In the present paper, a wavelet method is proposed to study the impact of electronic media on economic situation. More precisely, wavelet techniques are applied versus classical methods to analyze economic indices in the market. The technique consists firstly of filtering the data from unprecise circumstances (noise) to construct next a wavelet denoised contingency table. Next, a thresholding procedure is applied to such a table to extract the essential information porters. The resulting table subject finally to correspondence analysis before and after thresholding. As a case of study, the KSA 2030-vision is considered in the empirical part based on electronic and social media. Effects of the electronic media texts about the trading 2030 vision on the Saudi and global economy has been studied. Recall that the Saudi market is the most important representative market in the GCC continent. It has both regional and worldwide influence on economies and besides, it is characterized by many political, economic and financial movements such as the worldwide economic NEOM project. The findings provided in the present paper may be applied to predict the future situation of markets in GCC region and may constitute therefore a guide for investors to decide about investing or not in these markets.

In the present paper, we propose a wavelet method to study the impact of electronic media on economic situations. We precisely apply wavelet techniques versus classical methods to analyze economic indices in the market. The technique consists firstly in filtering the data from unprecise circumstances (noise) to construct next a wavelet denoised contingency table. Next, a thresholding procedure is applied to such a table to extract the essential information porters. The resulting tables subject finally to correspondence analysis before and after thresholding. As a case of study, we are empirically concerned with the 2030 KSA vision in electronic and social media. Effects of the electronic media texts about the trading 2030 Vision on the Saudi and global economy have been studied. Recall that the Saudi market is the most important representative market in the GCC continent. It has both regional and worldwide influence on economies and besides, it is characterized by many political, economic, and financial movements such as the worldwide economic NEOM project. The findings provided in the present paper may be applied to predict future GCC markets situation and thus may be a basis for investors’ decisions in such markets.

The present paper is concerned with the study of the quality of life index. Such an index has become an important index for measuring the well-being of individuals. However, the quality of life index is always subjective, intangible, and often hard to quantify with precision due to the lack of quantitative models. The main goal of the present paper is thus to propose a mathematical, quantitative model for the measurement of a quality of life index. The main novelty is firstly the construction of a wavelet dynamic multiscale model to quantify and investigate the effect of time scale on the quality of life index measuring. The proposed procedure is acted empirically on a sample corresponding to Saudi Arabia as a case study during the period from 2003 to 2020 as part of the 2030 vision plan. Saudi Arabia has implemented the so-called 2030 vision plan where quality of life improvement is one of the main goals. The findings show that wavelets are capable of localizing the time-wise behavior of the index contrarily to classical studies, which estimate a global view of the index. Moreover, the study shows the link between the quality of life behavior and many other indices.

In the present paper, we investigate the impact of the timescale factor on the quality of life index behavior on specific time intervals characterized by the presence of socio-economic, political, and/or health severe movements such as pandemics and crises. We essentially aim to show that effectively the quality of life measuring based on a single index in the existing studies may be described more adequately by a variable index due to the social, political, economic, and also healthy environment. The variability discovered is expressed by the existence and the estimation of a multi-index instead of a single one relatively to many factors. Our focus is mainly on the effect of the COVID-19 pandemic on the quality of life. Our model is applied empirically to a sample corresponding to Saudi Arabia as a case of study during the period from January 1990 to December 2021 as the main period affected by the COVID-19 pandemic. The sample is based on social media conversations and texts discussing and describing the satisfaction with the quality of life. The study confirms effectively that the role of the timescale factor is more described when considering a multi-index rather than measurement on the whole time interval.

In the present article, we investigate the impact of the timescale factor on the quality of life index behaviour on specific time intervals characterized by the presence of socio‐economic, political, and/or health severe movements such as pandemics and crises. We essentially aim to show that effectively the quality of life evaluation based on a single index as in the existing studies may be described more adequately by a variable index due to the social, political, economic, and also healthy environment. The variability discovered is expressed by the existence and the estimation of a multi‐index instead of a single one with relatively too many factors. Our focus is mainly on the effect of the COVID‐19 pandemic and crises or crashes on the quality of life. It turns out that the first essays of empirical treatments of such a series bring out a fractal/multifractal aspect. This motivates our main idea reposing on the fractal/multifractal structure of the data to construct a quantitative model based on wavelets combined with change‐point analysis. Our model is applied empirically on a sample corresponding to Saudi Arabia as a case of study during the period from January 1990 to December 2021. The end of this period is strongly affected by the COVID‐19 pandemic. The sample is based on social media conversations and texts discussing and describing the satisfaction with the quality of life. The study confirms effectively that the role of the timescale factor is more described when considering a multi‐index rather than measurement on the whole time interval. Besides, this multi‐index is clearly illustrated by means of the multifractal spectra of the data used.