Giuseppe Orlando

Personal Details

First Name:	Giuseppe
Middle Name:
Last Name:	Orlando
Suffix:
RePEc Short-ID:	por230
	[This author has chosen not to make the email address public]
	https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=2129018

Affiliation

Dipartimento di Economia e Finanza
Facoltà di Economia
Università degli Studi di Bari "Aldo Moro"

Bari, Italy
http://www.uniba.it/ricerca/dipartimenti/dse
RePEc:edi:debarit (more details at EDIRC)

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. Julio Guerrero & Giuseppe Orlando, 2022. "Stochastic Local Volatility models and the Wei-Norman factorization method," Papers 2201.11241, arXiv.org.

   Cited by:

   1. Francesco Cesarone & Raffaello Cesetti & Giuseppe Orlando & Manuel Luis Martino & Jacopo Maria Ricci, 2022. "Comparing SSD-Efficient Portfolios with a Skewed Reference Distribution," Mathematics, MDPI, vol. 11(1), pages 1-20, December.

2. Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2019. "Forecasting interest rates through Vasicek and CIR models: a partitioning approach," Papers 1901.02246, arXiv.org, revised Jan 2019.
   • Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2020. "Forecasting interest rates through Vasicek and CIR models: A partitioning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 569-579, July.

   Cited by:

   1. Marco Di Francesco & Kevin Kamm, 2021. "How to handle negative interest rates in a CIR framework," Papers 2106.03716, arXiv.org.
   2. Giuseppe Orlando & Michele Bufalo, 2021. "Interest rates forecasting: Between Hull and White and the CIR#—How to make a single‐factor model work," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1566-1580, December.
   3. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
   4. Ascione, Giacomo & Mehrdoust, Farshid & Orlando, Giuseppe & Samimi, Oldouz, 2023. "Foreign Exchange Options on Heston-CIR Model Under Lévy Process Framework," Applied Mathematics and Computation, Elsevier, vol. 446(C).
   5. Gareth Liu-Evans, 2021. "Improving the Estimation and Predictions of Small Time Series Models," Working Papers 202106, University of Liverpool, Department of Economics.
   6. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).
   7. Anna Battauz & Francesco Rotondi, 2022. "American options and stochastic interest rates," Computational Management Science, Springer, vol. 19(4), pages 567-604, October.
   8. Giuseppe Orlando & Michele Bufalo, 2022. "A generalized two‐factor square‐root framework for modeling occurrences of natural catastrophes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1608-1622, December.

3. Michele Mininni & Giuseppe Orlando & Giovanni Taglialatela, 2018. "Challenges in approximating the Black and Scholes call formula with hyperbolic tangents," Papers 1810.04623, arXiv.org.
   • Michele Mininni & Giuseppe Orlando & Giovanni Taglialatela, 2021. "Challenges in approximating the Black and Scholes call formula with hyperbolic tangents," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 73-100, June.

   Cited by:

   1. Giuseppe Orlando & Michele Bufalo, 2021. "Interest rates forecasting: Between Hull and White and the CIR#—How to make a single‐factor model work," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1566-1580, December.
   2. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
   3. Daniel Wei-Chung Miao & Xenos Chang-Shuo Lin & Chang-Yao Lin, 2021. "Using Householder’s method to improve the accuracy of the closed-form formulas for implied volatility," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(3), pages 493-528, December.
   4. Geon Lee & Tae-Kyoung Kim & Hyun-Gyoon Kim & Jeonggyu Huh, 2022. "Newton Raphson Emulation Network for Highly Efficient Computation of Numerous Implied Volatilities," Papers 2210.15969, arXiv.org.

Articles

1. Orlando, Giuseppe, 2022. "Simulating heterogeneous corporate dynamics via the Rulkov map," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 32-42.

   Cited by:

   1. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.

2. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).

   Cited by:

   1. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.
   2. Wanying Song & Jian Min & Jianbo Yang, 2023. "Credit Risk Assessment of Heavy-Polluting Enterprises: A Wide- ℓ p Penalty and Deep Learning Approach," Mathematics, MDPI, vol. 11(16), pages 1-19, August.
   3. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).
   4. Juan Meng & Bin Mo & He Nie, 2023. "The dynamics of crude oil future prices on China's energy markets: Quantile‐on‐quantile and casualty‐in‐quantiles approaches," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(12), pages 1853-1871, December.

3. Francesco Cesarone & Raffaello Cesetti & Giuseppe Orlando & Manuel Luis Martino & Jacopo Maria Ricci, 2022. "Comparing SSD-Efficient Portfolios with a Skewed Reference Distribution," Mathematics, MDPI, vol. 11(1), pages 1-20, December.

