The Analysis of Multifractal System, Long-Term Memory, and Weak Form Efficiency of the Returns in Tehran Stock Exchange

Abstract

Studying and recognizing the behaviour of securities returns has always been the focus of investors and researchers since the dawn of capital markets. Based on the statistics of the last decade, the stock market has been one of the major centres for making investment and getting high returns. Analysis and forecasting the price of financial assets has always been an intriguing topic in both scientific and practical disciplines which created various challenges for financial analysis. Chaos theory and fractal analysis are the latest theories in this regard. The present study has reviewed the information on Tehran Stock Exchange (TSE) companies' returns between 2014 and 2018 in monthly intervals to measure the multifractal system, long-term memory (LTM), and weak-form efficiency of the stock return variable. The aim of the study has been addressed by using Hurst's rescaled range (R/S) statistic model. Any R/S larger than 0.5 indicated a correlation between future stock returns and previous returns and that previous data influence the market. Consequently, it is not a random market but has an LTM, a fractal dimension, and is relevant to the Efficient Market Hypothesis (EMH) that confirms these variables.