The Early-warning System of Stock Market Crises with Investor Sentiment: Evidence from the United Kingdom

Nguyen, Thi Minh Tam (2020) The Early-warning System of Stock Market Crises with Investor Sentiment: Evidence from the United Kingdom. [Dissertation (University of Nottingham only)]

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While traditional financial models have insufficient explaining power for the historical stock market crisis, the introduction of behavioural approach is expected to understand and predict these events. Following the work of Zouaoui et al. (2011) and employing the early-warning system proposed by numerous researchers, this paper testifies the connection between investor sentiment and the occurrence of stock crisis by answering whether investor sentiment can be a potential indicator in the crisis signalling model. With the UK stock market data from January 2005 to June 2020 including the financial crisis in 2007 and the recession caused by the recent epidemic, investor sentiment after controlling for the fundamental variables displays a significant positive relationship with the occurrence of the stock crash as expected. The models overall show the incremental predicting power of sentiment in the traditional early warning model, which is consistent with the literature though less significant. However, its solely impact on signalling the crisis has mixed results. The findings from the UK are partially, but not fully, explained by the sentiment hypothesis which is testified by other scholars. The model outcomes display the significant linkage between sentiment and the upcoming stock market crisis but the signs are diverse. Some of the potential explanations for these results are also detected and discussed in this dissertation such as the difference in the nature of the crises themselves, the limitation of the data, and the use of the model.

Item Type: Dissertation (University of Nottingham only)
Keywords: Investor Sentiment, Stock Market, Crisis, Early-warning
Depositing User: Nguyen, Thi
Date Deposited: 13 Apr 2023 12:19
Last Modified: 13 Apr 2023 12:19

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