    17. Yi, He & Cui, Lirong, 2017. "Distribution and availability for aggregated second-order semi-Markov ternary system with working time omission," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 50-60.
    18. Fang, Chen & Cui, Lirong, 2021. "Reliability evaluation for balanced systems with auto-balancing mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    19. D׳Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Reliability measures for indexed semi-Markov chains applied to wind energy production," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 170-177.
    20. Riccardo De Blasis, 2023. "Weighted-indexed semi-Markov model: calibration and application to financial modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    21. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.
    22. Yi, He & Cui, Lirong & Balakrishnan, Narayanaswamy, 2021. "New reliability indices for first- and second-order discrete-time aggregated semi-Markov systems with an application to TT&C system," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    23. Jónsdóttir, Guðrún Margrét & Milano, Federico, 2019. "Data-based continuous wind speed models with arbitrary probability distribution and autocorrelation," Renewable Energy, Elsevier, vol. 143(C), pages 368-376.

  5. D’Amico, Guglielmo & Petroni, Filippo, 2012. "A semi-Markov model for price returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4867-4876.
    See citations under working paper version above.
  6. Petroni, Filippo & Serva, Maurizio, 2010. "Measures of lexical distance between languages," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(11), pages 2280-2283.

    Cited by:

    1. Ingo E. Isphording & Marc Piopiunik & Núria Rodríguez-Planas, 2015. "Speaking in Numbers: The Effect of Reading Performance on Math Performance among Immigrants," CESifo Working Paper Series 5589, CESifo.
    2. Isphording, Ingo E. & Otten, Sebastian, 2014. "Linguistic barriers in the destination language acquisition of immigrants," Journal of Economic Behavior & Organization, Elsevier, vol. 105(C), pages 30-50.
    3. Ingo Eduard Isphording & Sebastian Otten, 2013. "The Costs of Babylon—Linguistic Distance in Applied Economics," Review of International Economics, Wiley Blackwell, vol. 21(2), pages 354-369, May.
    4. Espitia, Diego & Larralde, Hernán, 2020. "Universal and non-universal text statistics: Clustering coefficient for language identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    5. Gamallo, Pablo & Pichel, José Ramom & Alegria, Iñaki, 2017. "From language identification to language distance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 152-162.
    6. Ibrahim Bousmah & Gilles Grenier & David M. Gray, 2021. "Linguistic Distance, Languages of Work and Wages of Immigrants in Montreal," Journal of Labor Research, Springer, vol. 42(1), pages 1-28, March.
    7. Erkan Gören, 2013. "Economic Effects of Domestic and Neighbouring Countries' Cultural Diversity," ZenTra Working Papers in Transnational Studies 16 / 2013, ZenTra - Center for Transnational Studies, revised Apr 2013.
    8. Lorraine Wong, 2023. "The effect of linguistic proximity on the labour market outcomes of the asylum population," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 609-652, April.
    9. Mehri, Ali & Jamaati, Maryam, 2021. "Statistical metrics for languages classification: A case study of the Bible translations," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).

  7. Ausloos, M. & Petroni, F., 2009. "Statistical dynamics of religion evolutions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4438-4444.

    Cited by:

    1. André Barreira da Silva Rocha, 2012. "Evolutionary Dynamics of Nationalism and Migration," Discussion Papers in Economics 12/11, Division of Economics, School of Business, University of Leicester, revised Jun 2012.
    2. Ausloos, M. & Herteliu, C. & Ileanu, B., 2015. "Breakdown of Benford’s law for birth data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 736-745.
    3. Crokidakis, Nuno, 2024. "Nonequilibrium phase transitions and absorbing states in a model for the dynamics of religious affiliation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    4. Coccia, Mario, 2014. "Socio-cultural origins of the patterns of technological innovation: What is the likely interaction among religious culture, religious plurality and innovation? Towards a theory of socio-cultural drive," Technology in Society, Elsevier, vol. 36(C), pages 13-25.
    5. Jeffs, Rebecca A. & Hayward, John & Roach, Paul A. & Wyburn, John, 2016. "Activist model of political party growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 359-372.
    6. McCartney, Mark & Glass, David H., 2015. "The dynamics of coupled logistic social groups," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 141-154.
    7. Yuri Biondi & Pierpaolo Giannoccolo & Serge Galam, 2011. "The formation of share market prices under heterogeneous beliefs and common knowledge," Papers 1105.3228, arXiv.org.
    8. McCartney, Mark & Glass, David H., 2015. "A three-state dynamical model for religious affiliation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 145-152.
    9. Doménech-Carbó, Antonio, 2019. "Rise and fall of historic tram networks: Logistic approximation and discontinuous events," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 315-323.
    10. Mir, T.A., 2012. "The law of the leading digits and the world religions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 792-798.
    11. Mir, T.A., 2014. "The Benford law behavior of the religious activity data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 1-9.

