The Efficacy of the Conditional CAPM: Improved Tests in an International Context

Stephen R. Owen, Jr.
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Abstract

Using a machine learning model known as a Long-Short Term Memory model to overcome high dimensionality obstacles, I jointly predict the conditional second moments of eight international indices and test the conditional Capital Asset Pricing Model (CAPM). My results indicate that the world price of covariance risk is equal across eight world equity markets according to the conditional CAPM. Strengths and weaknesses of the estimation process are studied. All results are assessed and reported using out-of-sample tests.
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条件CAPM的有效性:国际背景下改进的测试
利用一种被称为长短期记忆模型的机器学习模型来克服高维障碍,我联合预测了八个国际指数的条件秒矩,并测试了条件资本资产定价模型(CAPM)。我的研究结果表明,根据条件CAPM,八个世界股票市场的协方差风险的世界价格是相等的。研究了估计过程的优缺点。使用样本外测试评估和报告所有结果。
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