Fabio Parlapiano

Personal Details

First Name:	Fabio
Middle Name:
Last Name:	Parlapiano
Suffix:
RePEc Short-ID:	ppa1225
	[This author has chosen not to make the email address public]
	https://scholar.google.com/citations?hl=enuser=JI-ApqEAAAAJ

Affiliation

Banca d'Italia

Roma, Italy
http://www.bancaditalia.it/
RePEc:edi:bdigvit (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. Giuseppe Cascarino & Mirko Moscatelli & Fabio Parlapiano, 2022. "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning," Questioni di Economia e Finanza (Occasional Papers) 674, Bank of Italy, Economic Research and International Relations Area.

   Cited by:

   1. 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.
      • Raffaele Marchi & Alessandro Moro, 2024. "Forecasting Fiscal Crises in Emerging Markets and Low-Income Countries with Machine Learning Models," Open Economies Review, Springer, vol. 35(1), pages 189-213, February.
   2. Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
   3. Rosaria Cerrone, 2023. "Are Artificial Intelligence and Machine Learning Shaping a New Risk Management Approach?," International Business Research, Canadian Center of Science and Education, vol. 16(12), pages 1-82, December.
   4. Jorge Tejero, 2022. "Unwrapping black box models A case study in credit risk," Revista de Estabilidad Financiera, Banco de España, issue NOV.
   5. Jorge Tejero, 2022. "Unwrapping black box models A case study in credit risk," Financial Stability Review, Banco de España, issue NOV.
   6. Antonietta di Salvatore & Mirko Moscatelli, 2024. "Improving survey information on household debt using granular credit databases," Questioni di Economia e Finanza (Occasional Papers) 839, Bank of Italy, Economic Research and International Relations Area.

2. Paolo Finaldi Russo & Fabio Parlapiano & Daniele Pianeselli & Ilaria Supino, 2020. "Firms’ listings: what is new? Italy versus the main European stock exchanges," Questioni di Economia e Finanza (Occasional Papers) 555, Bank of Italy, Economic Research and International Relations Area.

   Cited by:

   1. Cappiello, Lorenzo & Holm-Hadulla, Fédéric & Maddaloni, Angela & Mayordomo, Sergio & Unger, Robert & Arts, Laura & Meme, Nicolas & Asimakopoulos, Ioannis & Migiakis, Petros & Behrens, Caterina & Moura, 2021. "Non-bank financial intermediation in the euro area: implications for monetary policy transmission and key vulnerabilities," Occasional Paper Series 270, European Central Bank.
   2. Francesco Columba & Tommaso Orlando & Francesco Palazzo & Fabio Parlapiano, 2022. "The features of equity capital increases by Italian corporates," Questioni di Economia e Finanza (Occasional Papers) 709, Bank of Italy, Economic Research and International Relations Area.

3. Mirko Moscatelli & Simone Narizzano & Fabio Parlapiano & Gianluca Viggiano, 2019. "Corporate default forecasting with machine learning," Temi di discussione (Economic working papers) 1256, Bank of Italy, Economic Research and International Relations Area.

   Cited by:

