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Luca Vincenzo Ballestra

Personal Details

First Name:Luca Vincenzo
Middle Name:
Last Name:Ballestra
Suffix:
RePEc Short-ID:pba2099
[This author has chosen not to make the email address public]

Affiliation

Dipartimento di Scienze Statistiche "Paolo Fortunati"
Alma Mater Studiorum - Università di Bologna

Bologna, Italy
http://www.stat.unibo.it/
RePEc:edi:dsbolit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Luca Vincenzo Ballestra & Christian Tezza, 2025. "A multi-factor model for improved commodity pricing: Calibration and an application to the oil market," Papers 2501.15596, arXiv.org.
  2. Luca Vincenzo Ballestra & Enzo D'Innocenzo & Christian Tezza, 2024. "A GARCH model with two volatility components and two driving factors," Papers 2410.14585, arXiv.org.
  3. Luca Vincenzo Ballestra & Enzo D'Innocenzo & Christian Tezza, 2024. "GARCH option valuation with long-run and short-run volatility components: A novel framework ensuring positive variance," Papers 2410.14513, arXiv.org.
  4. Foad Shokrollahi & Davood Ahmadian & Luca Vincenzo Ballestra, 2021. "Actuarial strategy for pricing Asian options under a mixed fractional Brownian motion with jumps," Papers 2105.06999, arXiv.org.

Articles

  1. Luca Vincenzo Ballestra & Riccardo De Blasis & Graziella Pacelli, 2025. "Multivariate GARCH models with spherical parameterizations: an oil price application," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-20, December.
  2. Luca Vincenzo Ballestra & Enzo D’Innocenzo & Andrea Guizzardi, 2024. "Score-Driven Modeling with Jumps: An Application to S&P500 Returns and Options," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 375-406.
  3. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Mazzucchelli, Lorenzo, 2024. "Integrating narrow and wide framing disposition effect: A novel approach incorporating perceived risk and realized asset performance," Journal of Economic Behavior & Organization, Elsevier, vol. 220(C), pages 422-432.
  4. Andrea Guizzardi & Luca Vincenzo Ballestra & Enzo D’Innocenzo, 2024. "Reverse engineering the last-minute on-line pricing practices: an application to hotels," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 943-971, July.
  5. Rahimi, Vaz'he & Ahmadian, Davood & Ballestra, Luca Vincenzo, 2024. "Construction and mean-square stability analysis of a new family of stochastic Runge-Kutta methods," Applied Mathematics and Computation, Elsevier, vol. 470(C).
  6. Ballestra, Luca Vincenzo & D’Innocenzo, Enzo & Guizzardi, Andrea, 2024. "A new bivariate approach for modeling the interaction between stock volatility and interest rate: An application to S&P500 returns and options," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1185-1194.
  7. Gibellato, Simone & Ballestra, Luca Vincenzo & Fiano, Fabio & Graziano, Domenico & Luca Gregori, Gian, 2023. "The impact of education on the Energy Trilemma Index: A sustainable innovativeness perspective for resilient energy systems," Applied Energy, Elsevier, vol. 330(PB).
  8. Guizzardi, Andrea & Ballestra, Luca Vincenzo & D'Innocenzo, Enzo, 2022. "Hotel dynamic pricing, stochastic demand and covid-19," Annals of Tourism Research, Elsevier, vol. 97(C).
  9. Luca Vincenzo Ballestra, 2021. "Enhancing finite difference approximations for double barrier options: mesh optimization and repeated Richardson extrapolation," Computational Management Science, Springer, vol. 18(2), pages 239-263, June.
  10. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2020. "Modeling CDS spreads: A comparison of some hybrid approaches," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 107-124.
  11. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.
  12. Alessandro Andreoli & Luca Vincenzo Ballestra & Graziella Pacelli, 2018. "Pricing Credit Default Swaps Under Multifactor Reduced-Form Models: A Differential Quadrature Approach," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 379-406, March.
  13. Luca Vincenzo Ballestra, 2018. "Fast and accurate calculation of American option prices," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 399-426, November.
  14. Onali, Enrico & Ginesti, Gianluca & Ballestra, Luca Vincenzo, 2017. "Investor reaction to IFRS for financial instruments in Europe: The role of firm-specific factors," Finance Research Letters, Elsevier, vol. 21(C), pages 72-77.
  15. Luca Vincenzo Ballestra & Graziella Pacelli & Davide Radi, 2017. "Computing the survival probability in the Madan–Unal credit risk model: application to the CDS market," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 299-313, February.
  16. Luca Vincenzo Ballestra & Graziella Pacelli & Davide Radi, 2017. "Valuing investment projects under interest rate risk: empirical evidence from European firms," Applied Economics, Taylor & Francis Journals, vol. 49(56), pages 5662-5672, December.
  17. Ballestra, Luca Vincenzo & Cecere, Liliana, 2016. "A numerical method to estimate the parameters of the CEV model implied by American option prices: Evidence from NYSE," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 100-106.
  18. Luca Vincenzo Ballestra & Graziella Pacelli & Davide Radi, 2016. "A Note On Fergusson And Platen: “Application Of Maximum Likelihood Estimation To Stochastic Short Rate Models”," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-7, December.
  19. Ballestra, Luca Vincenzo, 2016. "The spatial AK model and the Pontryagin maximum principle," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 87-94.
  20. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2016. "A very efficient approach to compute the first-passage probability density function in a time-changed Brownian model: Applications in finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 330-344.
  21. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2016. "A very efficient approach for pricing barrier options on an underlying described by the mixed fractional Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 240-248.
  22. Alessandro Andreoli & Luca Vincenzo Ballestra & Graziella Pacelli, 2016. "From insurance risk to credit portfolio management: a new approach to pricing CDOs," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1495-1510, October.
  23. Ballestra, Luca Vincenzo & Cecere, Liliana, 2015. "Pricing American options under the constant elasticity of variance model: An extension of the method by Barone-Adesi and Whaley," Finance Research Letters, Elsevier, vol. 14(C), pages 45-55.
  24. Rad, Jamal Amani & Parand, Kourosh & Ballestra, Luca Vincenzo, 2015. "Pricing European and American options by radial basis point interpolation," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 363-377.
  25. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2014. "Valuing risky debt: A new model combining structural information with the reduced-form approach," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 261-271.
  26. Luca Vincenzo Ballestra & Luca Guerrini & Graziella Pacelli, 2013. "Stability Switches and Hopf Bifurcation in a Kaleckian Model of Business Cycle," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-8, August.
  27. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2013. "Pricing European and American options with two stochastic factors: A highly efficient radial basis function approach," Journal of Economic Dynamics and Control, Elsevier, vol. 37(6), pages 1142-1167.
  28. Ballestra, Luca Vincenzo & Ottaviani, Massimiliano & Pacelli, Graziella, 2012. "An operator splitting harmonic differential quadrature approach to solve Young’s model for life insurance risk," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 442-448.
  29. Luca Vincenzo Ballestra & Graziella Pacelli, 2011. "The constant elasticity of variance model: calibration, test and evidence from the Italian equity market," Applied Financial Economics, Taylor & Francis Journals, vol. 21(20), pages 1479-1487.
  30. Pacelli, Graziella & Ballestra, Luca Vincenzo, 2010. "On a variational formulation used in credit risk modeling," Finance Research Letters, Elsevier, vol. 7(2), pages 110-118, June.
  31. Luca Vincenzo Ballestra & Graziella Pacelli, 2009. "A Numerical Method to Price Defaultable Bonds Based on the Madan and Unal Credit Risk Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(1), pages 17-36.
  32. Luca Vincenzo Ballestra & Roberto Ferri & Graziella Pacelli, 2007. "The Heston Stochastic Volatility Model For Single Assets And For Asset Portfolios: Parameter Estimation And An Application To The Italian Financial Market," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 1(2), pages 11-23.
  33. Ballestra, Luca Vincenzo & Pacelli, Graziella & Zirilli, Francesco, 2007. "A numerical method to price exotic path-dependent options on an underlying described by the Heston stochastic volatility model," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3420-3437, November.

