Jun 2020, Volume 14 Issue 2

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    Jian Huang, Junyi Chai, Stella Cho

    Deep learning has been widely applied in computer vision, natural language processing, and audio-visual recognition. The overwhelming success of deep learning as a data processing technique has sparked the interest of the research community. Given the proliferation of Fintech in recent years, the use of deep learning in finance and banking services has become prevalent. However, a detailed survey of the applications of deep learning in finance and banking is lacking in the existing literature. This study surveys and analyzes the literature on the application of deep learning models in the key finance and banking domains to provide a systematic evaluation of the model preprocessing, input data, and model evaluation. Finally, we discuss three aspects that could affect the outcomes of financial deep learning models. This study provides academics and practitioners with insight and direction on the state-of-the-art of the application of deep learning models in finance and banking.

    Mohammad Khalilzadeh, Laleh Katoueizadeh, Edmundas Kazimieras Zavadskas

    Identifying risks and prioritizing is important for payment service provider (PSP) companies to get banking projects and gain more market share. However, studies regarding the identification of risks and causal relationships are insufficient in the Iranian PSP industry and the industry is unique because of its characteristics. In this study, 30 experts involved with PSP companies are employed as the research sample. Eleven key risks and Forty-six sub-risks are also identified. Subsequently, the fuzzy decision-making trial and evaluation laboratory technique is applied to determine the effective and affected risks and the severity of their effects on each other. Finally, all risks are ranked. Due to the internal interrelationships of the main risks, the weight of each risk is calculated via the fuzzy analytic network process. As the second-level risks have no significant interrelationships, they are ranked via the fuzzy analytical hierarchy process. Moreover, the best-worst method is used to ensure that the obtained rankings are reliable. This study identifies the risks affecting the loss of banking projects and determines the impacts of these risks on each. A sensitivity analysis is then conducted on the weights of the criteria, and the results are compared.

    Wilson H. S. Tong, Michael B. T. Wong

    Contrary to other markets where underwriters perform a combined role of underwriting and sponsoring in an Initial Public Offering (IPO), IPO issuers in Hong Kong must appoint at least one sponsor in addition to the underwriters. The splitting of the single role of underwriters into two separate ones offers an ideal setting to disentangle the effects of the two roles and to examine which of the two roles—sponsor or underwriter—is more important in explaining IPO underpricing and initial volatility in the Hong Kong equity market. Interestingly, our findings provide supportive evidence that the sponsor reputation does matter in an IPO and it is even more significant than the underwriter reputation in explaining the IPO underpricing phenomenon. Given the recent high-tech fervor, our research goes deeper to examine specifically the role of sponsors on high-tech firms, with results indicating that the reliance on sponsors is higher for traditional issuers than for technology firms. We further discover that sponsors and underwriters are playing substitution roles rather than complementary roles. In order to examine the regulatory policy impact, our research also compares the role of IPO sponsors before and after the launch of the new sponsor regulatory regime in 2013. The empirical findings lend support to our argument that after the launch of the new regulations, public awareness of sponsors is raised, respect towards more reputable sponsor increases, and thus, the role of sponsors becomes more important than before.

    Yajie Chen, Qinlin Zhong, Fuxiu Jiang

    We analyze whether product market advertising has a spillover effect on stock price synchronicity by transmitting firm-specific information to the capital market and attracting more investor attention. Using a sample of Chinese listed firms from 2009 to 2017, we find that firms with greater advertising expenditures have lower stock price synchronicity. The results are robust after we address endogeneity concerns. In accord with our hypothesis that product market advertising increases the amount of firm-level information capitalized into stock prices through the information channel, we find that the impact of advertising on synchronicity is more pronounced for firms with a higher degree of information asymmetry and firms in the consumer-product industry. Further tests show that product market advertising enhances the ability of current period returns to reflect future earnings, and thus rules out that the negative relationship between advertising and synchronicity is driven by noise trading. Our results imply that product market advertising plays an informative role and improves information efficiency in a capital market.

    Lifeng Zhong, Zhichao Qian, Dongdong Wang

    Drawing on the conservation of resource theory, this study investigates the mediating effects of self-efficacy and academic engagement in the relationship between servant supervision and postgraduates’ employability. We conducted a field study with 598 postgraduates (students for the research-based master's degree and PhD candidates) enrolled in universities in China to test our hypotheses. We developed and tested a model contending that servant supervisors propagate servant supervision among postgraduates through postgraduates’ self-efficacy and academic engagement, which indirectly influences postgraduates’ employability. The results support the mediating effects of both self-efficacy and academic engagement on the relationship between servant supervision and postgraduates’ employability. Finally, the theoretical and practical implications are discussed.

    Yibo Bi, Zhiyi Ren, Kun Bao

    Multinational enterprises (MNEs) make investment decisions according to the distance factors at a sub-national level. This paper made estimates using the gravity model with provincial foreign direct investment (FDI) data from 2000 to 2012 and employed three concepts of distance. Our empirical results indicate that geographic distance and cultural distance have significant negative effects on FDI flow, whereas economic distance has a significant positive effect. It suggests that FDI prefers to locate in regions that are geographically and culturally close but economically distant from the home country, which further implies that FDI in China is dominated by vertical FDI. Our findings suggest that Chinese provincial governments should place emphasis on attracting FDI from culturally close countries and provide institutional support to encourage and promote horizontal FDI.