{"title":"洞察、趋势与前沿:信息时代金融与风险建模的文献综述(2008-2019)","authors":"Markus Vogl, P. Roetzel","doi":"10.2139/ssrn.3764570","DOIUrl":null,"url":null,"abstract":"This study provides an overview of the model evolution and research trends in the field of financial and risk modelling by applying a bibliometric approach from 2008–2019 and an overall citation network analysis. We present a content analysis of contributing authors, countries, journals, main topics, agreements, disagreements and frontiers within the research community and highlight quantitative features such as implemented models, aggregated model-family combinations and algorithms. Moreover, we describe the data sets employed by researchers. Finally, we discuss insights, such as the main statement, namely the non-existence of a “single-best”-approach as well as the future prospects of our findings.","PeriodicalId":367100,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Corporate Finance & Governance (Topic)","volume":"7 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Insights, Trends and Frontiers: A Literature Review on Financial and Risk Modelling in the Information Age (2008-2019)\",\"authors\":\"Markus Vogl, P. Roetzel\",\"doi\":\"10.2139/ssrn.3764570\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study provides an overview of the model evolution and research trends in the field of financial and risk modelling by applying a bibliometric approach from 2008–2019 and an overall citation network analysis. We present a content analysis of contributing authors, countries, journals, main topics, agreements, disagreements and frontiers within the research community and highlight quantitative features such as implemented models, aggregated model-family combinations and algorithms. Moreover, we describe the data sets employed by researchers. Finally, we discuss insights, such as the main statement, namely the non-existence of a “single-best”-approach as well as the future prospects of our findings.\",\"PeriodicalId\":367100,\"journal\":{\"name\":\"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Corporate Finance & Governance (Topic)\",\"volume\":\"7 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Corporate Finance & Governance (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3764570\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Corporate Finance & Governance (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3764570","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Insights, Trends and Frontiers: A Literature Review on Financial and Risk Modelling in the Information Age (2008-2019)
This study provides an overview of the model evolution and research trends in the field of financial and risk modelling by applying a bibliometric approach from 2008–2019 and an overall citation network analysis. We present a content analysis of contributing authors, countries, journals, main topics, agreements, disagreements and frontiers within the research community and highlight quantitative features such as implemented models, aggregated model-family combinations and algorithms. Moreover, we describe the data sets employed by researchers. Finally, we discuss insights, such as the main statement, namely the non-existence of a “single-best”-approach as well as the future prospects of our findings.