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

    Sorry, no citations of working papers recorded.

Articles

  1. Luca Vincenzo Ballestra & Enzo D’Innocenzo & Andrea Guizzardi, 2024. "Score-Driven Modeling with Jumps: An Application to S&P500 Returns and Options," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 375-406.

    Cited by:

    1. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Papers 2408.02391, arXiv.org, revised Sep 2024.

  2. Ballestra, Luca Vincenzo & D’Innocenzo, Enzo & Guizzardi, Andrea, 2024. "A new bivariate approach for modeling the interaction between stock volatility and interest rate: An application to S&P500 returns and options," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1185-1194.

    Cited by:

    1. Luca Vincenzo Ballestra & Enzo D'Innocenzo & Christian Tezza, 2024. "GARCH option valuation with long-run and short-run volatility components: A novel framework ensuring positive variance," Papers 2410.14513, arXiv.org.
    2. Luca Vincenzo Ballestra & Enzo D'Innocenzo & Christian Tezza, 2024. "A GARCH model with two volatility components and two driving factors," Papers 2410.14585, arXiv.org.

  3. Gibellato, Simone & Ballestra, Luca Vincenzo & Fiano, Fabio & Graziano, Domenico & Luca Gregori, Gian, 2023. "The impact of education on the Energy Trilemma Index: A sustainable innovativeness perspective for resilient energy systems," Applied Energy, Elsevier, vol. 330(PB).

