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Modeling Philippine Stock Exchange Composite Index Using Weighted Geometric Brownian Motion Forecasts

机译:使用加权几何布朗运动预测建模菲律宾证券交易所综合指数

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Philippine Stock Exchange Composite Index (PSEi) is the main stock index of the Philippine Stock Exchange (PSE). PSEi is computed using a weighted mean of the top 30 publicly traded companies in the Philippines, called component stocks. It provides a single value by which the performance of the Philippine stock market is measured. Unfortunately, these weights, which may vary for every trading day, are not disclosed by the PSE. In this paper, we propose a model of forecasting the PSEi by estimating the weights based on historical data and forecasting each component stock using Monte Carlo simulation based on a Geometric Brownian Motion (GBM) assumption. The model performance is evaluated and its forecast compared is with the results using a direct GBM forecast of PSEi over different forecast periods. Results showed that the forecasts using WGBM will yield smaller error compared to direct GBM forecast of PSEi.
机译:菲律宾证券交易所综合指数(PSEI)是菲律宾证券交易所(PSE)的主要股指。 PSEI使用菲律宾前30名公开交易公司的加权平均值计算,称为组件股票。它提供了单一的价值,通过该价值测量菲律宾股市的表现。不幸的是,这些重量可能因每个交易日而变化,而不是PSE。在本文中,我们提出了一种通过基于历史数据估计权重预测PSEI的模型,并根据几何褐色运动(GBM)假设使用Monte Carlo仿真来预测每个组件库存。评估模型性能及其预测,比较了在不同预测期间使用PSEI的直接GBM预测结果。结果表明,与PSEI的直接GBM预测相比,使用WGBM的预测将产生较小的错误。

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