16 research outputs found

    FinnGen provides genetic insights from a well-phenotyped isolated population

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    Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10–11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.publishedVersionPeer reviewe

    Retail Exposures Credit Scoring Models for Chinese Commercial Banks

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    Functional Data Analysis for Optimizing Strategies of Cash-Flow Management

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    The cash management deals with problem of automating and managing cash-flow processes. Optimization of the management processes greatly reduces overall cash handling costs. The present analysis is an empirical study of cash flows, from and to bank branches, deriving an underlying theoretical framework, which can in a reasonable way be connected with the optimal strategy. Functional data analysis is considered an appropriate framework to analyze the dynamics of the time series behavior of cash flows: since the observations are not equally spaced in time and their number is different for each series, they are converted into a collection of random curves in a space spanned by finite dimensional functional bases. A central issue in the analysis is describing specific patterns of the curves, taking into account the temporal dependence, and the dependence between curves. The analysis provides a dynamic cash management model that is applied with alternative strategies for programming a cash in transit for the difference between cash inflows and cash outflows in a fixed interval of time. As the strategies are affected by changes in the behavior of the cash flows, the dynamic model outperforms more traditional approaches in identifying the optimal strategy

    Developing and Testing Models for Replicating Credit Ratings: A Multicriteria Approach

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    Credit ratings issued by international agencies are extensively used in practice to support investment and financing decisions. Furthermore, a considerable portion of the financial research has been devoted to the analysis of credit ratings, in terms of their effectiveness, and practical implications. This paper explores the development of appropriate models to replicate the credit ratings issued by a rating agency. The analysis is based on a multicriteria classification method used in the development of the model. Special focus is laid on testing the out-of-time and out-of-sample effectiveness of the models and a comparison is performed with other parametric and non-parametric classification methods. The results indicate that using publicly available financial data, it is possible to replicate the credit ratings of the firms with a satisfactory accuracy. Copyright Springer Science + Business Media, Inc. 2005credit rating, classification, model testing, multicriteria decision aid,
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