    Cited by:

    1. Yang, Zhaofu & Liu, Hong & Yuan, Yongna & Li, Muhua, 2024. "Can renewable energy development facilitate China's sustainable energy transition? Perspective from Energy Trilemma," Energy, Elsevier, vol. 304(C).
    2. Lauren E. Natividad & Pablo Benalcazar, 2023. "Hybrid Renewable Energy Systems for Sustainable Rural Development: Perspectives and Challenges in Energy Systems Modeling," Energies, MDPI, vol. 16(3), pages 1-15, January.
    3. Oluwafemi Awolesi & Corinne A. Salter & Margaret Reams, 2024. "A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions," Energies, MDPI, vol. 17(14), pages 1-17, July.
    4. Zhang, Guidong & Wang, Jianlong & Liu, Yong, 2024. "“Carbon” suppresses “energy” - How does carbon emission right trading policy alleviate the energy trilemma?," Energy, Elsevier, vol. 307(C).
    5. Fang, Guochang & Zhou, Huixin & Meng, Aoxiang & Tian, Lixin, 2024. "How to crack the impossible triangle of new energy coupled system——Evidence from China," Applied Energy, Elsevier, vol. 374(C).
    6. Arkadiusz Piwowar & Maciej Dzikuć, 2024. "The Economic and Social Dimension of Energy Transformation in the Face of the Energy Crisis: The Case of Poland," Energies, MDPI, vol. 17(2), pages 1-12, January.

  4. Guizzardi, Andrea & Ballestra, Luca Vincenzo & D'Innocenzo, Enzo, 2022. "Hotel dynamic pricing, stochastic demand and covid-19," Annals of Tourism Research, Elsevier, vol. 97(C).

    Cited by:

    1. Maria Giovanna Brandano & Alessandra Faggian & Adriana C Pinate, 2024. "The impact of COVID-19 on the tourism sector in Italy: A regional spatial perspective," Tourism Economics, , vol. 30(8), pages 2181-2202, December.

  5. Luca Vincenzo Ballestra, 2021. "Enhancing finite difference approximations for double barrier options: mesh optimization and repeated Richardson extrapolation," Computational Management Science, Springer, vol. 18(2), pages 239-263, June.

    Cited by:

    1. Oleg Kudryavtsev, 2024. "A simplified Wiener–Hopf factorization method for pricing double barrier options under Lévy processes," Computational Management Science, Springer, vol. 21(1), pages 1-30, June.

  6. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2020. "Modeling CDS spreads: A comparison of some hybrid approaches," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 107-124.

    Cited by:

    1. Livieri, Giulia & Radi, Davide & Smaniotto, Elia, 2024. "Pricing transition risk with a jump-diffusion credit risk model: evidences from the CDS market," LSE Research Online Documents on Economics 123650, London School of Economics and Political Science, LSE Library.
    2. Giulia Livieri & Davide Radi & Elia Smaniotto, 2023. "Pricing Transition Risk with a Jump-Diffusion Credit Risk Model: Evidences from the CDS market," Papers 2303.12483, arXiv.org.
    3. Davide Radi & Vu Phuong Hoang & Gabriele Torri & Hana Dvořáčková, 2021. "A revised version of the Cathcart & El-Jahel model and its application to CDS market," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 669-705, December.
    4. Murphy, Austin & Headley, Adrian, 2022. "An empirical evaluation of alternative fundamental models of credit spreads," International Review of Financial Analysis, Elsevier, vol. 81(C).

  7. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.

    Cited by:

    1. Onur Enginar & Kazim Baris Atici, 2022. "Optimal forecast error as an unbiased estimator of abnormal return: A proposition," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 158-166, January.
    2. Byung Yeon Kim & Heejoon Han, 2022. "Multi-Step-Ahead Forecasting of the CBOE Volatility Index in a Data-Rich Environment: Application of Random Forest with Boruta Algorithm," Korean Economic Review, Korean Economic Association, vol. 38, pages 541-569.
    3. Xu Gong & Keqin Guan & Qiyang Chen, 2022. "The role of textual analysis in oil futures price forecasting based on machine learning approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1987-2017, October.
    4. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
    5. Ghosh, Indranil & Chaudhuri, Tamal Datta & Alfaro-Cortés, Esteban & Gámez, Matías & García, Noelia, 2022. "A hybrid approach to forecasting futures prices with simultaneous consideration of optimality in ensemble feature selection and advanced artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    6. Li, Jianping & Li, Guowen & Liu, Mingxi & Zhu, Xiaoqian & Wei, Lu, 2022. "A novel text-based framework for forecasting agricultural futures using massive online news headlines," International Journal of Forecasting, Elsevier, vol. 38(1), pages 35-50.
    7. Jonas Freibauer & Silja Grawert, 2022. "Testing of a Volatility-Based Trading Strategy Using Behavioral Modified Asset Allocation," JRFM, MDPI, vol. 15(10), pages 1-20, September.
    8. Xu Gong & Mengjie Li & Keqin Guan & Chuanwang Sun, 2023. "Climate change attention and carbon futures return prediction," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1261-1288, September.
    9. Yun‐Huan Lee & Tzu‐Hsiang Liao & Hsiu‐Chuan Lee, 2022. "Overnight returns of industry exchange‐traded funds, investor sentiment, and futures market returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1114-1134, June.