   1. Nicola Branzoli & Ilaria Supino, 2020. "FinTech credit: a critical review of empirical research," Questioni di Economia e Finanza (Occasional Papers) 549, Bank of Italy, Economic Research and International Relations Area.
   2. Agnese Carella & Federica Ciocchetta & Valentina Michelangeli & Federico Maria Signoretti, 2020. "What can we learn about mortgage supply from online data?," Questioni di Economia e Finanza (Occasional Papers) 583, Bank of Italy, Economic Research and International Relations Area.
   3. Francesco Cusano & Giuseppe Marinelli & Stefano Piermattei, 2021. "Learning from revisions: a tool for detecting potential errors in banks' balance sheet statistical reporting," Questioni di Economia e Finanza (Occasional Papers) 611, Bank of Italy, Economic Research and International Relations Area.
   4. Giuseppe Cascarino & Mirko Moscatelli & Fabio Parlapiano, 2022. "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning," Questioni di Economia e Finanza (Occasional Papers) 674, Bank of Italy, Economic Research and International Relations Area.
   5. Fantazzini, Dean & Calabrese, Raffaella, 2021. "Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure," MPRA Paper 110391, University Library of Munich, Germany.
      • 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.
   6. Henri Fraisse & Matthias Laporte, 2021. "Return on Investment on AI: The Case of Capital Requirement," Working papers 809, Banque de France.
   7. Lisa Crosato & Caterina Liberati & Marco Repetto, 2021. "Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default," Papers 2108.13914, arXiv.org, revised Sep 2021.
   8. Golbayani, Parisa & Florescu, Ionuţ & Chatterjee, Rupak, 2020. "A comparative study of forecasting corporate credit ratings using neural networks, support vector machines, and decision trees," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
   9. Alonso-Robisco, Andrés & Carbó, José Manuel, 2022. "Can machine learning models save capital for banks? Evidence from a Spanish credit portfolio," International Review of Financial Analysis, Elsevier, vol. 84(C).
   10. Salvatore Cardillo & Raffaele Gallo & Francesco Guarino, 2021. "Main challenges and prospects for the European banking sector: a critical review of the ongoing debate," Questioni di Economia e Finanza (Occasional Papers) 634, Bank of Italy, Economic Research and International Relations Area.
   11. Falco J. Bargagli-Dtoffi & Massimo Riccaboni & Armando Rungi, 2020. "Machine Learning for Zombie Hunting. Firms Failures and Financial Constraints," Working Papers 01/2020, IMT School for Advanced Studies Lucca, revised Jun 2020.
   12. Falco J. Bargagli-Stoffi & Jan Niederreiter & Massimo Riccaboni, 2020. "Supervised learning for the prediction of firm dynamics," Papers 2009.06413, arXiv.org.
   13. Falco J. Bargagli-Stoffi & Fabio Incerti & Massimo Riccaboni & Armando Rungi, 2023. "Machine Learning for Zombie Hunting: Predicting Distress from Firms' Accounts and Missing Values," Papers 2306.08165, arXiv.org.
   14. Flavio Bazzana & Marco Bee & Ahmed Almustfa Hussin Adam Khatir, 2024. "Machine learning techniques for default prediction: an application to small Italian companies," Risk Management, Palgrave Macmillan, vol. 26(1), pages 1-23, February.
   15. Andrés Alonso & José Manuel Carbó, 2021. "Understanding the performance of machine learning models to predict credit default: a novel approach for supervisory evaluation," Working Papers 2105, Banco de España.
   16. Parisa Golbayani & Ionuc{t} Florescu & Rupak Chatterjee, 2020. "A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees," Papers 2007.06617, arXiv.org.
   17. 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.
   18. Alessandro Bitetto & Stefano Filomeni & Michele Modina, 2021. "Understanding corporate default using Random Forest: The role of accounting and market information," DEM Working Papers Series 205, University of Pavia, Department of Economics and Management.
   19. Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2021. "Machine Learning and Credit Risk: Empirical Evidence from SMEs," DEM Working Papers Series 201, University of Pavia, Department of Economics and Management.
   20. Branka Hadji Misheva & Joerg Osterrieder & Ali Hirsa & Onkar Kulkarni & Stephen Fung Lin, 2021. "Explainable AI in Credit Risk Management," Papers 2103.00949, arXiv.org.

4. Parlapiano, Fabio & Alexeev, Vitali, 2012. "Exchange Rate Risk Exposure and the Value of European Firms," Working Papers 2012-09, University of Tasmania, Tasmanian School of Business and Economics, revised 20 Nov 2012.
   • Fabio Parlapiano & Vitali Alexeev & Mardi Dungey, 2017. "Exchange rate risk exposure and the value of European firms," The European Journal of Finance, Taylor & Francis Journals, vol. 23(2), pages 111-129, January.

   Cited by:

