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" Financial investment behaviour between Hong Kong and Mainland Chinese investors and predicting investors' preferences "
Mak, Mark Kwong Yiu
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Latin Dissertation
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| Record Number
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896437
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TLets810681
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| Main Entry
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University of Warwick
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| Title & Author
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Financial investment behaviour between Hong Kong and Mainland Chinese investors and predicting investors' preferences\ Mak, Mark Kwong Yiu
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| College
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University of Warwick
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| Date
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2018
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| Degree
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Thesis (Ph.D.)
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2018
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| Abstract
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Behavioural finance has been popular in the literature pertaining to investment behaviour in recent years. However, the number of applications for exploring individual investment behaviour in Hong Kong and mainland China are limited. This research investigates investor behaviour to identify the major determining factors influencing investor behaviour between Hong Kong and mainland China, and derive customers' investment preferences from the behavioural patterns identified. The approach developed generates two new models, namely PSYC Model and Financial Data Mining Model (FDMM). Data from 142,496 mainland Chinese and Hong Kong investors of Convoy Financial Service Limited ("Convoy"), one of the largest financial service providers in Hong Kong, were used to identify major influencing factors and examine differences of mainland Chinese and Hong Kong investors. Statistical analyses, including descriptive analysis, factor analysis, correlation analysis and regression analysis, were adopted. Six major factors were statistically supported to have impact on investment behaviours. More importantly, investment decisions made by investors from mainland China and Hong Kong are mainly affected by (i) age (demographic factor) (ii) investment experience (psychological factor) and (iii) annual income (sociological factor). The newly developed PSYC Model on the basis of the statistical results generalized two major perspectives of investor behaviours, namely investing involvement and risk appetite, in response to the three factors of Hong Kong and mainland China investors. Following this, the FDMM was created to assist financial institutions in predicting customer behaviour. Clustering analysis and association rules were applied. Ten experts with at least 15 years of experience in banking, insurance and stock markets in Hong Kong and mainland China were consulted in form of group meetings, telephone interviews and teleconference to justify the two new models with their experience and practical knowledge in the industry. The PSYC Model and FDMM were implemented within Convoy for validation. The former model helped in design and identification of appropriate product and marketing strategies for different classes of products while the latter model generated eight specific rules for Convoy to implement product offerings to Hong Kong investors which greatly improved business workflow and efficiency. As a result, the success rate selling financial products to its customers and the customer satisfaction level were boosted by 66% and 8.7% respectively. With these promising results, the research objectives were met, and the outcomes of this research can assist financial institutions to gain better insights into the behaviour of their customers from Hong Kong and mainland Chinese, and offer the most suitable financial products for fulfilment. The model developed could be further generalized for adoption by other financial institutions after further evaluation and case studies with the support of a wider range of customer profiles in diversified financial institutions.
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HG Finance
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University of Warwick
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