   Cited by:

   1. Francesco Cesarone & Manuel Luis Martino & Federica Ricca & Andrea Scozzari, 2023. "Managing ESG Ratings Disagreement in Sustainable Portfolio Selection," Papers 2312.10739, arXiv.org.
   2. Francesco Cesarone & Justo Puerto, 2024. "New approximate stochastic dominance approaches for Enhanced Indexation models," Papers 2401.12669, arXiv.org.
   3. Francesco Cesarone & Rosella Giacometti & Manuel Luis Martino & Fabio Tardella, 2023. "A return-diversification approach to portfolio selection," Papers 2312.09707, arXiv.org.

4. Giuseppe Orlando & Michele Bufalo, 2022. "A generalized two‐factor square‐root framework for modeling occurrences of natural catastrophes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1608-1622, December.

   Cited by:

   1. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.

5. Giuseppe Orlando & Michele Bufalo, 2021. "Interest rates forecasting: Between Hull and White and the CIR#—How to make a single‐factor model work," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1566-1580, December.

   Cited by:

   1. Giuseppe Orlando & Michele Bufalo, 2022. "A generalized two‐factor square‐root framework for modeling occurrences of natural catastrophes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1608-1622, December.

6. Michele Mininni & Giuseppe Orlando & Giovanni Taglialatela, 2021. "Challenges in approximating the Black and Scholes call formula with hyperbolic tangents," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 73-100, June.
   • Michele Mininni & Giuseppe Orlando & Giovanni Taglialatela, 2018. "Challenges in approximating the Black and Scholes call formula with hyperbolic tangents," Papers 1810.04623, arXiv.org.
   See citations under working paper version above.
7. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.

   Cited by:

   1. Francesco Cesarone & Raffaello Cesetti & Giuseppe Orlando & Manuel Luis Martino & Jacopo Maria Ricci, 2022. "Comparing SSD-Efficient Portfolios with a Skewed Reference Distribution," Mathematics, MDPI, vol. 11(1), pages 1-20, December.
   2. Orlando, Giuseppe, 2022. "Simulating heterogeneous corporate dynamics via the Rulkov map," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 32-42.
   3. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).
   4. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).

8. Giuseppe Orlando & Edward Bace, 2021. "Challenging Times for Insurance, Banking and Financial Supervision in Saudi Arabia (KSA)," Administrative Sciences, MDPI, vol. 11(3), pages 1-28, June.

   Cited by:

   1. Faisal Mohammed O. Almaslukh & Haliyana Khalid & Alaa Mahdi Sahi, 2022. "The Impact of Internal Marketing Practices on Employees’ Job Satisfaction during the COVID-19 Pandemic: The Case of the Saudi Arabian Banking Sector," Sustainability, MDPI, vol. 14(15), pages 1-15, July.
   2. Pejman Peykani & Mostafa Sargolzaei & Mohammad Hashem Botshekan & Camelia Oprean-Stan & Amir Takaloo, 2023. "Optimization of Asset and Liability Management of Banks with Minimum Possible Changes," Mathematics, MDPI, vol. 11(12), pages 1-24, June.

9. Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2020. "Forecasting interest rates through Vasicek and CIR models: A partitioning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 569-579, July.
   • Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2019. "Forecasting interest rates through Vasicek and CIR models: a partitioning approach," Papers 1901.02246, arXiv.org, revised Jan 2019.
   See citations under working paper version above.
10. Giuseppe Orlando & Roberta Pelosi, 2020. "Non-Performing Loans for Italian Companies: When Time Matters. An Empirical Research on Estimating Probability to Default and Loss Given Default," IJFS, MDPI, vol. 8(4), pages 1-22, November.

    Cited by:

    1. Aneta Ptak-Chmielewska & Paweł Kopciuszewski & Anna Matuszyk, 2023. "Application of the kNN-Based Method and Survival Approach in Estimating Loss Given Default for Unresolved Cases," Risks, MDPI, vol. 11(2), pages 1-14, February.
    2. Seyed Alireza Athari & Chafic Saliba & Danielle Khalife & Madonna Salameh-Ayanian, 2023. "The Role of Country Governance in Achieving the Banking Sector’s Sustainability in Vulnerable Environments: New Insight from Emerging Economies," Sustainability, MDPI, vol. 15(13), pages 1-15, July.
    3. Khalil Alnabulsi & Emira Kozarević & Abdelaziz Hakimi, 2023. "Non-Performing Loans and Net Interest Margin in the MENA Region: Linear and Non-Linear Analyses," IJFS, MDPI, vol. 11(2), pages 1-17, April.
    4. Nikita Moiseev & Aleksander Sorokin & Natalya Zvezdina & Alexey Mikhaylov & Lyubov Khomyakova & Mir Sayed Shah Danish, 2021. "Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework," Mathematics, MDPI, vol. 9(19), pages 1-12, September.
    5. Chafic Saliba & Panteha Farmanesh & Seyed Alireza Athari, 2023. "Does country risk impact the banking sectors’ non-performing loans? Evidence from BRICS emerging economies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-30, December.
    6. Ekaterina V. Orlova, 2021. "Methodology and Models for Individuals’ Creditworthiness Management Using Digital Footprint Data and Machine Learning Methods," Mathematics, MDPI, vol. 9(15), pages 1-28, August.
    7. Aydin Aslan & Lars Poppe & Peter Posch, 2021. "Are Sustainable Companies More Likely to Default? Evidence from the Dynamics between Credit and ESG Ratings," Sustainability, MDPI, vol. 13(15), pages 1-16, July.
    8. Giuseppe Orlando & Edward Bace, 2021. "Challenging Times for Insurance, Banking and Financial Supervision in Saudi Arabia (KSA)," Administrative Sciences, MDPI, vol. 11(3), pages 1-28, June.

