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Research on Application of Combination Forecasting Model in Markowitz Model

机译:组合预测模型在Markowitz模型中的应用研究

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we make a new definition for the Markowitz model that uses the prediction errors as risk measure and the Generalized Autoregressive Conditional heteroskedasticity (GARCH) predictor as the future stock returns.Using the prediction errors of the TGARCH model to calculate the risk,we can figure out the problem of the kurtosis and skewness distribution of returns in order that it improves the traditional Markowitz model and has better efficient frontier.With the combination of TGARCH and grey predictors,the new model presents a higher accurate prediction.Taking into consideration of the stock characteristic,a new combination forecasting model is proposed.On the basic theory,we use TGARCH to predict the volatility characteristic and GM to predict the trend characteristic.Combined with the above two methods,we can get the new combination forecasting model.Through the out-of-sample forecast method,we can obtain the optimal portfolio,proving that the results are more accurate on shorter horizons.
机译:我们对Markowitz模型进行了新的定义,该模型使用预测误差作为风险度量,并使用广义自回归条件异方差(GARCH)预测器作为未来股票收益。使用TGARCH模型的预测误差来计算风险,我们可以得出为了改善传统的Markowitz模型并具有更好的有效前沿,存在收益率峰度和偏度分布的问题。结合TGARCH和灰色预测因子,新模型提供了更高的准确预测。在基本理论的基础上,采用TGARCH方法预测波动率特征,采用GM方法预测趋势特征。结合以上两种方法,可以得到新的组合预测模型。样本预测方法,我们可以获得最优的投资组合,证明在较短的水平方向上结果更准确ns。

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