Measuring financial resilience with consumer sentiment data from India

Yadav, Priti; Shaikh, Imlak

doi:10.1108/ijbm-07-2022-0325

Cited by 5 publications

(1 citation statement)

References 34 publications

(130 reference statements)

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“…Thus, understanding factors contributing to their financial well-being is significant in dealing with financial-related stress (Fan and Henager, 2022) and coping with financial shocks (Salignac et al ., 2020). It also draws implications for designing effective strategies and educational programmes to combat the economic downturn and improve work productivity, consumer resilience and satisfaction (Netemeyer et al ., 2018; Yadav and Shaikh, 2023).…”

Section: Introductionmentioning

confidence: 99%

Future time perspective and consumer well-being of millennials: implications for consumer resilience

She

Ray

2023

IJBM

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PurposeThe study investigated the relationship between future time perspective and financial well-being among Chinese working millennials and its serial mediators, such as financial goal clarity, subjective financial knowledge and responsible financial behaviour, to foster consumer resilience in the financial realm.Design/methodology/approachA total of 526 Chinese working millennials (Mage = 31.78) participated in the online survey in response to questions on demographic characteristics and items to measure the variables adopted in the research model. Covariance-based structural equation modelling (CB-SEM) and AMOS version 27 were used to test the research hypotheses.FindingsThe results revealed a positive correlation between future time perspective and financial well-being. Moreover, the results showed that financial goal clarity, subjective financial knowledge and responsible financial behaviour serially mediated the correlation between future time perspective and financial well-being.Practical implicationsThe findings provide implications for companies and policymakers to refine their intervention programmes to boost young millennials' future time perspectives in reinforcing their financial knowledge and financial goal clarity which in turn fosters their responsible financial behaviour in contributing to financial well-being in boosting their overall consumer resilience. Future studies should deepen the way in which the studied factors are leveraged as a tool to improve individuals' resilience in the economic realm.Originality/valueThe findings of this study shed light on the underlying mechanisms that drive and promote the financial well-being of Chinese working millennials.

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Section: Introductionmentioning

confidence: 99%

Future time perspective and consumer well-being of millennials: implications for consumer resilience

She

Ray

2023

IJBM

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Factors influencing Fintech adoption for women in the post-Covid-19 pandemic

Igamo,

Rachmat,

Siregar

et al. 2024

Journal of Open Innovation: Technology, Market, and Complexity

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Macroeconomic shocks, market uncertainty and speculative bubbles: a decomposition-based predictive model of Indian stock markets

Ghosh,

Chaudhuri,

Sarkar

et al. 2024

CFRI

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PurposeStock markets are essential for households for wealth creation and for firms for raising financial resources for capacity expansion and growth. Market participants, therefore, need an understanding of stock price movements. Stock market indices and individual stock prices reflect the macroeconomic environment and are subject to external and internal shocks. It is important to disentangle the impact of macroeconomic shocks, market uncertainty and speculative elements and examine them separately for prediction. To aid households, firms and policymakers, the paper proposes a granular decomposition-based prediction framework for different time periods in India, characterized by different market states with varying degrees of uncertainty.Design/methodology/approachEnsemble empirical mode decomposition (EEMD) and fuzzy-C-means (FCM) clustering algorithms are used to decompose stock prices into short, medium and long-run components. Multiverse optimization (MVO) is used to combine extreme gradient boosting regression (XGBR), Facebook Prophet and support vector regression (SVR) for forecasting. Application of explainable artificial intelligence (XAI) helps identify feature contributions.FindingsWe find that historic volatility, expected market uncertainty, oscillators and macroeconomic variables explain different components of stock prices and their impact varies with the industry and the market state. The proposed framework yields efficient predictions even during the COVID-19 pandemic and the Russia–Ukraine war period. Efficiency measures indicate the robustness of the approach. Findings suggest that large-cap stocks are relatively more predictable.Research limitations/implicationsThe paper is on Indian stock markets. Future work will extend it to other stock markets and other financial products.Practical implicationsThe proposed methodology will be of practical use for traders, fund managers and financial advisors. Policymakers may find it useful for assessing the impact of macroeconomic shocks and reducing market volatility.Originality/valueDevelopment of a granular decomposition-based forecasting framework and separating the effects of explanatory variables in different time scales and macroeconomic periods.

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Measuring financial resilience with consumer sentiment data from India

Cited by 5 publications

References 34 publications

Future time perspective and consumer well-being of millennials: implications for consumer resilience

Future time perspective and consumer well-being of millennials: implications for consumer resilience

Factors influencing Fintech adoption for women in the post-Covid-19 pandemic

Macroeconomic shocks, market uncertainty and speculative bubbles: a decomposition-based predictive model of Indian stock markets

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