11. Giuseppe Orlando & Fabio Della Rossa, 2019. "An Empirical Test on Harrod’s Open Economy Dynamics," Mathematics, MDPI, vol. 7(6), pages 1-13, June.

    Cited by:

    1. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.

12. Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2019. "Interest rates calibration with a CIR model," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 20(4), pages 370-387, September.

    Cited by:

    1. Wulan Anggraeni & Sudradjat Supian & Sukono & Nurfadhlina Binti Abdul Halim, 2022. "Earthquake Catastrophe Bond Pricing Using Extreme Value Theory: A Mini-Review Approach," Mathematics, MDPI, vol. 10(22), pages 1-22, November.
    2. Marco Di Francesco & Kevin Kamm, 2021. "How to handle negative interest rates in a CIR framework," Papers 2106.03716, arXiv.org.
    3. Mohamed Ben Alaya & Ahmed Kebaier & Djibril Sarr, 2021. "Deep Calibration of Interest Rates Model," Papers 2110.15133, arXiv.org.
    4. Giuseppe Orlando & Michele Bufalo, 2021. "Interest rates forecasting: Between Hull and White and the CIR#—How to make a single‐factor model work," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1566-1580, December.
    5. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
    6. Ascione, Giacomo & Mehrdoust, Farshid & Orlando, Giuseppe & Samimi, Oldouz, 2023. "Foreign Exchange Options on Heston-CIR Model Under Lévy Process Framework," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    7. Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2019. "Forecasting interest rates through Vasicek and CIR models: a partitioning approach," Papers 1901.02246, arXiv.org, revised Jan 2019.
       • Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2020. "Forecasting interest rates through Vasicek and CIR models: A partitioning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 569-579, July.
    8. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).
    9. Wulan Anggraeni & Sudradjat Supian & Sukono & Nurfadhlina Abdul Halim, 2023. "Single Earthquake Bond Pricing Framework with Double Trigger Parameters Based on Multi Regional Seismic Information," Mathematics, MDPI, vol. 11(3), pages 1-44, January.
    10. Giuseppe Orlando & Michele Bufalo, 2022. "A generalized two‐factor square‐root framework for modeling occurrences of natural catastrophes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1608-1622, December.

13. Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2019. "A new approach to forecast market interest rates through the CIR model," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 37(2), pages 267-292, September.

    Cited by:

    1. Marco Di Francesco & Kevin Kamm, 2021. "How to handle negative interest rates in a CIR framework," Papers 2106.03716, arXiv.org.
    2. Giuseppe Orlando & Michele Bufalo, 2021. "Interest rates forecasting: Between Hull and White and the CIR#—How to make a single‐factor model work," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1566-1580, December.
    3. Ascione, Giacomo & Mehrdoust, Farshid & Orlando, Giuseppe & Samimi, Oldouz, 2023. "Foreign Exchange Options on Heston-CIR Model Under Lévy Process Framework," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    4. Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2019. "Forecasting interest rates through Vasicek and CIR models: a partitioning approach," Papers 1901.02246, arXiv.org, revised Jan 2019.
       • Giuseppe Orlando & Rosa Maria Mininni & Michele Bufalo, 2020. "Forecasting interest rates through Vasicek and CIR models: A partitioning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 569-579, July.
    5. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).

14. Orlando, Giuseppe & Zimatore, Giovanna, 2018. "Recurrence quantification analysis of business cycles," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 82-94.
    • Giuseppe Orlando & Giovanna Zimatore, 2021. "Recurrence Quantification Analysis of Business Cycles," Dynamic Modeling and Econometrics in Economics and Finance, in: Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), Nonlinearities in Economics, chapter 0, pages 269-282, Springer.