  8. Petroni, Filippo & Rotundo, Giulia, 2008. "Effectiveness of measures of performance during speculative bubbles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3942-3948.
    See citations under working paper version above.
  9. Petroni, Filippo & Ausloos, Marcel, 2008. "High frequency intrinsic modes in El Niño/Southern Oscillation Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5246-5254.

    Cited by:

    1. Samuel T. Ogunjo, 2023. "The impact of the 2007–2008 global financial crisis on the multifractality of the Nigerian Stock Exchange," SN Business & Economics, Springer, vol. 3(1), pages 1-17, January.
    2. Huang, Xu & Maçaira, Paula Medina & Hassani, Hossein & Cyrino Oliveira, Fernando Luiz & Dhesi, Gurjeet, 2019. "Hydrological natural inflow and climate variables: Time and frequency causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 480-495.

  10. Ausloos, M. & Petroni, F., 2007. "Tsallis non-extensive statistical mechanics of El Niño southern oscillation index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 721-736.

    Cited by:

    1. Hoyos, Isabel & Rodríguez, Boris Anghelo, 2020. "Drawing the complexity of Colombian climate from non-extensive extreme behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    2. Chan-juan Li & Yuan-qing Chai & Lin-sheng Yang & Hai-rong Li, 2016. "Spatio-temporal distribution of flood disasters and analysis of influencing factors in Africa," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(1), pages 721-731, May.
    3. Petroni, Filippo & Ausloos, Marcel, 2008. "High frequency intrinsic modes in El Niño/Southern Oscillation Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5246-5254.
    4. Ferri, Gustavo L. & Figliola, Alejandra & Rosso, Osvaldo A., 2012. "Tsallis’ statistics in the variability of El Niño/Southern Oscillation during the Holocene epoch," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2154-2162.
    5. Ferri, G.L. & Reynoso Savio, M.F. & Plastino, A., 2010. "Tsallis’ q-triplet and the ozone layer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1829-1833.

  11. Petroni, F. & Ausloos, M. & Rotundo, G., 2007. "Generating synthetic time series from Bak–Sneppen co-evolution model mixtures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 359-367.

    Cited by:

    1. Rotundo, G. & Ausloos, M. & Herteliu, C. & Ileanu, B., 2015. "Hurst exponent of very long birth time series in XX century Romania. Social and religious aspects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 109-117.
    2. Marcel Ausloos, 2014. "A biased view of a few possible components when reflecting on the present decade financial and economic crisis," Papers 1412.0127, arXiv.org.

  12. Serva, M. & Fulco, U.L. & Gléria, I.M. & Lyra, M.L. & Petroni, F. & Viswanathan, G.M., 2006. "A Markov model of financial returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 393-403.

    Cited by:

    1. Silva, L.B.M. & Vermelho, M.V.D. & Lyra, M.L. & Viswanathan, G.M., 2009. "Multifractal detrended fluctuation analysis of analog random multiplicative processes," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2806-2811.
    2. Lu, Changxiang & Ye, Yong & Fang, Yongjun & Fang, Jiaqi, 2023. "An optimal control theory approach for freight structure path evolution post-COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    3. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2013. "First and second order semi-Markov chains for wind speed modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1194-1201.

  13. Petroni, Filippo & Serva, Maurizio, 2004. "Real prices from spot foreign exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 194-197.

    Cited by:

    1. Sato, Aki-Hiro, 2007. "Frequency analysis of tick quotes on the foreign exchange market and agent-based modeling: A spectral distance approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 258-270.

  14. Jensen, M.H & Johansen, A & Petroni, F & Simonsen, I, 2004. "Inverse statistics in the foreign exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(4), pages 678-684.
    See citations under working paper version above.
  15. F. Petroni & M. Serva, 2003. "Spot foreign exchange market and time series," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 34(4), pages 495-500, August.

    Cited by:

    1. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551, arXiv.org, revised Jun 2012.
    2. Guglielmo D'Amico & Filippo Petroni, 2011. "A semi-Markov model with memory for price changes," Papers 1109.4259, arXiv.org, revised Dec 2011.
    3. G. D'Amico & F. Petroni & F. Prattico, 2013. "Semi-Markov Models in High Frequency Finance: A Review," Papers 1312.3894, arXiv.org.
    4. Guglielmo D'Amico & Filippo Petroni, 2020. "A micro-to-macro approach to returns, volumes and waiting times," Papers 2007.06262, arXiv.org.
    5. Guglielmo D'Amico & Filippo Petroni, 2013. "Multivariate high-frequency financial data via semi-Markov processes," Papers 1305.0436, arXiv.org.

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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 6 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-MST: Market Microstructure (4) 2011-04-09 2011-10-01 2013-05-05 2013-12-20
  2. NEP-ETS: Econometric Time Series (2) 2012-05-22 2013-05-05
  3. NEP-CMP: Computational Economics (1) 2012-05-22
  4. NEP-ECM: Econometrics (1) 2012-05-22
  5. NEP-FMK: Financial Markets (1) 2012-05-22
  6. NEP-ORE: Operations Research (1) 2013-12-20
  7. NEP-RMG: Risk Management (1) 2015-03-22

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