   1. Asif, Raheel & Frömmel, Michael, 2022. "Exchange rate exposure for exporting and domestic firms in central and Eastern Europe," Emerging Markets Review, Elsevier, vol. 51(PA).
   2. Willem Thorbecke, 2022. "Understanding the transmission of COVID-19 news to French financial markets in early 2020," International Economics, CEPII research center, issue 170, pages 103-114.
      • Thorbecke, Willem, 2022. "Understanding the transmission of COVID-19 news to French financial markets in early 2020," International Economics, Elsevier, vol. 170(C), pages 103-114.
   3. Ekta Sikarwar & Roopak Gupta, 2019. "Economic exposure to exchange rate risk and financial hedging," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(4), pages 965-984, August.
   4. Ibrahim Ethem Guney & Abdullah Kazdal & Doruk Kucuksarac & Muhammed Hasan Yilmaz, 2019. "Exchange Rate Sensitivity of Firm Value : Recent Evidence from Non-Financial Firms Listed on Borsa Istanbul," CBT Research Notes in Economics 1911, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
   5. Stephen Chan & Jeffrey Chu & Saralees Nadarajah & Joerg Osterrieder, 2017. "A Statistical Analysis of Cryptocurrencies," JRFM, MDPI, vol. 10(2), pages 1-23, May.
   6. Milutinovic, Monia, 2018. "Cryptocurrency," Ekonomika, Journal for Economic Theory and Practice and Social Issues, Society of Economists Ekonomika, Nis, Serbia, vol. 64(1), March.
   7. Asep Risman & Ubud Salim & Sumiati Sumiati & Nur Khusniyah Indrawati, 2017. "Commodity Prices, Exchange Rates and Investment on Firm's Value Mediated by Business Risk: A Case from Indonesian Stock Exchange," European Research Studies Journal, European Research Studies Journal, vol. 0(3A), pages 511-524.
   8. İbrahim Ethem Güney & Abdullah Kazdal & Doruk Küçüksaraç & Muhammed Hasan Yılmaz, 2021. "Exchange Rate Sensitivity of Firm Value: Evidence from Nonfinancial Firms Listed on Borsa Istanbul," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 141-165, Springer.
   9. Jun Wei, 2020. "Optimal Combination of Currency Assets and Algorithm Simulation under Exchange Rate Risk," Complexity, Hindawi, vol. 2020, pages 1-10, November.
   10. Muhammad Tahir & Haslindar Ibrahim & Abdul Hadi Zulkafli & Muhammad Mushtaq, 2020. "Influence of Exchange Rate Fluctuations and Credit Supply on Dividend Repatriation Policy of U.S. Multinational Corporations," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 9(special i), pages 267-290.
   11. Ahmet Akca & Ethem Çanakoğlu, 2021. "Adaptive stochastic risk estimation of firm operating profit," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 48(3), pages 463-504, September.
   12. Meen Chee Hong & Ei Yet Chu & Saw Imm Song, 2018. "Exchange Rate Exposure and Crude Oil Price: The Case of an Emerging Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 14(2), pages 157-184.
   13. Zakiya Begum Sayed & J. Gayathri, 2023. "Factors Determining the Exchange Rate Exposure of Firms: Evidence from India," Business Perspectives and Research, , vol. 11(2), pages 210-226, May.
   14. Subhadip Mukherjee & Soumyatanu Mukherjee & Tapas Mishra & Udo Broll & Mamata Parhi, 2021. "Spot exchange rate volatility, uncertain policies and export investment decision of firms: a mean-variance decision approach," The European Journal of Finance, Taylor & Francis Journals, vol. 27(8), pages 752-773, May.
   15. Joseba Luzarraga-Goitia & Marta Regúlez-Castillo & Arturo Rodríguez-Castellanos, 2021. "The dynamics between the stock market and exchange rates: Spain 1999–2015," The European Journal of Finance, Taylor & Francis Journals, vol. 27(7), pages 655-678, May.
   16. Julio Pindado & Ignacio Requejo & Juan C. Rivera, 2020. "Does money supply shape corporate capital structure? International evidence from a panel data analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 26(6), pages 554-584, April.
   17. Sung C. Bae & Taek Ho Kwon, 2023. "Exchange Rate Risk Management using Currency Derivatives: The Case of Exposures to Japanese Yen," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(3), pages 621-647, September.

Articles

1. Matteo Accornero & Giuseppe Cascarino & Roberto Felici & Fabio Parlapiano & Alberto Maria Sorrentino, 2018. "Credit risk in banks’ exposures to non‐financial firms," European Financial Management, European Financial Management Association, vol. 24(5), pages 775-791, November.

   Cited by:

   1. Roberta Fiori & Claudia Pacella, 2019. "Should the CCYB be enhanced with a sectoral dimension? The case of Italy," Questioni di Economia e Finanza (Occasional Papers) 499, Bank of Italy, Economic Research and International Relations Area.
   2. Natalia Nehrebecka, 2023. "Distribution of credit-risk concentration in particular sectors of the economy, and economic capital before and during the COVID-19 pandemic," Economic Change and Restructuring, Springer, vol. 56(1), pages 129-158, February.

2. Fabio Parlapiano & Vitali Alexeev & Mardi Dungey, 2017. "Exchange rate risk exposure and the value of European firms," The European Journal of Finance, Taylor & Francis Journals, vol. 23(2), pages 111-129, January.
   • Parlapiano, Fabio & Alexeev, Vitali, 2012. "Exchange Rate Risk Exposure and the Value of European Firms," Working Papers 2012-09, University of Tasmania, Tasmanian School of Business and Economics, revised 20 Nov 2012.
   See citations under working paper version above.

Chapters

Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 5 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-CFN: Corporate Finance (3) 2018-03-26 2020-05-04 2021-11-29
2. NEP-BAN: Banking (2) 2021-11-29 2022-04-04
3. NEP-BIG: Big Data (2) 2020-01-13 2022-04-04
4. NEP-CMP: Computational Economics (2) 2020-01-13 2022-04-04
5. NEP-RMG: Risk Management (2) 2020-01-13 2022-04-04
6. NEP-SBM: Small Business Management (2) 2020-05-04 2021-11-29
7. NEP-CWA: Central and Western Asia (1) 2021-11-29
8. NEP-EEC: European Economics (1) 2020-05-04
9. NEP-FMK: Financial Markets (1) 2020-05-04
10. NEP-FOR: Forecasting (1) 2022-04-04
11. NEP-ORE: Operations Research (1) 2020-01-13

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Fabio Parlapiano should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.