The Non-Seasonal Holt-Winters Method for Forecasting Stock Price Returns of Companies Affected by BDS Action

Anggun Yuliarum Qur'ani, Chandra Sari Widyaningrum
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Abstract

The non-seasonal Holt-Winters method is one of the methods of smoothing theory. This method can be implemented on time series data that does not have a seasonal component. In this study, this method is used to forecast the stock price returns of companies affected by the Boycott, Divestment, and Sanctions (BDS) action. Forecasting gets very good results that can be seen from the MAPE value of modeling the six stocks affiliated with Israel that continue to carry out Zionism against Palestine is not more than 10%. This method can also accommodate the limitations of existing data while still obtaining good forecasting results. In addition, the use of several transformations of stock price returns in this case is very useful in modeling to obtain appropriate error assumptions. The forecasting results of the model formed as a whole follow the trend in the stock price of each company. To produce good forecasting results using this method, it is recommended to do forecasting in the short term. The forecasting results show that of the six company stocks, almost all of them experienced a decrease in stock price returns. Only one stock of PT Map Boga Adiperkasa Tbk has increased. This also illustrates that the BDS action influences on these companies.
预测受 BDS 行动影响的公司股价回报的非季节性 Holt-Winters 方法
非季节性 Holt-Winters 方法是平滑理论的方法之一。该方法可用于不含季节性成分的时间序列数据。在本研究中,该方法被用于预测受抵制、撤资和制裁(BDS)行动影响的公司的股票价格回报。预测结果非常好,这可以从与以色列有关联并继续对巴勒斯坦实施犹太复国主义的六只股票的建模 MAPE 值不超过 10%看出。这种方法还能适应现有数据的局限性,同时获得良好的预测结果。此外,在这种情况下,使用股票价格收益的几种变换在建模中非常有用,可以获得适当的误差假设。从整体上看,模型形成的预测结果与各公司股价的走势相一致。要使用这种方法得出良好的预测结果,建议在短期内进行预测。预测结果显示,在六家公司股票中,几乎所有股票的股价收益都有所下降。只有 PT Map Boga Adiperkasa Tbk 的一只股票上涨。这也说明了 BDS 行动对这些公司的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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