{"title":"股票收益波动性、相关性和beta的频谱分析","authors":"Shomesh E. Chaudhuri, A. Lo","doi":"10.1109/DSP-SPE.2015.7369558","DOIUrl":null,"url":null,"abstract":"We apply spectral techniques to analyze the volatility and correlation of U.S. common-stock returns across multiple time horizons at the aggregate-market and individual-firm level. Using the cross-periodogram to construct frequency band-limited measures of variance, correlation and beta, we find that volatilities and correlations change not only in magnitude over time, but also in frequency. Factors that may be responsible for these trends are proposed and their implications for portfolio construction are explored.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"34 1","pages":"232-236"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Spectral analysis of stock-return volatility, correlation, and beta\",\"authors\":\"Shomesh E. Chaudhuri, A. Lo\",\"doi\":\"10.1109/DSP-SPE.2015.7369558\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We apply spectral techniques to analyze the volatility and correlation of U.S. common-stock returns across multiple time horizons at the aggregate-market and individual-firm level. Using the cross-periodogram to construct frequency band-limited measures of variance, correlation and beta, we find that volatilities and correlations change not only in magnitude over time, but also in frequency. Factors that may be responsible for these trends are proposed and their implications for portfolio construction are explored.\",\"PeriodicalId\":91992,\"journal\":{\"name\":\"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)\",\"volume\":\"34 1\",\"pages\":\"232-236\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSP-SPE.2015.7369558\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSP-SPE.2015.7369558","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spectral analysis of stock-return volatility, correlation, and beta
We apply spectral techniques to analyze the volatility and correlation of U.S. common-stock returns across multiple time horizons at the aggregate-market and individual-firm level. Using the cross-periodogram to construct frequency band-limited measures of variance, correlation and beta, we find that volatilities and correlations change not only in magnitude over time, but also in frequency. Factors that may be responsible for these trends are proposed and their implications for portfolio construction are explored.