Scaling analysis of time series of daily prices from stock markets of transitional economies in the Western Balkans

TL;DR

This study investigates the scaling properties of stock market index time series in Western Balkans' developing economies, revealing correlations, anti-correlations, and periodic influences that vary with economic maturity.

Contribution

It applies three analytical methods to compare scaling behaviors of stock markets in developing versus developed economies, highlighting the impact of economic maturity on market dynamics.

Findings

Scaling behavior present in all analyzed SMI data sets.

Transition from long-range correlation to anti-correlation with economic development.

Identification of a ~90-day periodic influence on SMI data.

Abstract

In this paper we have analyzed scaling properties of time series of stock market indices (SMIs) of developing economies of Western Balkans, and have compared the results we have obtained with the results from more developed economies. We have used three different techniques of data analysis to obtain and verify our findings: Detrended Fluctuation Analysis (DFA) method, Detrended Moving Average (DMA) method, and Wavelet Transformation (WT) analysis. We have found scaling behavior in all SMI data sets that we have analyzed. The scaling of our SMI series changes from long-range correlated to slightly anti-correlated behavior with the change in growth or maturity of the economy the stock market is embedded in. We also report the presence of effects of potential periodic-like influences on the SMI data that we have analyzed. One such influence is visible in all our SMI series, and appears at a period $T_{p}\approx 90$ days. We propose that the existence of various periodic-like influences on SMI data may partially explain the observed difference in types of correlated behavior of corresponding scaling functions.