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Pedro N. Rodriguez

Personal Details

First Name:Pedro
Middle Name:N.
Last Name:Rodriguez
Suffix:
RePEc Short-ID:pro117
[This author has chosen not to make the email address public]
http://www.pnrodriguez.com

Affiliation

Facultad de Ciencias Económicas y Empresariales
Universidad Complutense de Madrid

Madrid, Spain
https://economicasyempresariales.ucm.es/
RePEc:edi:feucmes (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.

Articles

  1. Pedro N. Rodriguez & Arnulfo Rodriguez, 2006. "Understanding and predicting sovereign debt rescheduling: a comparison of the areas under receiver operating characteristic curves," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 459-479.

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. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.

    Cited by:

    1. Giulio Palomba, 2008. "Multivariate GARCH models and the Black-Litterman approach for tracking error constrained portfolios: an empirical analysis," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 10(4), pages 379-413.

Articles

  1. Pedro N. Rodriguez & Arnulfo Rodriguez, 2006. "Understanding and predicting sovereign debt rescheduling: a comparison of the areas under receiver operating characteristic curves," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 459-479.

    Cited by:

    1. Fantazzini, Dean, 2022. "Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death," MPRA Paper 113744, University Library of Munich, Germany.
    2. Raffaele De Marchi & Alessandro Moro, 2023. "Forecasting fiscal crises in emerging markets and low-income countries with machine learning models," Temi di discussione (Economic working papers) 1405, Bank of Italy, Economic Research and International Relations Area.
    3. Tonatiuh Peña & Serafín Martínez & Bolanle Abudu, 2011. "Bankruptcy Prediction: A Comparison of Some Statistical and Machine Learning Techniques," Dynamic Modeling and Econometrics in Economics and Finance, in: Herbert Dawid & Willi Semmler (ed.), Computational Methods in Economic Dynamics, pages 109-131, Springer.
    4. Dean Fantazzini & Raffaella Calabrese, 2021. "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, vol. 14(11), pages 1-23, October.
    5. Francis Kipkogei & Ignace H. Kabano & Belle Fille Murorunkwere & Nzabanita Joseph, 2021. "Business success prediction in Rwanda: a comparison of tree-based models and logistic regression classifiers," SN Business & Economics, Springer, vol. 1(8), pages 1-19, August.
    6. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
    7. Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
    8. Pasiouras, Fotios & Tanna, Sailesh, 2010. "The prediction of bank acquisition targets with discriminant and logit analyses: Methodological issues and empirical evidence," Research in International Business and Finance, Elsevier, vol. 24(1), pages 39-61, January.
    9. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 12(4), pages 84-137.
    10. Moreno Badia, Marialuz & Medas, Paulo & Gupta, Pranav & Xiang, Yuan, 2022. "Debt is not free," Journal of International Money and Finance, Elsevier, vol. 127(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper 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 (1) 2006-07-21
  2. NEP-FMK: Financial Markets (1) 2006-07-21
  3. NEP-FOR: Forecasting (1) 2006-07-21
  4. NEP-RMG: Risk Management (1) 2006-07-21

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