Analisis Pola Harga Saham dengan Modifikasi Metode Eksponen Hurst dan Box Counting

DOI:
https://doi.org/10.36456/buanamatematika.v13i2.7072
Keywords:
Stock price patterns, modified Hurst exponent method, box counting, fractal dimensionAbstract
A stock chart is a graphical representation of a stock's past performance. The dynamic pattern of stock prices is important to know because an investor wants to invest, expecting high returns with low risk. The dynamic pattern of stock prices can be known by fractal dimension analysis because the stock price graph is self-affine, which is one of the properties of fractal objects. In this study, a modification of the Hurst exponent method and box counting are used to analyze the fractal dimension. The calculated results are classified into three types, namely random, persistent and anti-persistent. Two data intervals are observed, namely January 2018-December 2021 stock prices (48 data) and January 2018-June 2022 stock prices (54 data). The resulting Hurst exponents of the two intervals are 0.043 and 0.003. Based on the resulting Hurst exponent value, the data is anti-persistent because the value 0<H<0.5. Then, the fractal dimension value obtained by applying the box-counting method is 1.547 and 1.562, meaning that Bank Rakyat Indonesia's price pattern is anti-persistent. The meaning of anti-persistent is that in certain months the stock has a high price and in the following months the stock has a low price to be traded.
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