{"title":"公司债券收益波动的宏观经济和金融决定因素","authors":"Belén Nieto, A. Novales, Gonzalo Rubio","doi":"10.1142/S2010139215500214","DOIUrl":null,"url":null,"abstract":"In this paper, we address the issue of how macroeconomic conditions affect corporate bond volatility. We employ the GARCH-MIDAS multiplicative two-component model of volatility that distinguishes the short-term dynamics from the long-run component of volatility. Both the in-sample and out-of-sample analysis show that recognizing the existence of a stochastic low-frequency component captured by macroeconomic and financial indicators may improve the fit of the model to actual bond return data, relative to the constant long-run component embedded in a typical GARCH model.","PeriodicalId":45339,"journal":{"name":"Quarterly Journal of Finance","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Macroeconomic and Financial Determinants of the Volatility of Corporate Bond Returns\",\"authors\":\"Belén Nieto, A. Novales, Gonzalo Rubio\",\"doi\":\"10.1142/S2010139215500214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we address the issue of how macroeconomic conditions affect corporate bond volatility. We employ the GARCH-MIDAS multiplicative two-component model of volatility that distinguishes the short-term dynamics from the long-run component of volatility. Both the in-sample and out-of-sample analysis show that recognizing the existence of a stochastic low-frequency component captured by macroeconomic and financial indicators may improve the fit of the model to actual bond return data, relative to the constant long-run component embedded in a typical GARCH model.\",\"PeriodicalId\":45339,\"journal\":{\"name\":\"Quarterly Journal of Finance\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2015-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quarterly Journal of Finance\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1142/S2010139215500214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quarterly Journal of Finance","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1142/S2010139215500214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Macroeconomic and Financial Determinants of the Volatility of Corporate Bond Returns
In this paper, we address the issue of how macroeconomic conditions affect corporate bond volatility. We employ the GARCH-MIDAS multiplicative two-component model of volatility that distinguishes the short-term dynamics from the long-run component of volatility. Both the in-sample and out-of-sample analysis show that recognizing the existence of a stochastic low-frequency component captured by macroeconomic and financial indicators may improve the fit of the model to actual bond return data, relative to the constant long-run component embedded in a typical GARCH model.
期刊介绍:
The Quarterly Journal of Finance publishes high-quality papers in all areas of finance, including corporate finance, asset pricing, financial econometrics, international finance, macro-finance, behavioral finance, banking and financial intermediation, capital markets, risk management and insurance, derivatives, quantitative finance, corporate governance and compensation, investments and entrepreneurial finance.