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Analytical methods to assess financial capacity in face of innovation projects risks
Rogulenko, Tatyana; Orlov, Evgeniy Vladimirovich; … - In: Risks : open access journal 9 (2021) 9, pp. 1-22
This paper aims to analyze the most relevant methods to determine the financial capacity of innovation projects and … capacity of innovation projects by charting an alternative balance with a minimum scope of data (annual balance sheet data … financial capacity of innovation projects in the context of different scales and terms of project jobs in an analyzed project …
Persistent link: https://www.econbiz.de/10012632031
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An academic response to Basel 3.5
Embrechts, Paul; Puccetti, Giovanni; Rüschendorf, Ludger; … - In: Risks : open access journal 2 (2014) 1, pp. 25-48
Recent crises in the financial industry have shown weaknesses in the modeling of Risk-Weighted Assets (RWAs). Relatively minor model changes may lead to substantial changes in the RWA numbers. Similar problems are encountered in the Value-at-Risk (VaR)-aggregation of risks. In this article, we...
Persistent link: https://www.econbiz.de/10010338097
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Neumann series on the recursive moments of copula-dependent aggregate discounted claims
Ramli, Siti Norafidah Mohd; Jang, Jiwook - In: Risks : open access journal 2 (2014) 2, pp. 195-210
We study the recursive moments of aggregate discounted claims, where the dependence between the inter-claim time and the subsequent claim size is considered. Using the general expression for the m-th order moment proposed by Léveillé and Garrido (Scand. Actuar. J. 2001, 2, 98-110), which takes...
Persistent link: https://www.econbiz.de/10010399755
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Hidden Markov model for stock selection
Nguyen, Nguyet; Nguyen, Dung - In: Risks : open access journal 3 (2015) 4, pp. 455-473
The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market predictions. In this paper, we use HMM for...
Persistent link: https://www.econbiz.de/10011402656
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Modified Munich chain-ladder method
Merz, Michael; Wüthrich, Mario V. - In: Risks : open access journal 3 (2015) 4, pp. 624-646
The Munich chain-ladder method for claims reserving was introduced by Quarg and Mack on an axiomatic basis. We analyze these axioms, and we define a modified Munich chain-ladder method which is based on an explicit stochastic model. This stochastic model then allows us to consider claims...
Persistent link: https://www.econbiz.de/10011408600
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Modeling the yield curve of BRICS countries : parametric vs. machine learning techniques
Castello, Oleksandr; Resta, Marina - In: Risks : open access journal 10 (2022) 2, pp. 1-18
We compare parametric and machine learning techniques (namely: Neural Networks) for in-sample modeling of the yield curve of the BRICS countries (Brazil, Russia, India, China, South Africa). To such aim, we applied the Dynamic De Rezende-Ferreira five-factor model with time-varying decay...
Persistent link: https://www.econbiz.de/10013093028
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A novel implementation of Siamese type neural networks in predicting rare fluctuations in financial time series
Basu, Treena; Menzer, Olaf; Ward, Joshua; SenGupta, Indranil - In: Risks : open access journal 10 (2022) 2, pp. 1-16
Stock trading has tremendous importance not just as a profession but also as an income source for individuals. Many investment account holders use the appreciation of their portfolio (as a combination of stocks or indexes) as income for their retirement years, mostly betting on stocks or indexes...
Persistent link: https://www.econbiz.de/10013093037
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Financial liquidity and debt recovery efficiency forecasting in a small industrial enterprise
Wiśniewski, Jerzy W. - In: Risks : open access journal 10 (2022) 3, pp. 1-13
Rational small business management necessitates the development of a system for recording important internal information. Companies are obliged to collect statistical data that mainly serves fiscal needs. Exemplary use of such significant data entails financial liquidity (LIQt) and debt recovery...
Persistent link: https://www.econbiz.de/10013161536
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An approach for variable selection and prediction model for estimating the Risk-Based Capital (RBC) based on machine learning algorithms
Park, Jaewon; Shin, Minsoo - In: Risks : open access journal 10 (2022) 1, pp. 1-20
The risk-based capital (RBC) ratio, an insurance company's financial soundness system, evaluates the capital adequacy needed to withstand unexpected losses. Therefore, continuous institutional improvement has been made to monitor the financial solvency of companies and protect consumers' rights,...
Persistent link: https://www.econbiz.de/10012805414
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Explaining aggregated recovery rates
Höcht, Stephan; Wieczorek, Jakub; Zagst, Rudi - In: Risks : open access journal 10 (2022) 1, pp. 1-30
This study on explaining aggregated recovery rates (ARR) is based on the largest existing loss and recovery database for commercial loans provided by Global Credit Data, which includes defaults from 5 continents and over 120 countries. The dependence of monthly ARR from bank loans on various...
Persistent link: https://www.econbiz.de/10012805466