  8. Luca Vincenzo Ballestra, 2018. "Fast and accurate calculation of American option prices," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 399-426, November.

    Cited by:

    1. Chinonso Nwankwo & Nneka Umeorah & Tony Ware & Weizhong Dai, 2022. "Deep learning and American options via free boundary framework," Papers 2211.11803, arXiv.org, revised Dec 2022.
    2. Cristina Viegas & José Azevedo-Pereira, 2020. "A Quasi-Closed-Form Solution for the Valuation of American Put Options," IJFS, MDPI, vol. 8(4), pages 1-16, October.
    3. Chinonso Nwankwo & Weizhong Dai, 2020. "An Adaptive and Explicit Fourth Order Runge-Kutta-Fehlberg Method Coupled with Compact Finite Differencing for Pricing American Put Options," Papers 2007.04408, arXiv.org, revised Jul 2021.
    4. Kirkby, J. Lars & Nguyen, Dang H. & Nguyen, Duy, 2020. "A general continuous time Markov chain approximation for multi-asset option pricing with systems of correlated diffusions," Applied Mathematics and Computation, Elsevier, vol. 386(C).

  9. Onali, Enrico & Ginesti, Gianluca & Ballestra, Luca Vincenzo, 2017. "Investor reaction to IFRS for financial instruments in Europe: The role of firm-specific factors," Finance Research Letters, Elsevier, vol. 21(C), pages 72-77.

    Cited by:

    1. Onali, Enrico & Ginesti, Gianluca & Cardillo, Giovanni & Torluccio, Giuseppe, 2024. "Market reaction to the expected loss model in banks," Journal of Financial Stability, Elsevier, vol. 74(C).
    2. Laura Bini & Francesco Giunta & Rebecca Miccini & Lorenzo Simoni, 2023. "Corporate governance quality and non-financial KPI disclosure comparability: UK evidence," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(1), pages 43-74, March.
    3. Julius Gaël Tchatchou Tchaptchet & Olivier Colot, 2019. "Goodwill’s Accounting Practices in Belgium and Compliance with IAS 36 Required Disclosures," International Business Research, Canadian Center of Science and Education, vol. 12(3), pages 139-152, March.
    4. Salazar, Yadira & Merello, Paloma & Zorio-Grima, Ana, 2023. "IFRS 9, banking risk and COVID-19: Evidence from Europe," Finance Research Letters, Elsevier, vol. 56(C).
    5. Mojca Gornjak, 2019. "IFRS 9: Initiator of Changes in Management Accounting Processes," Management, University of Primorska, Faculty of Management Koper, vol. 14(2), pages 95-116.

  10. Luca Vincenzo Ballestra & Graziella Pacelli & Davide Radi, 2017. "Computing the survival probability in the Madan–Unal credit risk model: application to the CDS market," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 299-313, February.

    Cited by:

    1. Giulia Livieri & Davide Radi & Elia Smaniotto, 2023. "Pricing Transition Risk with a Jump-Diffusion Credit Risk Model: Evidences from the CDS market," Papers 2303.12483, arXiv.org.
    2. Davide Radi & Vu Phuong Hoang & Gabriele Torri & Hana Dvořáčková, 2021. "A revised version of the Cathcart & El-Jahel model and its application to CDS market," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 669-705, December.
    3. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2020. "Modeling CDS spreads: A comparison of some hybrid approaches," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 107-124.
    4. Feng-Hui Yu & Jiejun Lu & Jia-Wen Gu & Wai-Ki Ching, 2019. "Modeling Credit Risk with Hidden Markov Default Intensity," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 1213-1229, October.

  11. Ballestra, Luca Vincenzo & Cecere, Liliana, 2016. "A numerical method to estimate the parameters of the CEV model implied by American option prices: Evidence from NYSE," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 100-106.

    Cited by:

    1. Malik Zaka Ullah, 2019. "Numerical Solution of Heston-Hull-White Three-Dimensional PDE with a High Order FD Scheme," Mathematics, MDPI, vol. 7(8), pages 1-13, August.
    2. Al–Zhour, Zeyad & Barfeie, Mahdiar & Soleymani, Fazlollah & Tohidi, Emran, 2019. "A computational method to price with transaction costs under the nonlinear Black–Scholes model," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 291-301.
    3. Duarte Queirós, Sílvio M. & Anteneodo, Celia, 2016. "Complexity in quantitative finance and economics," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 1-2.
    4. Lahmiri, Salim & Bekiros, Stelios & Salvi, Antonio, 2018. "Long-range memory, distributional variation and randomness of bitcoin volatility," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 43-48.
    5. Kim, See-Woo & Kim, Jeong-Hoon, 2018. "Analytic solutions for variance swaps with double-mean-reverting volatility," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 130-144.

