A new financial well-being index based on big data

Alkhdaer, Fahd (2024) A new financial well-being index based on big data. Doctoral thesis, University of East Anglia.

Preview

PDF Download (4MB) | Preview

Abstract

This study proposes a new Financial Well-Being (FWB) measurement methodology based on Google Trends Search (GTS). Current survey-based FWB measurement methods are lagging. Moreover, their capability to cover the multi-faceted FWB concepts is limited. On the other hand, the GTS has real-time values that could capture the multidimensions of FWB. The FWB is based on keywords extracted from the literature and processed by machine learning on constructs of unemployment, inflation, interest rate, stock index, and uncertainty that are mediated by financial behaviour. The proposed methodology involves selecting, filtering, expanding, and transforming keywords from these constructs to build an FWB index.

Consequently, the study creates an instant overarching model based on financial patterns of individual search from GTS using Partial Least Square Modelling (PLS-SEM). The GTS model keywords were transformed with several preprocessing steps, including stationarity and seasonality adjustments. The GTS model was compared with another developed model, the Alternative Proxy model, based on proxy variables data extracted from the UK. Both models had a sizeable explanatory analysis, as indicated by their large R2 values; however, the GTS shows a few variations due to its dynamic measurements of extreme economic events over a selected period.

In contrast, all the variables in the Alternative Proxy model were significant; however, inflation was positively correlated with positive financial behaviour. The study contributes to a new FWB Index based on GTS that provides a direct instant measurement of FWB. The FWB Index is useful for financial practitioners, policymakers, and government entities. The model provides an instant measure that promptly assesses public financial sentiment, facilitating timely and informed decision-making.

Keywords: Financial Well-Being (FWB), Google Trends Search (GTS), Partial Least Square Modelling (PLS-SEM), Economic Events, Financial Behaviour, FWB Index.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Social Sciences > Norwich Business School
Depositing User:	Chris White
Date Deposited:	29 Oct 2024 09:58
Last Modified:	29 Oct 2024 09:58
URI:	https://ueaeprints.uea.ac.uk/id/eprint/97289
DOI:

Downloads

Actions (login required)

View Item