Determining factors and impacts of the intention to adopt mobile banking app in Cameroon: Case of SARA by afriland First Bank

This study aims to know what are the factors determining the adoption of M-Banking app among customers in Cameroon. In other words, what are the factors that influence users in their decisions to adopt and use a system or technology such as the MBanking app, and indirectly, what is the impact of this use on both the customers and financial inclusion? The research model developed relying on a combination of Technology Acceptance Model (TAM ), Unified Theory of Acceptance and Use of Technology ( UTAUT2 ), Information System Success Model ( ISSM ), and Protection Motivation Theory ( PMT ) and other constructs; it was then tested with a sample of 223 users of the “ SARA” M-Banking app of the financial institution called “ Afriland First Bank” . Findings revealed that: (1) utilitarian expectation, hedonic motivation, and status gain, habit, and perceived privacy concern have a significant influence on the intention to adopt M-Banking apps; and (2) the exploitative/explorative use of this technology has an impact on user’s loyalty and satisfaction but also contributes strongly to fostering financial inclusion in Cameroon. Also, the Multi-group analysis was performed on the sample using 2 gender-based groups (males, n=121; females, n=102).     

Do leveraged warrants prompt individuals to speculate on stock price reversals?

Using proprietary data on bank-issued knock-out warrants written on a stock index, we find that individual investors’ aggregate warrant portfolio speculates against the short-term trend of the index. We argue that contrarian trading is driven by the interaction of product design and investors’ preference for large leveraged positions. Investors tend to open larger positions whenever warrants offer higher leverage. As a result, investors open an aggregate long position when calls offer higher leverage than puts. Since knock-out leverages move systematically with the underlying, aggregate warrant positions become contrarian even if investors do not intend to speculate on reversals.     

金融资源配置、技术进步与经济高质量发展

随着我国发展阶段及内外部条件的变化,科技创新已成为新时代引领我国经济高质量发展的核心驱动力。本文以金融驱动技术进步的视角,构建内生增长DSGE模型,分析金融资源配置、技术进步和经济增长之间的关系。研究佐证了我国技术创新的逆周期性,并发现金融资源在企业生产性投资与创新投资之间的分配,可以通过改变生产要素投入规模和技术进步率两种途径影响经济增长,且这两种影响之间存在“跷跷板”关系,但后者更具主导性。在此基础上,诠释了金融、技术与经济的动态传导机制:经济扩张期,企业生产规模扩张,金融资源对生产性投资的支持增加,对创新的投入相对减少,技术进步率放缓;经济收缩期,企业缩减生产规模,金融资源对生产性投资的支持减少,对创新的投入相对增加,技术进步率提升。本研究的政策启示为,面对当前发展新矛盾、新挑战,应把握发展新格局、新机遇,进一步深化金融改革,优化金融资源配置机制,鼓励创新投资,充分发挥股权市场对企业研发创新的支持作用,并辅以稳健适度的宏观调控政策,为企业创新提供良性的宏观环境,激活企业创新需求,促进技术进步,推动经济高质量发展。     

能源企业技术创新能力对财务绩效的影响——基于企业规模的门槛效应研究

能源消费和供给的重要性使得政府给予能源企业技术创新更多关注和支持，能源企业经营存在较大风险使得能源企业技术创新能力对财务绩效的影响呈现一定特殊性。以我国能源企业2013-2018年技术创新投入与产出能力指标为样本数据，采用因子分析法和动态面板门槛效应模型，在评价能源企业技术创新能力的基础上，分别研究能源企业技术创新投入和产出能力对财务绩效的影响及企业规模门槛效应。研究结果表明，能源企业的技术创新投入和综合能力对财务绩效的影响存在显著的门槛效应，而产出能力的表现并不显著。研究结果可为国家和能源企业的技术政策制定和创新投入决策提供参考。     

Financial development,portfolio investments and the real economy in Africa

According to the conservative view, capital flows enhance economic growth. Focussing on Africa’s real economy, this study investigates the linkage between portfolio investments and real sector growth, and whether financial sector development strengthens this association. The study covers 30 countries over the period 1990–2017. We adopt the Lewbel instrumental variable general method of moments (IV-GMM) two-step robust estimator, which relies on heteroscedasticity for identification, while dealing with instrument insufficiency, unavailability, endogeneity and omitted variable bias. We found that portfolio equity has no growth impact on Africa’s real sector. Debt flows deter the growth of the overall real sector as well as the manufacturing and industrial sectors, but have no impact on agriculture and service growth. We found that financial development does strengthen the positive association between capital flows and economic growth, but this is dependent on the type of sector and portfolio investment, as well as on the degree of financial development. We control for known determinants of economic growth.     

