Forecasting Stock Prices Through Exponential Smoothing Techniques in The Creative Industry of The UK Stock Market

Md Aminur Rahman

doi:10.55927/ijabm.v3i3.9104

Authors

Md Aminur Rahman University for the Creative Arts

DOI:

https://doi.org/10.55927/ijabm.v3i3.9104

Keywords:

Forecasting Stock Price, Creative Industry, Exponential Smoothing Techniques, Random Walk Model, Structural Breakpoints

Abstract

The purpose of this study is to thoroughly and critically evaluate the predictive ability of exponential smoothing approaches in the UK stock market's creative industry. Because of this, weekly closing price data were gathered for the sample period spanning October 13, 2003, to February 2, 2024, as determined by the FTSE-350 General Industrial Index and the five creative industry enterprises. Using the multiple breakpoints test of Bai-Perron's L + 1 vs. L sequentially determined breaks, the plain data of the sub-sample period for each selected series has been determined. The weekly closing prices are not normally distributed, as can be shown by looking at the descriptive statistics table, histograms, and kernel density graphs from each series. verifies, through the use of test papers, that the weekly closing prices of each series are not random. Furthermore, the Chow-Denning joint test's variance ratio establishes the martingale model's applicability to all series. Additionally, according to the great majority of the programs, serial auto-correlation is not present at the first difference. Test of serial correlation for LB. Moreover, it seems that none of the series have a unit root at the first difference, according to the results of the Augmented Dickey Fuller unit root test. As a result, statistical research showed that the creative sector's home, the London Stock Exchange (LSE), was weak-form inefficient and had consistent stock values across the testing period. Holt's double exponential smoothing technique has helped to enhance the short-term forecastability of stock prices for the FTSE 350 General Industrial Index and most creative industry series

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