  12. Luca Vincenzo Ballestra & Graziella Pacelli & Davide Radi, 2016. "A Note On Fergusson And Platen: “Application Of Maximum Likelihood Estimation To Stochastic Short Rate Models”," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-7, December.

    Cited by:

    1. Luca Vincenzo Ballestra & Graziella Pacelli & Davide Radi, 2017. "Valuing investment projects under interest rate risk: empirical evidence from European firms," Applied Economics, Taylor & Francis Journals, vol. 49(56), pages 5662-5672, December.
    2. Davide Radi & Vu Phuong Hoang & Gabriele Torri & Hana Dvořáčková, 2021. "A revised version of the Cathcart & El-Jahel model and its application to CDS market," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 669-705, December.
    3. Valerii Maltsev & Michael Pokojovy, 2021. "Applying Heath-Jarrow-Morton Model to Forecasting the US Treasury Daily Yield Curve Rates," Mathematics, MDPI, vol. 9(2), pages 1-25, January.

  13. Ballestra, Luca Vincenzo, 2016. "The spatial AK model and the Pontryagin maximum principle," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 87-94.

    Cited by:

    1. Emmanuelle Augeraud-Veron & Raouf Boucekkine & Fausto Gozzi & Alain Vendetti & Benteng Zou, 2024. "Fifty years of mathematical growth theory: Classical topics and new trends," DEM Discussion Paper Series 24-02, Department of Economics at the University of Luxembourg.
    2. Spyridon Tsangaris & Anastasios Xepapadeas & Athanasios Yannacopoulos, 2022. "Spatial externalities, R&D spillovers, and endogenous technological change," DEOS Working Papers 2225, Athens University of Economics and Business.
    3. Paulo Brito, 2004. "The Dynamics of Growth and Distribution in a Spatially Heterogeneous World," Working Papers Department of Economics 2004/14, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    4. Raouf Boucekkine & Giorgio Fabbri & Salvatore Federico & Fausto Gozzi, 2019. "A Spatiotemporal Framework for the Analytical Study of Optimal Growth Under Transboundary Pollution," Department of Economics University of Siena 813, Department of Economics, University of Siena.
    5. Emmanuelle Augeraud-Véron & Raouf Boucekkine & Vladimir Veliov, 2019. "Distributed Optimal Control Models in Environmental Economics: A Review," AMSE Working Papers 1902, Aix-Marseille School of Economics, France.
    6. Xepapadeas, Anastasios & Yannacopoulos, Athanasios N., 2023. "Spatial growth theory: Optimality and spatial heterogeneity," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).

  14. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2016. "A very efficient approach to compute the first-passage probability density function in a time-changed Brownian model: Applications in finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 330-344.

    Cited by:

    1. Zhang, Wei-Guo & Li, Zhe & Liu, Yong-Jun, 2018. "Analytical pricing of geometric Asian power options on an underlying driven by a mixed fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 402-418.

  15. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2016. "A very efficient approach for pricing barrier options on an underlying described by the mixed fractional Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 240-248.

    Cited by:

    1. Shokrollahi, F. & Ahmadian, D. & Ballestra, L.V., 2024. "Pricing Asian options under the mixed fractional Brownian motion with jumps," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 226(C), pages 172-183.
    2. Farshid Mehrdoust & Ali Reza Najafi, 2018. "Pricing European Options under Fractional Black–Scholes Model with a Weak Payoff Function," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 685-706, August.
    3. Foad Shokrollahi & Davood Ahmadian & Luca Vincenzo Ballestra, 2021. "Actuarial strategy for pricing Asian options under a mixed fractional Brownian motion with jumps," Papers 2105.06999, arXiv.org.
    4. Zhang, Wei-Guo & Li, Zhe & Liu, Yong-Jun, 2018. "Analytical pricing of geometric Asian power options on an underlying driven by a mixed fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 402-418.
    5. Yang, Xiangfeng & Zhang, Zhiqiang & Gao, Xin, 2019. "Asian-barrier option pricing formulas of uncertain financial market," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 79-86.
    6. Ahmadian, D. & Ballestra, L.V., 2020. "Pricing geometric Asian rainbow options under the mixed fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    7. Wei-Guo Zhang & Zhe Li & Yong-Jun Liu & Yue Zhang, 2021. "Pricing European Option Under Fuzzy Mixed Fractional Brownian Motion Model with Jumps," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 483-515, August.
    8. Zeng, Yue & Zhang, Yao-jia & Huang, Nan-jing, 2024. "A stochastic fractional differential variational inequality with Lévy jump and its application," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    9. Marianito R. Rodrigo, 2020. "Pricing of Barrier Options on Underlying Assets with Jump-Diffusion Dynamics: A Mellin Transform Approach," Mathematics, MDPI, vol. 8(8), pages 1-20, August.