Corporate financial distress: The case of publicly listed firms in an emerging market economy

Occurrences of financial distress (FD) are not readily obvious yet can span several periods. This paper examines episodes of FD using industry‐relative (IR) firm‐/ accounting‐, market‐ and macro‐level information. Mixed logit regressions reveal that firm‐ and market‐based measures, as well as macro‐level variables explain the likelihood of FD in 263 publicly listed non‐banking firms in the Philippines during the period 1995 to 2018. Rates of identification of firms in financial distressed states of close to 69 percent are obtained at a cutoff probability of 0.30 in the model with time‐varying intercept and slope. This study shows the importance of recognizing heterogeneous firm behavior. The ability to more accurately predict the probability of FD and to determine the financial health of firms can help financial institutions in allocating funds and policy makers in predicting crises episodes.     

Incorporating textual information in customer churn prediction models based on a convolutional neural network

This study investigates the value added by incorporating textual data into customer churn prediction (CCP) models. It extends the previous literature by benchmarking convolutional neural networks (CNNs) against current best practices for analyzing textual data in CCP, and, using real life data from a European financial services provider, validates a framework that explains how textual data can be incorporated in a predictive model. First, the results confirm previous research showing that the inclusion of textual data in a CCP model improves its predictive performance. Second, CNNs outperform current best practices for text mining in CCP. Third, textual data are an important source of data for CCP, but unstructured textual data alone cannot create churn prediction models that are competitive with models that use traditional structured data. A calculation of the additional profit obtained from a customer retention campaign through the inclusion of textual information can be used by practitioners directly to help them make more informed decisions on whether to invest in text mining.     

Does more finance mean more inequality in times of crisis?

Many recent empirical studies show that both banking crises and financial development (FD) play an important role in understanding the dynamics of income inequality (IncI) over the last decades. However, so far no study has investigated the role of FD in the amplification of IncI following banking crises. This paper seeks to address this issue based on a sample of 69 banking crises in 54 countries over the 1977–2013 period. Our analysis suggests that FD is associated with a significant increase in IncI in the aftermath of banking crises. This result is robust to a broad range of alternative specifications and is unaffected by various potential sources of endogeneity. We also show that the relationship between FD and the redistributive consequences of banking crises is not subject to a threshold effect and is stronger for developing countries.     

Fair value accounting from a distributed cognition perspective

This study offers a unique interdisciplinary perspective on fair value accounting. The growing influence of esoteric financial instruments whose valuation is becoming increasingly complex makes it necessary to focus on actual valuation practices. Based on an extensive review, this paper regards fair value accounting for complex financial instruments as involving processes distributed among actors located inside and/or outside a reporting entity. It also draws attention to collaboration by organizations that apply their external and internal resources to perform complex financial valuations. Furthermore, it demonstrates that cases involving unusual market conditions underline the importance of human interactions to the valuation process.     

Corporate social responsibility reporting in financial institutions: Evidence from Euronext

The legitimacy, the identity and the social impact of financial institutions go beyond the generation of revenues for providers of capital, through financial intermediation. Financial institutions bear significant corporate social responsibility (CSR). We produce measures of CSR disclosure and explore the determinants of CSR disclosure practices in a cross section of financial institutions. Working with financial companies whose stocks are listed in the Euronext stock exchange, we find that the extent of disclosure of CSR practices is greater in large companies and also in companies of greater financial leverage. Therefore, increased corporate visibility and financial risk increase stakeholder demand for transparency on the social impact of financial institutions and their CSR practices.