{"title":"提高OLS模型套期保值性能的一种新方法","authors":"Chongwon Kim, Hyeonjong Jung, Hyoung-Goo Kang","doi":"10.3905/jai.2022.1.176","DOIUrl":null,"url":null,"abstract":"The sensitivity of VIX futures to market movements changes over time with changes in market risk. Accordingly, in the case of using the OLS (ordinary least squares) model to hedge S&P 500 exposure with VIX futures, hedge ratios are affected by changes in risk appetite, which in turn contributes to the overall hedging performance as well as the asymmetry of the performance distribution. The conventional OLS approach does not effectively reflect this phenomenon in the model. In this study, the authors explore a new approach to improving hedging performance in the OLS model. They introduce an interaction term between the VIX and VIX futures returns into the OLS model. They find that the hedge ratios derived by the new approach provide better hedging results compared to the univariate OLS model in terms of mean return and downside risk protection, and also improve the asymmetry of the performance distribution. They extend their research to compare it with the performance of the dynamic conditional correlation (DCC)-generalized autoregressive conditional heteroskedasticity (GARCH) model. The new approach also shows better results than the DCC-GARCH approach. They obtain the same results in case studies of the Global Financial Crisis and the COVID-19 pandemic, and also in applying a trading strategy to each hedging methodology.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2022-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A New Approach to Improving Hedging Performance in the OLS Model\",\"authors\":\"Chongwon Kim, Hyeonjong Jung, Hyoung-Goo Kang\",\"doi\":\"10.3905/jai.2022.1.176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The sensitivity of VIX futures to market movements changes over time with changes in market risk. Accordingly, in the case of using the OLS (ordinary least squares) model to hedge S&P 500 exposure with VIX futures, hedge ratios are affected by changes in risk appetite, which in turn contributes to the overall hedging performance as well as the asymmetry of the performance distribution. The conventional OLS approach does not effectively reflect this phenomenon in the model. In this study, the authors explore a new approach to improving hedging performance in the OLS model. They introduce an interaction term between the VIX and VIX futures returns into the OLS model. They find that the hedge ratios derived by the new approach provide better hedging results compared to the univariate OLS model in terms of mean return and downside risk protection, and also improve the asymmetry of the performance distribution. They extend their research to compare it with the performance of the dynamic conditional correlation (DCC)-generalized autoregressive conditional heteroskedasticity (GARCH) model. The new approach also shows better results than the DCC-GARCH approach. They obtain the same results in case studies of the Global Financial Crisis and the COVID-19 pandemic, and also in applying a trading strategy to each hedging methodology.\",\"PeriodicalId\":45142,\"journal\":{\"name\":\"Journal of Alternative Investments\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2022-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Alternative Investments\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3905/jai.2022.1.176\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Alternative Investments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/jai.2022.1.176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
A New Approach to Improving Hedging Performance in the OLS Model
The sensitivity of VIX futures to market movements changes over time with changes in market risk. Accordingly, in the case of using the OLS (ordinary least squares) model to hedge S&P 500 exposure with VIX futures, hedge ratios are affected by changes in risk appetite, which in turn contributes to the overall hedging performance as well as the asymmetry of the performance distribution. The conventional OLS approach does not effectively reflect this phenomenon in the model. In this study, the authors explore a new approach to improving hedging performance in the OLS model. They introduce an interaction term between the VIX and VIX futures returns into the OLS model. They find that the hedge ratios derived by the new approach provide better hedging results compared to the univariate OLS model in terms of mean return and downside risk protection, and also improve the asymmetry of the performance distribution. They extend their research to compare it with the performance of the dynamic conditional correlation (DCC)-generalized autoregressive conditional heteroskedasticity (GARCH) model. The new approach also shows better results than the DCC-GARCH approach. They obtain the same results in case studies of the Global Financial Crisis and the COVID-19 pandemic, and also in applying a trading strategy to each hedging methodology.
期刊介绍:
The Journal of Alternative Investments (JAI) provides you with cutting-edge research and expert analysis on managing investments in hedge funds, private equity, distressed debt, commodities and futures, energy, funds of funds, and other nontraditional assets. JAI is the official publication of the Chartered Alternative Investment Analyst Association (CAIA®). JAI provides you with challenging ideas and practical tools to: •Profit from the growth of hedge funds and alternatives •Determine the optimal mix of traditional and alternative investments •Measure and track portfolio performance •Manage your alternative investment portfolio with proven risk management practices