  16. Alessandro Andreoli & Luca Vincenzo Ballestra & Graziella Pacelli, 2016. "From insurance risk to credit portfolio management: a new approach to pricing CDOs," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1495-1510, October.

    Cited by:

    1. Dan Luo & Dragon Yongjun Tang & Sarah Qian Wang, 2018. "Model specification and collateralized debt obligation (mis)pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1284-1312, November.

  17. Ballestra, Luca Vincenzo & Cecere, Liliana, 2015. "Pricing American options under the constant elasticity of variance model: An extension of the method by Barone-Adesi and Whaley," Finance Research Letters, Elsevier, vol. 14(C), pages 45-55.

    Cited by:

    1. Liu, Yanchu & Cui, Zhenyu & Zhang, Ning, 2016. "Integral representation of vega for American put options," Finance Research Letters, Elsevier, vol. 19(C), pages 204-208.
    2. Chinonso Nwankwo & Weizhong Dai & Tony Ware, 2023. "Enhancing accuracy for solving American CEV model with high-order compact scheme and adaptive time stepping," Papers 2309.03984, arXiv.org, revised Sep 2023.
    3. Shi, Guangping & Liu, Xiaoxing & Tang, Pan, 2016. "Pricing options under the non-affine stochastic volatility models: An extension of the high-order compact numerical scheme," Finance Research Letters, Elsevier, vol. 16(C), pages 220-229.
    4. Jia‐Hau Guo & Lung‐Fu Chang, 2020. "Repeated Richardson extrapolation and static hedging of barrier options under the CEV model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 974-988, June.
    5. Aricson Cruz & José Carlos Dias, 2020. "Valuing American-style options under the CEV model: an integral representation based method," Review of Derivatives Research, Springer, vol. 23(1), pages 63-83, April.
    6. Oleg L. Kritski & Vladimir F. Zalmezh, 2017. "Asymptotics for Greeks under the constant elasticity of variance model," Papers 1707.04149, arXiv.org, revised Jul 2017.

  18. Rad, Jamal Amani & Parand, Kourosh & Ballestra, Luca Vincenzo, 2015. "Pricing European and American options by radial basis point interpolation," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 363-377.

    Cited by:

    1. Li, Shuling & Li, Xiaolin, 2016. "Radial basis functions and level set method for image segmentation using partial differential equation," Applied Mathematics and Computation, Elsevier, vol. 286(C), pages 29-40.
    2. Luca Vincenzo Ballestra, 2018. "Fast and accurate calculation of American option prices," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 399-426, November.
    3. Seda Gulen & Catalin Popescu & Murat Sari, 2019. "A New Approach for the Black–Scholes Model with Linear and Nonlinear Volatilities," Mathematics, MDPI, vol. 7(8), pages 1-14, August.
    4. Gong, Pu & Zou, Dong & Wang, Jiayue, 2018. "Pricing and simulation for real estate index options: Radial basis point interpolation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 177-188.
    5. Hajimohammadi, Zeinab & Parand, Kourosh, 2021. "Numerical learning approximation of time-fractional sub diffusion model on a semi-infinite domain," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    6. Kirkby, J. Lars & Nguyen, Dang H. & Nguyen, Duy, 2020. "A general continuous time Markov chain approximation for multi-asset option pricing with systems of correlated diffusions," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    7. Xubiao He & Pu Gong, 2020. "A Radial Basis Function-Generated Finite Difference Method to Evaluate Real Estate Index Options," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 999-1019, March.
    8. A. Golbabai & E. Mohebianfar, 2017. "A New Stable Local Radial Basis Function Approach for Option Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 49(2), pages 271-288, February.
    9. Shirzadi, Mohammad & Rostami, Mohammadreza & Dehghan, Mehdi & Li, Xiaolin, 2023. "American options pricing under regime-switching jump-diffusion models with meshfree finite point method," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    10. Somayeh Abdi-Mazraeh & Ali Khani & Safar Irandoust-Pakchin, 2020. "Multiple Shooting Method for Solving Black–Scholes Equation," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 723-746, December.
    11. Gong, Pu & Dai, Jun, 2017. "Pricing real estate index options under stochastic interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 309-323.

  19. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2014. "Valuing risky debt: A new model combining structural information with the reduced-form approach," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 261-271.

