Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Mobile Banking Adoption: An Integration of TAM and TPB with Trust and Perceived Risk

Abstract Mobile banking has been a game changer for financial organizations in terms of remote banking services. However, many customers remain uncertain due to its security. Therefore, improving the comprehension of the customer’s reasons and methods of using bank sites, including their behaviour towards e-banking, is crucial. This article discusses the matter by suggesting a technology acceptance model that integrates the theory of the planned behavior model in the classic TAM model with trust and perceived risk in order to elucidate the aspects that influence users’ acceptance of mobile banking applications in Palestine. This study is designed to give both theoretical and empirical support for e-commerce adoption. We are also capable in providing particular marketing ideas for practitioners in relation to the uptake of mobile banking.
CPA Exam Performance and Environmental and Other Opportunity Factors

CPA certification is an important measure of professional achievement and a critical element to advancement in the accounting profession. The CPA exam is rigorous, with overall lower pass rates relative to other professional exams, and even lower pass rates for historically disadvantaged groups. Thus, a key policy question is how to improve candidates’ performance on the CPA exam. In this paper, we examine the role that environmental (community segregation, socioeconomic status, and education and income gaps) and other factors representing opportunity play in CPA exam performance. The results of univariate analysis of CPA exam performance across various demographic and opportunity factors and those of several multivariate models indicate that opportunity affects exam performance of all candidates and more so for the disadvantaged groups. Finally, we offer recommendations for programs to help meet the profession’s need for an increasing number of qualified CPAs and its diversity and inclusion goals.
The Underdeterrence, Underperformance Response to Privacy, Data Protection Laws

Abstract The digital economy has been defined in the economic literature as one with near zero marginal cost, unmonetized services but also an escalating data flow. After a careful review of the most recent economic papers, we offer an alternative theory on the cost of privacy and data protection regulations. We have observed that the characteristics of the regulation lead not only to the amplification of costs that have been traditionally assigned as variable costs by the literature, but also of costs that used to be fixed but have been outsourced in the digital economy, meaning that significant new variable costs might trigger diseconomies of scale. At the same time, privacy and data protection regulations have created incentives that are making the dominant firms insource, in what seems to be a way back to increased sunk fixed costs for these firms. Having all that in mind, we claim that the perception of deterrence and compliance costs has affected how firms might decide to incur higher risks to avoid costs. Although compliance costs are high, we claim that an efficient implementation of the regulation avoids much of these costs. Our claim is supported by evidence that a relevant share of the regulatory costs are now variable costs, leaving room for at least two efficient strategies that medium-sized firms might implement in order to avoid them. First, firms can lower the volumes of data that they use without significantly impairing the predictive functions of their algorithms. Second, firms can invest in security at a comparatively lower degree than dominant firms considering their lower exposure to strong regulatory action.
About the Bootstrap Weak Convergence for the Foster-Greer-Thorbecke Poverty Index

We assume the Foster-Greer-Thorbecke (FGT) poverty index as a centered and normalized empirical process indexed by a particular Donsker class or collection of functions and define this poverty index as a bootstrapped empirical process, to show that the weak convergence of the FGT empirical process centered and normalized is a necessary and sufficient condition for the weak convergence of the FGT bootstrap empirical process centered and normalized. Thus, this result reflects that under certain conditions, the consistency in weak convergence of the FGT empirical process considered as a classical estimator of poverty (statistics) and the consistency in weak convergence of the FGT bootstrap empirical process considered as a bootstrap estimator of poverty (bootstrap statistics) are asymptotically equivalents for random samples of incomes statistically large and representative of a statistical universe of households.
The Term Structure of Default Probabilities

Accounting standards require that financial institutions must measure default risk with respect to the full maturity of a financial instrument. This requires forecasting of future default probabilities. The forecast of future default probabilities concerns two aspects: forecasting macroeconomic scenarios and future average (with respect to the macro-economy) default probabilities. The present paper addresses the modelling of future average default probabilities. Due to the small number of defaults and observations this poses a difficult problem in the corporate area and requires a parsimonious model to deal with the sparse data situation. The degree of difficulty is made greater by the fact that default probabilities change for corporations via different patterns over time, with the pattern being depend on the initial rating grade. For initial investment-grade ratings the risk of a default increases, while for the bottom of the rating scale default probabilities decrease. To model these different patterns the paper proposes to extend the existing discrete-time survival model and to incorporate an additional time- and co-variate-dependent shape parameter into the hazard function. Using data from Standard &amp; Poor's the paper shows that the shape parameter is able to reproduce the different patterns. The proposed model is bench-marked against a model which does not employ a shape parameter and the results show that the shape parameter improves in-sample and out-of-sample prediction.
Lending When Relationships Are Scarce: The Role of Information Spread via Bank Networks

