Modelling stock market prices using the open, high and closes prices: Evidence from international financial markets - Samuel Tabot Enow (International Journal of Business and Economic Sciences Applied Research (IJBESAR), 2023)
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.
Keywords: G1; G2; G4; 330; Modelling stock price; Bayesian Model; Stock market; Financial markets; VAR