{"title":"好的风险度量、糟糕的统计假设、难看的风险预测","authors":"Michael Michaelides, Niraj Poudyal","doi":"10.1111/fire.12368","DOIUrl":null,"url":null,"abstract":"<p>This paper proposes the time-heterogeneous Student's <i>t</i> autoregressive model as an alternative to the various volatility forecast models documented in the literature. The empirical results indicate that: (i) the proposed model has better forecasting performance than other commonly used models, and (ii) the problem of reliable risk measurement arises primarily from the model risk associated with risk forecast models rather than the particular risk measure for computing risk. Based on the results, the paper makes recommendations to regulators and practitioners.</p>","PeriodicalId":47617,"journal":{"name":"FINANCIAL REVIEW","volume":"59 2","pages":"519-543"},"PeriodicalIF":2.6000,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/fire.12368","citationCount":"0","resultStr":"{\"title\":\"Good risk measures, bad statistical assumptions, ugly risk forecasts\",\"authors\":\"Michael Michaelides, Niraj Poudyal\",\"doi\":\"10.1111/fire.12368\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper proposes the time-heterogeneous Student's <i>t</i> autoregressive model as an alternative to the various volatility forecast models documented in the literature. The empirical results indicate that: (i) the proposed model has better forecasting performance than other commonly used models, and (ii) the problem of reliable risk measurement arises primarily from the model risk associated with risk forecast models rather than the particular risk measure for computing risk. Based on the results, the paper makes recommendations to regulators and practitioners.</p>\",\"PeriodicalId\":47617,\"journal\":{\"name\":\"FINANCIAL REVIEW\",\"volume\":\"59 2\",\"pages\":\"519-543\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/fire.12368\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FINANCIAL REVIEW\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/fire.12368\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FINANCIAL REVIEW","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/fire.12368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
摘要
本文提出了时间异质性 Student's t 自回归模型,作为文献中各种波动率预测模型的替代。实证结果表明(i) 所提出的模型比其他常用模型具有更好的预测性能,(ii) 可靠的风险度量问题主要来自与风险预测模型相关的模型风险,而不是计算风险的特定风险度量。根据研究结果,本文向监管机构和从业人员提出了建议。
Good risk measures, bad statistical assumptions, ugly risk forecasts
This paper proposes the time-heterogeneous Student's t autoregressive model as an alternative to the various volatility forecast models documented in the literature. The empirical results indicate that: (i) the proposed model has better forecasting performance than other commonly used models, and (ii) the problem of reliable risk measurement arises primarily from the model risk associated with risk forecast models rather than the particular risk measure for computing risk. Based on the results, the paper makes recommendations to regulators and practitioners.