Financial Innovation volume 9, Article number: 125 (2023)
The 42nd issue of Financial Innovation (FIN), Volume 9, No.6 (2023) presents 28 papers contributed by authors and co-authors from Twenty-four countries and areas: Australia, Bangladesh, Belgium, China, German, Hungary, Iran, Italy, Japan, Korea, Netherlands, Pakistan, Poland, Russia, Saudi Arabia, Spain, Sweden, Taiwan, Tunisia, Türkiye, UK, USA, Uzbekistan and Vietnam. These papers can mainly be categorized into four sub themes.
Financial technology and innovation
Song et al. (2023) uses the time-varying parameter/stochastic volatility vector autoregression model to explore the risk hedging and terrorist financing capabilities of Bitcoin. Its findings improve the theoretical system of anti-terrorist financing, helping to maintain world peace and security. Zheng et al. (2023) investigates the short- and long-run causal effects between cryptocurrency transaction and electricity consumption. The study covers short and long-run causalities simultaneously and includes breaks obtained from the cointegration test, which can support the credibility of causality. Ali et al. (2023) analyzes 249 firm-event observations containing firms from around the world and concludes that blockchain technology has a non-significant long-term impact on operating performance. Feng et al. (2023) proposes a blockchain-oriented approach to handle real-time detection of cyber attacks, which has significant scope for applications. Tosunoğlu et al. (2023) investigates the existence of the day-of-the-week anomaly in cryptocurrency markets with artificial neural networks, which is unlike traditional time series methods, and an evaluation was made from a different perspective. Bazzanella and Gangemi (2023) presents the new proof-of-work system that would regularize the variance of block entry and improve the system’s security. Yae and Luo (2023) provides a machine-learning solution for the out-of-sample-hacking problem in robust monitoring, the approach can further enhance the performance and stability of forecasts from any models and methods. Kuhle (2023) offers an alternative perspective, where a relaxation, rather than a tightening, of market constraints helps to avoid the costs of latency arbitrage.
Behavioral finance and decision-making
Mikhaylov et al. (2023) analyzes the financial development and open innovation oriented fintech potential for emerging economies using an integrated decision-making approach of MF-X-DMA and golden cut bipolar q-ROFSs. Moiseev et al. (2023) investigates the market capitalization shock effects on open innovation models in e-commerce using golden cut q-rung orthopair fuzzy multicriteria decision-making analysis. Kim (2023) examines how ambiguity influences the innovation strategies of ambiguity-averse managers and derives the values of the real options for innovation strategies and the probabilities of strategies under ambiguity. Javaid et al. (2023) finds that having a critical mass of female directors (three or more) shows a significant positive impact on modified value-added intellectual coefficient (MVAIC) and its components, including human capital efficiency, structural capital efficiency, relational capital efficiency, and physical capital efficiency, with physical capital being the critical driver. Zang et al. (2023) conducts an in-person survey of 480 randomly selected Ethnic Tibetans (ETs) households in rural China and indicates that mental accounting plays a significant role in the financial decision-making process of ET households. Long et al. (2023) investigates how financial literacy and behavioral traits affect the adoption of electronic payment (ePayment) services in Japan and suggests that the effects of financial literacy on the adoption and use of ePayment differ among people with different behavioral traits. Tetteh (2023) examines the effects of local digital lending development on deprivation and explores the implications of these effects on rural inhabitants. It recommends the decentralization of financial inclusion policies as a pathway to promote digital lending at the local level. Hu et al. (2023) identifies the essential components of artificial intelligence applications under an internal audit framework and provides an appropriate direction of company strategies.
Market impact and economic analysis
BenSaïda (2023) investigates the connectedness between Bitcoin and fiat currencies in two groups of countries: the developed G7 and the emerging BRICS. The results highlight the weak dependency between Bitcoin and the G7 currencies, as well as the BRICS exchange rates over the entire period under study. Salas-Molina et al. (2023) summarizes and analyzes the relevant research on the cash management problem appearing in the literature and highlights several open research questions. Xie et al. (2023) derives a new decomposition of stock returns using price extremes and proposes a conditional autoregressive shape (CARS) model with beta density to predict the direction of stock returns. Frömmel and Kadioglu (2023) examines the effect of trading hours extensions on forex rate volatility of Moscow Exchange Market and the results have theoretical, practical, and regulatory implications. Arnell et al. (2023) investigates how technology subsector stocks interact with financial assets in the face of economic and financial uncertainty and indicates that the connectedness response varies depending on the type of uncertainty shock. Preziuso et al. (2023) examines how the Payment Services Directive (PSD2) and open banking (OB) impact inclusive finance in the EU based on the perspectives of the Netherlands’ ecosystem, one of the leaders in the EU’s financial technology (FinTech) landscape. It suggested that adjustments are necessary from technological, regulatory, and market perspectives to reach disadvantaged population groups who have difficulties accessing such services and eventually using them. Fakher and Ahmed (2023) analyzes the role of financial development (FD) on the impact of technological innovation (TI) on six environmental quality indicators for the 25 economies for the period from 2000 to 2019. It indicates that FD should be an important parameter in designing policies for innovation to achieve the goal of net-zero carbon emissions. Lassoued et al. (2023) finds that the three types of political connections explored (aggregate, CEO, and board of directors) have negative effects on banks’ technical and cost efficiencies using random effect tobit regressions. Liu et al. (2023) analyzes financial innovation by private banks from an organizational perspective and provides an economic analysis for private banking development in China.
Real estate and investment
Swinkels (2023) examines the financial and economic consequences of tokenizing 58 residential rental properties in the US and reports that real estate token prices move according to the house price index; hence, investing in real estate tokens provides economic exposure to residential house prices. Zhang et al. (2023) aims to predict the United States REIT market using Group Method of Data Handling (GMDH). Compared with generalized autoregressive conditional heteroscedasticity (GARCH) model, GMDH’s accuracy is much higher, indicating that the machine learning approach can provide a highly accurate prediction of REIT prices. Chen et al. (2023) proposes an integrated multi-criteria group decision-making approach to improve the normative and reliability of credit risk assessment for Chinese real estate enterprises.
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Kou, G. Editor’s introduction. Financ Innov 9, 125 (2023). https://doi.org/10.1186/s40854-023-00562-7