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.,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.,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.,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.,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.

中文翻译：

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股市中的石油和风险溢价

这项研究旨在通过双变量交叉量子图研究石油价格对与市场，规模，账面市价和动量因子相关的超额收益的预测作用，从一个新的角度探索石油与股票市场之间的联系。这项研究利用了Han等人最近开发的双变量交叉量子图方法。（2016）通过关注正式区分正常，牛市和熊市以及极端市场状态的各种分位数来分析石油和股票市场的可预测性模式。对四个地区的系统性风险溢价的研究分析表明，原油石油收益的确能获得有关股票市场超额收益的预测信息，特别是那些与市场，规模和动量因素有关的收益。然而，