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Small-sample tests for stock return predictability with possibly non-stationary regressors and GARCH-type effects

机译:具有可能非稳定性回归和GARCH型效果的股票回归可预测性的小样本测试

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We develop a simulation-based procedure to test for stock return predictability with multiple regressors. The process governing the regressors is left completely free and the test procedure remains valid in small samples even in the presence of non-normalities and GARCH-type effects in the stock returns. The usefulness of the new procedure is demonstrated in a simulation study and by examining the ability of a group of financial variables to predict excess stock returns. We find some evidence of predictability during the period 1948-2014, driven entirely by the term spread. This empirical evidence, however, is much weaker over subsamples. (C) 2020 The Author(s). Published by Elsevier B.V.
机译:我们开发了一种基于仿真的过程,以测试具有多元回归的库存回报可预测性。 管理回归的过程完全免费留下,即使在股票回报中的非归属和Garch类型的效果存在下,测试程序也仍然有效。 在模拟研究中展示了新程序的有用性,并通过检查一组金融变量预测超额股票回报的能力。 我们在1948 - 2014年期间发现了一些可预测性的证据,完全由术语传播。 然而,这种经验证据越弱了副页。 (c)2020提交人。 elsevier b.v出版。

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