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Navigating inflation challenges : AI-based portfolio management insights
Bareith, Tibor; Tatay, Tibor; Vancsura, László - In: Risks : open access journal 12 (2024) 3, pp. 1-16
significantly in 2021. Inflation jumped to levels not seen for 40 years in the EU. Our study aims to use artificial intelligence to … forecast inflation. We also use artificial intelligence to forecast stock index changes. Based on the forecasts, we propose … portfolio reallocation decisions to protect against inflation. The forecasting literature does not address the importance of …
Persistent link: https://www.econbiz.de/10014497442
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Implied distributions from GBPUSD risk-reversals and implication for Brexit scenarios
Clark, Iain J.; Amen, Saeed - In: Risks : open access journal 5 (2017) 3, pp. 1-17
Much of the debate around a potential British exit (Brexit) from the European Union has centred on the potential macroeconomic impact. In this paper, we instead focus on understanding market expectations for price action around the Brexit referendum date. Extracting implied distributions from...
Persistent link: https://www.econbiz.de/10011688238
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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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Hidden Markov model for stock selection
Nguyen, Nguyet; Nguyen, Dung - In: Risks : open access journal 3 (2015) 4, pp. 455-473
for the four macroeconomic variables: inflation (consumer price index (CPI)), industrial production index (INDPRO), stock …
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