This paper has two aims. The first one is to investigate the existence of chaotic structures in the oil prices, expectations of investors and stock returns by combining the Lyapunov exponent and Kolmogorov entropy, an...This paper has two aims. The first one is to investigate the existence of chaotic structures in the oil prices, expectations of investors and stock returns by combining the Lyapunov exponent and Kolmogorov entropy, and the second one is to analyze the dependence behavior of oil prices, expectations of investors and stock returns from January 02, 1990, to June06, 2017. Lyapunov exponents and Kolmogorov entropy determined that the oil price and the stock return series exhibited chaotic behavior. TAR-TR-GARCH and TAR-TR-TGARCH copula methods were applied to study the co-movement among the selected variables. The results showed significant evidence of nonlinear tail dependence between the volatility of the oil prices, the expectations of investors and the stock returns. Further, upper and lower tail dependence and comovement between the analyzed series could not be rejected. Moreover, the TAR-TR-GARCH and TAR-TR-TGARCH copula methods revealed that the volatility of oil price had crucial effects on the stock returns and on the expectations of investors in the long run.展开更多
当前,一些零售商通过自有在线平台为用户提供BOPS(Buy Online and Pick-up in Store)全渠道购物模式和个性化推荐服务。然而,在线购物存在两个弊端:一是在线购物平台隐私信息安全事件频发,引发了用户对其个人隐私信息的担忧;二是在线购...当前,一些零售商通过自有在线平台为用户提供BOPS(Buy Online and Pick-up in Store)全渠道购物模式和个性化推荐服务。然而,在线购物存在两个弊端:一是在线购物平台隐私信息安全事件频发,引发了用户对其个人隐私信息的担忧;二是在线购物极易造成用户与产品的不匹配,降低了用户在线购买意愿。为刺激在线购物需求,全渠道零售商可为用户提供无理由退货服务和个性化推荐关闭选项。基于无理由退货的市场背景,考虑用户的隐私关切行为,将市场划分为非隐私关切型市场、隐私关切型市场以及混合型市场三类,构建允许退货情形下全渠道零售商实施个性化推荐策略与否的六个决策模型,分析退货和隐私关切行为对全渠道零售商利润、定价和个性化推荐决策的影响。研究表明:(1)无论全渠道零售商是否实施个性化推荐策略,基本退货量、隐私关切型用户的隐私关切程度和市场占比的增加都会造成零售价格、市场销量和利润的减少;(2)实施个性化推荐策略后,全渠道零售商均可在三种市场中制定更高零售价格,且零售价格和零售商利润随个性化推荐精度敏感系数单调递增;(3)全渠道零售商采用个性化推荐策略后,非隐私关切型市场和隐私关切型市场的利润都实现了正向增长,且实施后零售商可在更高的隐私关切程度下开启在线购物平台,混合型市场下全渠道零售商实施个性化推荐策略受限制因素较多,即采用个性化推荐策略不一定有利于零售商利润增长。展开更多
文摘This paper has two aims. The first one is to investigate the existence of chaotic structures in the oil prices, expectations of investors and stock returns by combining the Lyapunov exponent and Kolmogorov entropy, and the second one is to analyze the dependence behavior of oil prices, expectations of investors and stock returns from January 02, 1990, to June06, 2017. Lyapunov exponents and Kolmogorov entropy determined that the oil price and the stock return series exhibited chaotic behavior. TAR-TR-GARCH and TAR-TR-TGARCH copula methods were applied to study the co-movement among the selected variables. The results showed significant evidence of nonlinear tail dependence between the volatility of the oil prices, the expectations of investors and the stock returns. Further, upper and lower tail dependence and comovement between the analyzed series could not be rejected. Moreover, the TAR-TR-GARCH and TAR-TR-TGARCH copula methods revealed that the volatility of oil price had crucial effects on the stock returns and on the expectations of investors in the long run.
文摘当前,一些零售商通过自有在线平台为用户提供BOPS(Buy Online and Pick-up in Store)全渠道购物模式和个性化推荐服务。然而,在线购物存在两个弊端:一是在线购物平台隐私信息安全事件频发,引发了用户对其个人隐私信息的担忧;二是在线购物极易造成用户与产品的不匹配,降低了用户在线购买意愿。为刺激在线购物需求,全渠道零售商可为用户提供无理由退货服务和个性化推荐关闭选项。基于无理由退货的市场背景,考虑用户的隐私关切行为,将市场划分为非隐私关切型市场、隐私关切型市场以及混合型市场三类,构建允许退货情形下全渠道零售商实施个性化推荐策略与否的六个决策模型,分析退货和隐私关切行为对全渠道零售商利润、定价和个性化推荐决策的影响。研究表明:(1)无论全渠道零售商是否实施个性化推荐策略,基本退货量、隐私关切型用户的隐私关切程度和市场占比的增加都会造成零售价格、市场销量和利润的减少;(2)实施个性化推荐策略后,全渠道零售商均可在三种市场中制定更高零售价格,且零售价格和零售商利润随个性化推荐精度敏感系数单调递增;(3)全渠道零售商采用个性化推荐策略后,非隐私关切型市场和隐私关切型市场的利润都实现了正向增长,且实施后零售商可在更高的隐私关切程度下开启在线购物平台,混合型市场下全渠道零售商实施个性化推荐策略受限制因素较多,即采用个性化推荐策略不一定有利于零售商利润增长。
