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引用次数: 0
摘要
本文采用 MM 估计、Theil-Sen 估计和量子回归三种稳健方法生成中国金融市场的盈利预测,并根据三种预测标准评估了这三种方法的预测准确性。我们研究了六个预测模型,预测变量包括每股收益、净利润和三个盈利能力指标。我们发现,这三种稳健方法的预测结果明显优于 OLS 方法。此外,MM 估计法和量化回归法的预测准确性也优于 Theil-Sen 方法。
Robust approach to earnings forecast: A comparison
This paper applies three robust approaches, namely, the MM estimation, the Theil–Sen estimation, and the quantile regression, to generate earnings forecasts in Chinese financial market and evaluates the forecast accuracy of these three methods based on three forecasting criteria. We examine six forecasting models where the predicted variables include earnings per share, net income, and three profitability measures. We show that the three robust methods significantly outperform the OLS method. Moreover, the MM estimation and the quantile regression have better forecast accuracy than the Theil–Sen approach.
期刊介绍:
The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.