尼日利亚股票价格的随机预测:几何布朗运动模型的应用

Q4 Economics, Econometrics and Finance International Journal of Banking, Accounting and Finance Pub Date : 2021-08-16 DOI:10.47941/IJF.646
A. Toby, Samuel Azubuike Agbam
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引用次数: 0

摘要

目的:本研究的目的是建模和模拟尼日利亚股票市场的趋势和行为模式,从而在几何布朗运动(GBM)框架内预测未来的股票价格。方法:该方法包括将预测的每日收盘价与实际价格进行比较,以评估预测模型的准确性。基于具有漂移:连续性、正态性和马尔可夫趋势的GBM模型假设,研究了尼日利亚证券交易所10只上市股票4年(2015 - 2018)的历史收盘价。本研究的样本是基于最连续交易的股票。结果表明,在模拟中,有一些实际股价位于轨迹实现之外,可能来自GBM模型。因此,该模型不能准确预测某些上市股票的价格行为。平均绝对百分比误差值越高,模型的预测能力越长。一至两年持有期的MAPE值为50%及以下,三年持有期的MAPE值高于50%。对理论、实践和政策的独特贡献:MAPE和定向预测精度方法为短期内GBM模型的准确性提供了支持。这意味着GBM在一到两年内是一个合理的预测模型,但对于三年,它是一个不准确的预测器。建议以牺牲其他参与者利益为主要动机的技术分析师在任何持有期间都应识别出高波动性的投资组合,以进行有效预测。以长期持有为投资策略的投资者应更多地关注低市值股票,而不是大市值股票。这是对理论、实践和政策的独特贡献。
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Stochastic Forecasting of Stock Prices in Nigeria: Application of Geometric Brownian Motion Model
Purpose:  The purpose of the study is to model and simulate the trends and behavioral patterns in The Nigerian Stock Market and hence predict the future stock prices within the Geometric Brownian Motion (GBM) framework. Methodology: The methodology involves a comparison of forecasted daily closing prices to actual prices in order to evaluate the accuracy of the prediction model. Based on the model assumptions of the GBM with drift: continuity, normality and Markov tendency, the study investigated four years (2015 - 2018) of historical closing prices of ten stocks listed on The Nigerian Stock Exchange. The sample for this study is based on the most continuously traded stocks. Findings: The results show that in the simulation there are some actual stock prices located outside trajectory realization that may be from GBM model. Thus, the model did not predict accurately the price behavior of some of the listed stocks.  The predictive power of the model is declining towards the longer the evaluated time frame proven by the higher value of the mean absolute percentage error. The value of the MAPE is 50% and below for the one- to two-year holding periods, and above 50% for the three-year holding period. Unique Contribution to theory, Practice and Policy:  The MAPE and directional prediction accuracy method provide support that over short periods the GBM model is accurate. Meaning that the GBM is a reasonable predictive model for one or two years, but for three years, therefore, it is an inaccurate predictor. It is recommended that the technical analyst whose primary motive is to make gain at the expense of other participants should identify high volatile portfolio in any holding period for effective prediction Investors with long-range holding position as investment strategy should concentrate more on low capitalized stocks rather than stocks with large market capitalization. This is a unique contribution to theory, practice and policy.
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来源期刊
International Journal of Banking, Accounting and Finance
International Journal of Banking, Accounting and Finance Economics, Econometrics and Finance-Finance
CiteScore
0.80
自引率
0.00%
发文量
12
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