{"title":"股票市场的石油和风险溢价","authors":"Satish Kumar, Rıza Demirer, A. Tiwari","doi":"10.2139/ssrn.3481593","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.\n\n\nDesign/methodology/approach\nThis study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.\n\n\nFindings\nThe study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.\n\n\nPractical implications\nThe findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.\n\n\nOriginality/value\nThis study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.\n","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"122 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Oil and Risk Premia in Equity Markets\",\"authors\":\"Satish Kumar, Rıza Demirer, A. Tiwari\",\"doi\":\"10.2139/ssrn.3481593\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.\\n\\n\\nDesign/methodology/approach\\nThis study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.\\n\\n\\nFindings\\nThe study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.\\n\\n\\nPractical implications\\nThe findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.\\n\\n\\nOriginality/value\\nThis study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.\\n\",\"PeriodicalId\":292025,\"journal\":{\"name\":\"Econometric Modeling: Commodity Markets eJournal\",\"volume\":\"122 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Modeling: Commodity Markets eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3481593\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Modeling: Commodity Markets eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3481593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Purpose
This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.
Design/methodology/approach
This study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.
Findings
The study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.
Practical implications
The findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.
Originality/value
This study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.