Is the choice of the candlestick dimension relevant in econophysics?

Despite the enormous amount of financial data stored as candlestick charts, their high and low dimensions are often neglected in econophysics research. In this contribution, stylized facts are computed for open, close, high and low price series: Power-law decay in return distribution tails, the Hurst exponent, and multifractal scaling are investigated, as well as the accuracy of a forecast model based on systems of differential equations. Two groups of stocks were chosen for the study, one belonging to a developed market and another from an emerging market. The hypothesis that the outcomes from high and low series and the ones from open and close data come from the same distribution was rejected at the 99% confidence level in the vast majority of cases analyzed. Taking high and low candlestick dimensions into account in econophysics can improve our understanding of market dynamics. It can also be useful for trading models.