Data for: Chaos in financial markets: Research insights, measures, and influences
Description
The 180 literature sample is scrutinized and used to perform a meta-literature review on chaotic detection and behaviour in financial markets to provide valuable insights on prolific authors and affiliations, productive institutions, countries, and journals, trending topics, and impactful studies. The sampled documents are linked to 347 authors, published in 98 journals, with stock indices and currency exchange as the top-2 dominant asset markets. China, Canada, Italy and the US accounted for 23.9% of the studies. Lahmiri Salim and Serletis Apostolos are joint prolific authors, with the former being the most influential author. Chaos, Solitons and Fractals, and ESCA School of Management are respectfully the most productive and impactful journal and institution. Our content analysis provide insights on the evidence for, and against chaos in financial markets using the empirical positions of the literature sample.
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The search and data extraction were carried out on February 12, 2024 from the Scopus database. The literature search was undertaken based on a multi-step inclusion and exclusion criteria. At the initial stage, we formulated 38 keywords combination (paired keywords) using “Chaos” (or “Chaos Theory”) against variant words of financial markets as our search query, from published documents whose titles, abstracts, and/or keywords include our search phrases, in no order of importance. The duration window for the search documents is limited to January 1994 through to December 2023. This 30-year data collection window was purposely chosen to capture major shocks that may have had significant impacts on financial markets, with ramification of influencing market complexities, as found in the studies of Alves et al., (2018) and Alves (2022). The global events considered includes, the 1997 Asian stock market crises, September 11 Attack on United States, 2007/2008 Global Financial Crises, Brexit, Covid-19 pandemic, and the recent Russia-Ukraine geopolitical unrest. In our subsequent step, we limited the data collection to capture areas of “Mathematics”, “Economics, Econometrics, and Finance”, “Business, Management, and Accounting” and “Multidisciplinary” fields. Due to the extensive coverage of research on chaotic behaviour in asset markets, it was decided to open up the search exercise to areas of finance and its closely related disciplines. This was to ensure that key documents are not missed from querying the Scopus database. Next, we filtered to include only English Language written documents, book chapters, journal articles, and conference papers. Sourced documents designated as final publications were considered, giving a total sample of 734. We then screened the sourced documents to remove 96 duplicates, reducing our sample to 638. Lastly, we review the content of the abstracts of the extracts to determine the relevance of each to chaotic detection and behaviour in financial markets. Upon the relevance-scrutinizing exercise, our final sample reduces to 180 documents. We manually perused the fields of the final extracts to clean and fix special characters of names, research titles, keywords, among others, mainly to confirm that such details correspond with the online published documents. The filtered and screened documents are now used as our sourced data for the meta-analysis.