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Territorial risk classification using spatially dependent frequency-severity models
Shi, Peng; Shi, Kun - In: Astin bulletin : the journal of the International … 47 (2017) 2, pp. 437-465
Persistent link: https://www.econbiz.de/10011729578
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Risk measures-based cluster methods for finance
Guedes, Pablo Cristini; Müller, Fernanda Maria; Righi, … - In: Risk management : an international journal 25 (2023) 1, pp. 1-56
Persistent link: https://www.econbiz.de/10013490814
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A clustering approach and a rule of thumb for risk aggregation
Di Lascio, F. Marta L.; Giammusso, Davide; Puccetti, … - In: Journal of banking & finance 96 (2018), pp. 236-248
Persistent link: https://www.econbiz.de/10011967212
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A Clustering Approach and a Rule of Thumb for Risk Aggregation
Di Lascio, F. Marta L. - 2018
risks. In this paper, we propose to apply a clustering procedure in order to partition a risk portfolio into independent …
Persistent link: https://www.econbiz.de/10012932252
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Credit risk clustering in a business group : which matters more, systematic or idiosyncratic risk?
Li, Feng; He, Zhuojing - In: Cogent economics & finance 7 (2019) 1, pp. 1-23
clustering". We also study the driving forces of the credit risk clustering in CEC business group in China. Our empirical … analysis shows that the credit risk clustering varies over time and exhibits different patterns across firm pairs in a business … group. We also investigate the impacts of systematic and idiosyncratic factors on credit risk clustering. We find that the …
Persistent link: https://www.econbiz.de/10012024047
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Chapter 21 Clusters of Generation Z and Travel Risks Perception: Constraining vs. Push–Pull Factors
Dragin, Aleksandra S.; Majstorović, Nebojša; … - In: The Emerald handbook of destination recovery in tourism …, (pp. 375-395). 2022
No matter the fact that it represents significant tourist contingents, Generation Z (Gen Z) is still insufficiently known regarding the main habits, fears or behaviours in changed circumstances. The main objective of this research is to examine the differences in travel risks perception among...
Persistent link: https://www.econbiz.de/10015392759
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Machine learning risk models
Kakushadze, Zura; Yu, Willie - In: Journal of risk & control 6 (2019) 1, pp. 37-64
Persistent link: https://www.econbiz.de/10012237599
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Risk profiling of Indian commercial banks - a clustering approach
Vashisht, Shailja; Sarva, Mahesh - In: Afro-Asian Journal of Finance and Accounting : AAJFA 14 (2024) 6, pp. 854-872
Persistent link: https://www.econbiz.de/10015326170
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Identifying risk-averse low-diameter clusters in graphs with stochastic vertex weights
Rysz, Maciej; Mahdavi Pajouh, Foad; Krokhmal, Pavlo; … - In: Risk management approaches in engineering applications, (pp. 89-108). 2018
Persistent link: https://www.econbiz.de/10011870000
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The SMEs’ perception of financial risks in the context of cluster cooperation
Havierniková, Katarína; Kordoš, Marcel - In: Quantitative finance and economics 3 (2019) 3, pp. 586-607
Persistent link: https://www.econbiz.de/10012176621