    Cited by:

    1. Zhou, Ling & You, Zhenzhen & Tang, Yun, 2021. "A new chaotic system with nested coexisting multiple attractors and riddled basins," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    2. Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," Economics Letters, Elsevier, vol. 213(C).
       • Hashem Dezhbakhsh & Daniel Levy, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," Working Paper series 22-05, Rimini Centre for Economic Analysis.
       • Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 213.
       • Daniel Levy & Hashem Dezhbakhsh, 2022. "Interpolation and Shock Persistence of Prewar U.S. Macroeconomic Time Series: A Reconsideration," Working Papers 2022-02, Bar-Ilan University, Department of Economics.
       • Dezhbakhsh, Hashem & Levy, Daniel, 2022. "Interpolation and Shock Persistence of Prewar U.S. Macroeconomic Time Series: A Reconsideration," MPRA Paper 112493, University Library of Munich, Germany.
    3. Ashe, Sinéad & Egan, Paul, 2023. "Examining financial and business cycle interaction using cross recurrence plot analysis," Finance Research Letters, Elsevier, vol. 51(C).
    4. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.
    5. Mostafa Shabani & Martin Magris & George Tzagkarakis & Juho Kanniainen & Alexandros Iosifidis, 2022. "Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots," Papers 2210.14605, arXiv.org, revised Nov 2022.
    6. He, Qian & Yu, Fusheng, 2023. "Trend recurrence analysis and time series classification via trend fuzzy granular recurrence plot method," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    7. Giuseppe Orlando & Fabio Della Rossa, 2019. "An Empirical Test on Harrod’s Open Economy Dynamics," Mathematics, MDPI, vol. 7(6), pages 1-13, June.
    8. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).

15. Orlando, Giuseppe, 2016. "A discrete mathematical model for chaotic dynamics in economics: Kaldor’s model on business cycle," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 125(C), pages 83-98.

    Cited by:

    1. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.
    2. 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.
    3. Giuseppe Orlando & Fabio Della Rossa, 2019. "An Empirical Test on Harrod’s Open Economy Dynamics," Mathematics, MDPI, vol. 7(6), pages 1-13, June.
    4. Muhamad Deni Johansyah & Aceng Sambas & Saleh Mobayen & Behrouz Vaseghi & Saad Fawzi Al-Azzawi & Sukono & Ibrahim Mohammed Sulaiman, 2022. "Dynamical Analysis and Adaptive Finite-Time Sliding Mode Control Approach of the Financial Fractional-Order Chaotic System," Mathematics, MDPI, vol. 11(1), pages 1-14, December.
    5. Gao, Wei & Yan, Li & Saeedi, Mohammadhossein & Saberi Nik, Hassan, 2018. "Ultimate bound estimation set and chaos synchronization for a financial risk system," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 154(C), pages 19-33.
    6. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).
    7. Orlando, Giuseppe & Zimatore, Giovanna, 2018. "Recurrence quantification analysis of business cycles," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 82-94.
       • Giuseppe Orlando & Giovanna Zimatore, 2021. "Recurrence Quantification Analysis of Business Cycles," Dynamic Modeling and Econometrics in Economics and Finance, in: Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), Nonlinearities in Economics, chapter 0, pages 269-282, Springer.

Chapters

1. Giuseppe Orlando & Giovanna Zimatore, 2021. "Recurrence Quantification Analysis of Business Cycles," Dynamic Modeling and Econometrics in Economics and Finance, in: Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), Nonlinearities in Economics, chapter 0, pages 269-282, Springer.
   • Orlando, Giuseppe & Zimatore, Giovanna, 2018. "Recurrence quantification analysis of business cycles," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 82-94.
   See citations under working paper version above.
2. Giuseppe Orlando & Giovanni Taglialatela, 2021. "Dynamical Systems," Dynamic Modeling and Econometrics in Economics and Finance, in: Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), Nonlinearities in Economics, chapter 0, pages 13-37, Springer.

   Cited by:

   1. Giuseppe Orlando & Fabio Della Rossa, 2019. "An Empirical Test on Harrod’s Open Economy Dynamics," Mathematics, MDPI, vol. 7(6), pages 1-13, June.

Books

1. Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), 2021. "Nonlinearities in Economics," Dynamic Modeling and Econometrics in Economics and Finance, Springer, number 978-3-030-70982-2, July-Dece.

   Cited by:

   1. Orlando, Giuseppe, 2022. "Simulating heterogeneous corporate dynamics via the Rulkov map," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 32-42.
   2. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.
   3. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).

More information

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 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-HME: Heterodox Microeconomics (2) 2023-05-01 2023-08-21. Author is listed
2. NEP-PKE: Post Keynesian Economics (2) 2023-05-01 2023-08-21. Author is listed
3. NEP-RMG: Risk Management (2) 2018-10-22 2022-03-07. Author is listed
4. NEP-MAC: Macroeconomics (1) 2023-05-01. Author is listed
5. NEP-ORE: Operations Research (1) 2022-03-07. Author is listed

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