We investigate how bank networks facilitate syndicate formation and lending in the leveraged buyout (LBO) market, where ties between banks and borrowers are scarce and borrower opacity is high. Using novel centrality measures that capture how information might flow through the network, we show that networks disseminate borrower-relevant information that influences which banks join the syndicate, the share the lead bank holds, and LBO lending terms. Further, banks’ knowledge of their network is highly localized, unrelated to their reputation, and a useful information source when ties to the borrower are lacking. Our findings emphasize the importance of information diffusion via networks for resolving asymmetric information problems during loan syndication.
How Can Management Control Systems Contribute to Acquisition Failure? A True Story

The purpose of the study is to identify what can go so wrong from the time managers decide to make an important acquisition to the time they actually liquidate their assets. When managers decide to invest in a certain project, they can normally justify its plus-value (financial and/or non-financial) to the shareholders. If not, there would be no point of investing. Therefore, how come an important investment can rapidly become a nightmare? Here, we focused on different theories that relate to managerial accounting to put light on what can go wrong from a management accounting perspective. We evaluated a specific case of acquisition/liquidation and conducted interviews to answer our research questions. We found that not considering the acquired firm control systems is definitely part of the acquisition failure. On the other side, strong post-acquisition controls can reduce losses of money and the acquiring firm wins at doing tight post-acquisition controls.
Combinatorial Optimization, Network Flow and Liquidity Management

The combinatorial liquidity management problem is formally defined. The nature and complexity of the resulting mathematical program are discussed. Casting the ensuing mathematical program into the physical analog of a network flow model offers a natural and elegant approach for problem formulation. This mitigates model misspecification, particularly, as the problem complexity grows. Efficient network algorithms for proofs of maxflow and mincost satisfaction are developed. A variety of examples are chosen to illustrate the presented concepts. The SAS PROC OPTMODEL is introduced as a powerful tool for solving the network flow mapped liquidity problem. <br>
Monetary Policy, Twitter and Financial Markets: Evidence from Social Media Traffic

How does central bank communication affect financial markets? This paper shows that the monetary policy announcements of three major central banks, i.e. the European Central Bank, the Federal Reserve and the Bank of England, trigger significant discussions on monetary policy on Twitter. Using machine learning techniques we identify Twitter messages related to monetary policy around the release of monetary policy decisions and we build a metric of the similarity between the policy announcement and Twitter traffic before and after the announcement. We interpret large changes in the similarity of tweets and announcements as a proxy for monetary policy surprise and show that market volatility spikes after the announcement whenever changes in similarity are high. These findings suggest that social media discussions on central bank communication are aligned with bond and stock market reactions.
The Disproportionation of Pu4+ in Nitric Acid Solutions

The Pu + disproportionation equilibrium in nitric acid has been examined at <25°C to extend our understanding and predictive ability with regard to species distribution under these conditions. Vis/UV absorption spectrophotometry has been used in a conventional manner to determine the concentrations of the various plutonium species. Values for the overall equilibrium quotient at 5, 15, and 25°C were determined to be 0.098, 3.46, and 58.8, respectively, at zero ionic strength. From these values, the enthalpy of the reaction was found to be +52.7 kcal(220 kJ)/mol. The excellent reproducibility of the equilibrium quotients, even while parameters such as acid, nitrate ion and plutonium concentrations were changed, lend confidence to future predictive calculations regarding this reaction.
The New International Regulation of Market Risk: Roles of VaR and CVaR in Model Validation

We model the new quantitative aspects of market risk management for banks that Basel established in 2016 and came into effect in January 2019. Market risk is measured by Conditional Value at Risk (CVaR) or Expected Shortfall at a confidence level of 97.5%. The regulatory backtest remains largely based on 99% VaR. As additional statistical procedures, in line with the Basel recommendations, supplementary VaR and CVaR backtests must be performed at different confidence levels. We apply these tests to various parametric distributions and use non-parametric measures of CVaR, including CVaR- and CVaR+ to supplement the modelling validation. Our data relate to a period of extreme market turbulence. After testing eight parametric distributions with these data, we find that the information obtained on their empirical performance is closely tied to the backtesting conclusions regarding the competing models.
The Joint Distribution of Value and Profitability: International Evidence

We examine the joint distribution of value and profitability in international markets. Over the 1990-2020 sample period, portfolios formed at the intersection of value and profitability generate systematic return patterns: value and high-profitability portfolios substantially outperform growth and low- profitability portfolios. The return differences are present in developed markets (ex-US), emerging markets, subsets and combinations thereof (EAFE, ACWI ex-US), as well as in large and small stocks. When viewed in combination with similar such evidence from the US, the data suggest important benefits to targeting value and profitability jointly rather than piecemeal.
Quantitative Easing, Bank Lending, and Competition

We study the effects of the European Central Bank’s quantitative easing (QE) program announced in January 2015 on lending by Italian banks. We use data from the Italian credit and loan application registers, and banks' security-level holdings data. Banks exposed to QE increased their lending at both the intensive and extensive margins after QE. There is also evidence of substitution. QE-exposed banks formed new credit relationships with firms that were previously rejected for credit by their non-exposed bank. Also, branches of non-QE exposed banks contracted lending in areas where QE-exposed banks dominate. Because of this credit substitution and the fact that only a narrow segment of the Italian banking system was exposed to QE, we find no evidence of an aggregate expansion in credit supply. Our evidence suggests that QE programs that target a broader swath of the banking system could more effectively expand lending.
The Economics of Hacking