    Cited by:

    1. Mario Mustilli & Francesco Campanella & Eugenio D’Angelo, 2017. "Basel III and Credit Crunch: An Empirical Test with Focus on Europe," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(3), pages 1-3.
    2. Liu, Jing, 2018. "LLN-type approximations for large portfolio losses," Insurance: Mathematics and Economics, Elsevier, vol. 81(C), pages 71-77.
    3. Hyong-Chol O. & Jong-Chol Kim & Il-Gwang Jon, 2017. "Numerical analysis for a unified 2 factor model of structural and reduced form types for corporate bonds with fixed discrete coupon," Papers 1709.06517, arXiv.org, revised Aug 2018.
    4. Cantia, Catalin & Tunaru, Radu, 2017. "A factor model for joint default probabilities. Pricing of CDS, index swaps and index tranches," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 21-35.
    5. Hainaut, Donatien, 2019. "Credit risk modelling with fractional self-excited processes," LIDAM Discussion Papers ISBA 2019027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Hyong Chol O & Tae Song Kim, 2020. "Analysis on the Pricing model for a Discrete Coupon Bond with Early redemption provision by the Structural Approach," Papers 2007.01511, arXiv.org.
    7. Feng-Hui Yu & Jiejun Lu & Jia-Wen Gu & Wai-Ki Ching, 2019. "Modeling Credit Risk with Hidden Markov Default Intensity," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 1213-1229, October.
    8. Hainaut, Donatien, 2020. "Credit risk modelling with fractional self-excited processes," LIDAM Discussion Papers ISBA 2020002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Qiu, Ming & Jin, Zhuo & Li, Shuanming, 2023. "Optimal risk sharing and dividend strategies under default contagion: A semi-analytical approach," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 1-23.

  20. Luca Vincenzo Ballestra & Luca Guerrini & Graziella Pacelli, 2013. "Stability Switches and Hopf Bifurcation in a Kaleckian Model of Business Cycle," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-8, August.

    Cited by:

    1. De Cesare, Luigi & Sportelli, Mario, 2022. "A non-linear approach to Kalecki’s investment cycle," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 57-70.

  21. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2013. "Pricing European and American options with two stochastic factors: A highly efficient radial basis function approach," Journal of Economic Dynamics and Control, Elsevier, vol. 37(6), pages 1142-1167.

    Cited by:

    1. Sinem Kozp{i}nar & Murat Uzunca & Bulent Karasozen, 2016. "Pricing European and American Options under Heston Model using Discontinuous Galerkin Finite Elements," Papers 1606.08381, arXiv.org, revised Mar 2020.
    2. Jamal Amani Rad & Kourosh Parand, 2014. "Numerical pricing of American options under two stochastic factor models with jumps using a meshless local Petrov-Galerkin method," Papers 1412.6064, arXiv.org.
    3. Reza Mollapourasl & Ali Fereshtian & Michèle Vanmaele, 2019. "Radial Basis Functions with Partition of Unity Method for American Options with Stochastic Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 259-287, January.
    4. Kozpınar, Sinem & Uzunca, Murat & Karasözen, Bülent, 2020. "Pricing European and American options under Heston model using discontinuous Galerkin finite elements," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 568-587.
    5. Rad, Jamal Amani & Parand, Kourosh & Ballestra, Luca Vincenzo, 2015. "Pricing European and American options by radial basis point interpolation," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 363-377.
    6. Guarin, Alexander & Liu, Xiaoquan & Ng, Wing Lon, 2014. "Recovering default risk from CDS spreads with a nonlinear filter," Journal of Economic Dynamics and Control, Elsevier, vol. 38(C), pages 87-104.
    7. Weiwei Liu & Zhile Yang & Kexin Bi, 2017. "Forecasting the Acquisition of University Spin-Outs: An RBF Neural Network Approach," Complexity, Hindawi, vol. 2017, pages 1-8, October.
    8. Gong, Pu & Zou, Dong & Wang, Jiayue, 2018. "Pricing and simulation for real estate index options: Radial basis point interpolation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 177-188.
    9. Golbabai, Ahmad & Mohebianfar, Ehsan, 2017. "A new method for evaluating options based on multiquadric RBF-FD method," Applied Mathematics and Computation, Elsevier, vol. 308(C), pages 130-141.
    10. Zaheer-ud-Din & Muhammad Ahsan & Masood Ahmad & Wajid Khan & Emad E. Mahmoud & Abdel-Haleem Abdel-Aty, 2020. "Meshless Analysis of Nonlocal Boundary Value Problems in Anisotropic and Inhomogeneous Media," Mathematics, MDPI, vol. 8(11), pages 1-19, November.
    11. A. Golbabai & E. Mohebianfar, 2017. "A New Stable Local Radial Basis Function Approach for Option Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 49(2), pages 271-288, February.
    12. Jamal Amani Rad & Kourosh Parand & Saeid Abbasbandy, 2014. "Local weak form meshless techniques based on the radial point interpolation (RPI) method and local boundary integral equation (LBIE) method to evaluate European and American options," Papers 1412.6063, arXiv.org.
    13. Shirzadi, Mohammad & Rostami, Mohammadreza & Dehghan, Mehdi & Li, Xiaolin, 2023. "American options pricing under regime-switching jump-diffusion models with meshfree finite point method," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    14. Yusho Kagraoka, 2020. "The Fractional Step Method versus the Radial Basis Functions for Option Pricing with Correlated Stochastic Processes," IJFS, MDPI, vol. 8(4), pages 1-13, December.
    15. Kentaro Hoshisashi & Yuji Yamada, 2023. "Pricing Multi-Asset Bermudan Commodity Options with Stochastic Volatility Using Neural Networks," JRFM, MDPI, vol. 16(3), pages 1-23, March.
    16. Alessandro Andreoli & Luca Vincenzo Ballestra & Graziella Pacelli, 2018. "Pricing Credit Default Swaps Under Multifactor Reduced-Form Models: A Differential Quadrature Approach," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 379-406, March.
    17. Kirkby, J. Lars & Nguyen, Duy & Cui, Zhenyu, 2017. "A unified approach to Bermudan and barrier options under stochastic volatility models with jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 75-100.
    18. Kaennakham, S. & Chuathong, N., 2019. "An automatic node-adaptive scheme applied with a RBF-collocation meshless method," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 102-125.
    19. Zhang, Hongyu & Guo, Xunxiang & Wang, Ke & Huang, Shoude, 2024. "The valuation of American options with the stochastic liquidity risk and jump risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 650(C).

