Modelling Stock Market Prices Using the Open, High and Closes Prices. Evidence from International Financial Markets

Samuel Tabot Enow
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引用次数: 5

Abstract

Purpose: Modelling security prices seem to be an ending debate in finance literature due to no clear consensus on behavioral patterns. Knowledge of stock price movement has always been an important source of information that is much needed in asset pricing and trading strategies. The aim of this study was to model stock market prices using six international markets as a sample. Design/methodology/approach: This study made use of the Bayesian Time-Varying coefficient for a five-year period from January 2, 2018, to January 2, 2023. Finding: The findings of this study revealed that there is strong empirical evidence that the returns of a security can be modelled using the open, high and low prices. Research limitations/implications: This implies that the drift in stock price movement can be better explained by observing the lag values of the open, high and low prices which may be an important tool for short term traders and incorporated in volatility estimation. Also, the lag values of the open, high and low price movements explain more than 98% of changes in the closing price. Originality/value: As per the author’s knowledge, this study is the first to model stock market prices using the open, high and low prices for multiple international markets.
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使用开盘价、高价和收盘价对股票市场价格进行建模。来自国际金融市场的证据
目的:由于对行为模式没有明确的共识,模拟证券价格似乎是金融文献中的一场结束辩论。股票价格波动的知识一直是资产定价和交易策略中急需的重要信息来源。本研究的目的是以六个国际市场为样本,对股票市场价格进行建模。设计/方法/方法:本研究使用贝叶斯时变系数,从2018年1月2日到2023年1月1日,为期五年。发现:这项研究的结果表明,有强有力的经验证据表明,证券的回报可以使用公开价格、高价格和低价格进行建模。研究局限性/影响:这意味着可以通过观察开盘价、高价和低价的滞后值来更好地解释股价波动的漂移,这可能是短期交易者的重要工具,并纳入波动性估计。此外,开盘价、高价和低价的滞后值解释了收盘价98%以上的变化。原创性/价值:据作者所知,本研究首次使用多个国际市场的公开、高和低价格对股票市场价格进行建模。
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发文量
8
审稿时长
5 weeks
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