Analysis of Structural Changes in Financial Datasets Using the Breakpoint Test and the Markov Switching Model

Abstract

The price movements of commodities are determined by changes in the expectations about future economic variables. Crude oil price is non-stationary, highly volatile, and unstructured in nature, which makes it very difficult to predict over short-to-medium time horizons. Some analysts have indicated that the difficulty in forecasting the crude oil price is due to the fact that economic models cannot consistently show evidence of a strong connection between commodities and economic fundamentals, and, as a result, regarded the idea that economic fundamentals help predict price values as random luck. This study aimed to overcome the limitations of the economic models through the detection of structural changes as well as breaks in the data, using a breakpoint test. The Markov switching model is used to address the price patterns that led to a different market state. The results show that there are several changes as well as breaks in the estimated model. Moreover, there is an asymmetric correlation between the crude oil price and the GDP.

A Markov Switching Approach in Assessing Oil Price and Stock Market Nexus in the Last Decade: The Impact of the COVID-19 Pandemic

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Application of a breakpoint model to population growth in Türkiye

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“…where '   u u is the residual of the limited sum of squares, ' j j u u is the sum of squared residuals from a sample drawn from a larger sample j, the number of parameters is denoted with k, and T marks the whole number of observations (Phoong, Phoong, and Phoong, 2020).…”

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