Hasil untuk "Banking"

T. Levesque, G. Mcdougall

Daesik Kim, Anthony M. Santomero

Douglas W. Diamond, Douglas W. Diamond, Raghu Rajan et al.

Nicole Koenig‐Lewis, A. Palmer, Alexander Moll

S. Al-Somali, Roya Gholami, B. Clegg

P. Gerrard, J. Cunningham

K. Lee, Namho Chung

Feisal Khan

P. Ngo

S. Chava, A. Purnanandam

Tao Zhou

Nicola Cetorelli, Linda S. Goldberg, Linda S. Goldberg

Mustafa Tevfik Kartal, Dilvin Taşkın, Marco Mele et al.

Abstract Environmental problems have been attracting the interest of all relevant parties because of the increasing negative effects on humanity. At this point, further clean, especially nuclear, energy consumption (EC) is seen as a strategic option to combat environmental deterioration (ED). Because clean energy, nuclear energy-related R&D investments (NRD), energy security risk (ESR), as well as increasing economic policy uncertainty (EPU) and trade policy uncertainty (TPU) in recent times have the potential to affect clean EC, this research uncovers the contribution of nuclear EC (NEC) in combating ED by considering also gross domestic product (GDP) and renewable EC (REC) along with the interaction terms of NEC with NRD, ESR, EPU, and TPU. In this vein, the study focuses on the USA case as the biggest economy and leading country in NEC, applies the kernel regularized least squares (KRLS) approach on data from 1974 through 2022, and uses carbon dioxide (CO2) emissions in the main analysis and ecological footprint (EFP) in checking robustness as an ED indicator. The empirical results show that (i) NEC (REC & EPU) is completely ineffective (beneficial) to reduce CO2 emissions; (ii) GDP, ESR, and TPU is almost completely unhelpful to decline CO2 emissions; (iii) the interaction of NRD and EPU with NEC provide a decrease in CO2 emissions; (iv) KRLS approach successfully estimates variations in CO2 emissions around 95%; (v) some variables (e.g., GDP & TPU) have a varying effect across percentiles, whereas others don’t. Thus, the study reveals the efficiency of certain factors (e.g., REC, EPU, interaction of NEC with NRD & EPU) on CO2 emissions, whereas GDP, NEC, ESR, & TPU can’t be helpful to protect the environment. Accordingly, the study argues policy implications (e.g., allocating free/low cost land, ensuring low cost financing support, removing customs-related barriers to import relevant components to install new clean EC capacity in short term, trying to nationally produce clean EC components in long term, ensuring long-term security of rare earth minerals, as well as preventing the displacement between REC and NEC through simultaneously supporting both REC and NEC to appropriately allocating incentives) for USA policymakers.

Visca Tri Winarty, Sena Safarina

Since the COVID-19 pandemic, the number of investors in the Indonesia Stock Exchange has steadily increased, emphasizing the importance of portfolio optimization in balancing risk and return. The classical mean-variance optimization model, while widely applied, depends on historical return and risk estimates that are uncertain and may result in suboptimal portfolios. To address this limitation, robust optimization incorporates uncertainty sets to improve portfolio reliability under market fluctuations. This study constructs such sets using moving-window and bootstrapping methods and applies them to Indonesian banking stock data with varying risk-aversion parameters. The results show that robust optimization with the moving-window method, particularly with a smaller risk-aversion parameter, provides a better risk-return trade-off compared to the bootstrapping approach. These findings highlight the potential of the moving-window method to generate more effective portfolio strategies for risk-tolerant investors.

Matt Brigida

Research has shown banks match interest income and expense betas, and thereby obtain net interest income margins which are insensitive to changes in short-term interest rates. The present analysis extends this research in a number of ways. First, we use state-space methods to estimate time-varying betas and test whether they are matched at each time interval. We find substantial variation in interest income and expense betas, which drives variation in net interest margin beta coefficients. Second, we estimate the time-varying conditional volatility of beta forecasts the uncertainty of future beta values. We find uncertainty in interest expense beta coefficients drives uncertainty in interest income betas. Further, large banks have greater expense beta uncertainty, whereas small banks have greater income beta uncertainty. Lastly, we find evidence that uncertainty in interest expense betas is priced by the market, and is negatively related to bank stock prices. This is a new and previously unmeasured source of unhedgeable risk in bank stocks, and highlights an additional benefit of the Federal Reserve's Zero Interest Rate Policy.

Georgy Lukyanov

I develop a tractable adverse-selection model comparing secured bank loans and bonds when both pledge collateral but differ in effective liquidation efficiency. A small wedge in recovery rates generates coexistence, a sharp bank-bond cutoff, and distinctive comparative statics in issuance, pricing, collateral, and default. Changes in insolvency regimes or creditor coordination shift the composition of external finance and welfare, with clear implications for bank-based versus market-based intermediation and financial stability.

Nguyễn Hải Quang, Nguyễn Thị Hải Anh

Attracting tourists to return to destinations is a key issue. From the Expectation Disconfirmation Theory (ECT) and the Theory of Planned Behavior (TPB), the study develops an integrated model to predict tourists’ intention to revisit attractions. The data of 405 tourists were surveyed at major tourist attractions in Ho Chi Minh City to test the hypotheses by Structural Equation Modeling (SEM) with the Partial Least Squares (PLS) technique. The results confirmed that Subjective Norms (SUN), Perceived Service Quality (PSQ), and Perceived Value (PEV) have a positive influence on Tourists’ Revisit Intention (TRI). Furthermore, Perceived Behavioral Control (PBC) not only has a direct impact on Tourists’ Revisit Intention (TRI) but also acts as a mediator between SUN and TRI. Similarly, Attitude towards Destination (ADV) also has a direct impact on TRI and plays a mediator role between the research factors and TRI. This study is considered as an attempt to combine ECT and TPB to explain TRI for tourist attractions. The findings serve as the foundation for suggesting managerial strategies to entice tourists to revisit the attraction.

Vítor Castro

Moch. Fandi Ansori, Kuntjoro Adji Sidarto, Novriana Sumarti et al.

This paper presents numerical works on estimating some logistic models using particle swarm optimization (PSO). The considered models are the Verhulst model, Pearl and Reed generalization model, von Bertalanffy model, Richards model, Gompertz model, hyper-Gompertz model, Blumberg model, Turner et al. model, and Tsoularis model. We employ data on commercial and rural banking assets in Indonesia due to their tendency to correspond with logistic growth. Most banking asset forecasting uses statistical methods concentrating solely on short-term data forecasting. In banking asset forecasting, deterministic models are seldom employed, despite their capacity to predict data behavior for an extended time. Consequently, this paper employs logistic model forecasting. To improve the speed of the algorithm execution, we use the Cauchy criterion as one of the stopping criteria. For choosing the best model out of the nine models, we analyze several considerations such as the mean absolute percentage error, the root mean squared error, and the value of the carrying capacity in determining which models can be unselected. Consequently, we obtain the best-fitted model for each commercial and rural bank. We evaluate the performance of PSO against another metaheuristic algorithm known as spiral optimization for benchmarking purposes. We assess the robustness of the algorithm employing the Taguchi method. Ultimately, we present a novel logistic model which is a generalization of the existence model. We evaluate its parameters and compare the result with the best-obtained model.

M. Aboelmaged, T. Gebba