Financial Risk Modeling

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Risk".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 3562

Special Issue Editor


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Guest Editor
Institute for Economic Forecasting, Romanian Academy, Bucharest University of Economic Studies, Bucharest, Romania
Interests: financial markets; asset pricing; monetary policy; credit risk; volatility modeling; financial econometrics; economic forecasting; risk management
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Special Issue Information

Dear Colleagues,

Deficient risk management has been considered by many to be one of the main drivers of the financial crisis of 2007–2009. The intricate interconnectedness of the contemporary financial system chains financial institutions together to an unprecedented extent, such that the problems faced by one institution due to excessive risk-taking can swiftly spread to others, creating systemic threats. The increasing challenges of the financial industry translate into the need for new instruments for measuring and managing financial risks capable of supporting solid decision-making processes within the current regulatory framework. Moreover, the existing modeling apparatus needs to be extended in order to accommodate the emergence of new financial products and services or new technologies such as artificial intelligence and big data analysis.

Given the above, this Special Issue aims to attract original contributions dealing with current advances in financial modeling and their applications in all fields of finance.

We encourage submissions that are related, but not limited, to the following topics:

  • Market risk;
  • Credit risk;
  • Systemic risk;
  • Model risk;
  • Liquidity risk;
  • Financial risk management and analysis;
  • Forecasting of financial distress;
  • Market dynamics and prediction;
  • Issues relating to domestic and international financial stability;
  • Macroprudential policies and supervision.

Dr. Adrian Cantemir Calin
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

15 pages, 1082 KiB  
Article
Evidential Strategies in Financial Statement Analysis: A Corpus Linguistic Text Mining Approach to Bankruptcy Prediction
by Tobias Nießner, Daniel H. Gross and Matthias Schumann
J. Risk Financial Manag. 2022, 15(10), 459; https://doi.org/10.3390/jrfm15100459 - 13 Oct 2022
Cited by 2 | Viewed by 3265
Abstract
The qualitative information of companies’ financial statements provides useful information that can increase the accuracy of bankruptcy prediction models. In this research, a dataset of 924,903 financial statements from 355,704 German companies classified into solvent, financially distressed, and bankrupt companies using the Amadeus [...] Read more.
The qualitative information of companies’ financial statements provides useful information that can increase the accuracy of bankruptcy prediction models. In this research, a dataset of 924,903 financial statements from 355,704 German companies classified into solvent, financially distressed, and bankrupt companies using the Amadeus database from Bureau van Dijk was examined. The results provide empirical evidence that a corpus linguistic approach implementing evidential strategy analysis towards financial statements helps to distinguish between companies’ financial situations. They show that companies use different approaches and confidence assessments when evaluating their financial statements based on solvency and vary their use of evidential strategies accordingly. This leads to the proposition of a procedure to quantify and generate features based on the analysis of evidential strategies that can be used to improve corporate bankruptcy prediction. The results presented here stem from an interdisciplinary adaptation of linguistic findings and provide future research with another means of analysis in the area of text mining. Full article
(This article belongs to the Special Issue Financial Risk Modeling)
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