  22. Ballestra, Luca Vincenzo & Ottaviani, Massimiliano & Pacelli, Graziella, 2012. "An operator splitting harmonic differential quadrature approach to solve Young’s model for life insurance risk," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 442-448.

    Cited by:

    1. Alessandro Andreoli & Luca Vincenzo Ballestra & Graziella Pacelli, 2018. "Pricing Credit Default Swaps Under Multifactor Reduced-Form Models: A Differential Quadrature Approach," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 379-406, March.

  23. Luca Vincenzo Ballestra & Graziella Pacelli, 2011. "The constant elasticity of variance model: calibration, test and evidence from the Italian equity market," Applied Financial Economics, Taylor & Francis Journals, vol. 21(20), pages 1479-1487.

    Cited by:

    1. Ballestra, Luca Vincenzo & Cecere, Liliana, 2015. "Pricing American options under the constant elasticity of variance model: An extension of the method by Barone-Adesi and Whaley," Finance Research Letters, Elsevier, vol. 14(C), pages 45-55.
    2. Ballestra, Luca Vincenzo & Cecere, Liliana, 2016. "A numerical method to estimate the parameters of the CEV model implied by American option prices: Evidence from NYSE," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 100-106.

  24. Luca Vincenzo Ballestra & Graziella Pacelli, 2009. "A Numerical Method to Price Defaultable Bonds Based on the Madan and Unal Credit Risk Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(1), pages 17-36.

    Cited by:

    1. Hyong-Chol O. & Jong-Chol Kim & Il-Gwang Jon, 2017. "Numerical analysis for a unified 2 factor model of structural and reduced form types for corporate bonds with fixed discrete coupon," Papers 1709.06517, arXiv.org, revised Aug 2018.
    2. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2014. "Valuing risky debt: A new model combining structural information with the reduced-form approach," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 261-271.

  25. Ballestra, Luca Vincenzo & Pacelli, Graziella & Zirilli, Francesco, 2007. "A numerical method to price exotic path-dependent options on an underlying described by the Heston stochastic volatility model," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3420-3437, November.

    Cited by:

    1. Kiseop Lee & Seongje Lim & Hyungbin Park, 2022. "Option pricing under path-dependent stock models," Papers 2211.10953, arXiv.org, revised Aug 2023.
    2. Carlos Esparcia & Elena Ibañez & Francisco Jareño, 2020. "Volatility Timing: Pricing Barrier Options on DAX XETRA Index," Mathematics, MDPI, vol. 8(5), pages 1-25, May.
    3. Bara Kim & In-Suk Wee, 2014. "Pricing of geometric Asian options under Heston's stochastic volatility model," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1795-1809, October.
    4. Fuh, Cheng-Der & Luo, Sheng-Feng & Yen, Ju-Fang, 2013. "Pricing discrete path-dependent options under a double exponential jump–diffusion model," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2702-2713.

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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-ECM: Econometrics (2) 2024-11-18 2024-11-25
  2. NEP-ETS: Econometric Time Series (2) 2024-11-18 2024-11-25
  3. NEP-RMG: Risk Management (2) 2024-11-18 2024-11-25
  4. NEP-SEA: South East Asia (1) 2021-05-24

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