Hacking is becoming more common and dangerous. The challenge of dealing with hacking often comes from the fact that much of our wisdom about conventional crime cannot be directly applied to understand hacking behavior. Against this backdrop, hacking studies are reviewed in view of the new features of cybercrime and how these features affect the application of the classical economic theory of crime in the cyberspace. Most findings of hacking studies can be interpreted with a parsimonious demand-and-supply framework. Hackers decide whether and how much to “supply” hacking by calculating the return on hacking over other opportunities. Defenders optimally tolerate some level of hacking risks because defense is costly. This tolerance can be interpreted as an indirect “demand” for hacking. Variations in law enforcement, hacking benefits, hacking costs, legal alternatives, private defense, and the dual-use problem can variously affect the supply or demand for hacking, and in turn the equilibrium amount of hacking in the market. Overall, it is suggested that the classical economic theory of crime remains a powerful framework to explain hacking behaviors. However, the application of this theory calls for considerations of different assumptions and driving forces, such as psychological motives and economies of scale in offenses, that are often less prevalent in conventional (offline) criminal behaviors but that tend to underscore hacking in the cyberspace.
Quadratic Variation

Time changes of Brownian motion impose restrictive jump structures in the motion of asset prices. Quadratic variations also depart from time changes. Joint Laplace Fourier transforms for quadratic variation and the stock are developed. They are used to study the multiple of the cap strike over the variance swap quote attaining a given percentage price reduction for the capped variance swap. Bootstrapped data and simulated paths spaces are used to study the multiple of the dynamic hedge return desired by a realized variance swap contract. The optimized hedge multiple in the bootstrapped data is consistently near unity. Simulated path spaces allow for departures matched by also similarly altering the position in the log contract. Value multiples of quadratic variation over variance swaps are consistently larger in simulations and bootstrapped data. The departures reflect negative dividend yields embedded in the skewness of risk neutral distributions.
What Mergers and Acquisitions Research is about – Theories, Topics, and the Scientific Community

Mergers and Acquisitions (M&amp;A) have become a central instrument of organizational development. Consequently, research on M&amp;A has developed into a complex research area of management science in recent years. However, the different perspectives are so heterogeneous that a holistic view is often difficult to achieve. The present research paper aims to take a holistic view of M&amp;A research and, based on a bibliometric analysis, to allocate the various studies to research clusters, to map interrelationships between documents, authors, countries, and institutions and to trace the development of M&amp;A research over time. For this purpose, a sample of 580 articles from 9 leading management science journals was bibliometrically examined and a total of 42,630 citations and 18,734 unique references were considered for the years 1963–2019.
On to the Next One: Transitions in Project Entrepreneurship

How does the level of success of the latest project impact the resource sets and decisions of a project entrepreneur? As they move from one project to the next one, project entrepreneurs are faced with the need to rewire and redeploy a variety of resources repeatedly. Even though such project-based enterprises are common a variety of industries, we know little about transitional dynamics of entrepreneurs situated in these industries. In this paper, I employ novel measurements and methods of causal empirical identification to investigate the impact an important determinant of resource sets available and decisions regarding future projects: success of the latest venture. In particular, using difference-in-differences methods in a film industry, I show that success in terms of resource sets, financial inputs are largely unaffected by the level of success, access to creative inputs increases disproportionately for entrepreneurs with prior connections in the industry. In terms of choices of subsequent projects, high levels of success leads artist entrepreneurs to take lower creative risk, while embeddedness and high levels of success both lead to the choice of projects with disproportionately lower levels of popularity. I end with a discussion on the contribution of the study to entrepreneurship theory and practice.
Efficiency and Distributional Effects of the Two-Tracked Labour Market Institutions in Albania

This study examines the efficiency and distributional effects of selected labour market institutions in Albania, a rather under-researched country. An initial overview of the post-communist developments articulates why Albania has the poorest labour market performance among other South East European countries. Using a set of mixed qualitative and descriptive quantitative methods we find evidence of inefficient segmental effects and a predatory structure of labour market institutions which noticeably diverge from the efficient institutions point of reference. The institutional/welfare regime at the cross-national level points out at a relationship between the labour market institutional framework and labour market performance, as measured by unemployment. At the country level, a disproportional relationship between the ‘de jure’ labour market regulation and unemployment is identified, which is also moderated by the interaction between labour market and economic institutions.
Hurdle Rate, Zero Lower Bound and Investors’ Active Risk Taking

We propose that the hurdle rate is helpful to understand the fund-flow decisions made by investors of fixed income mutual funds. Hurdle rates are inelastic and heterogeneous. Investors with positive hurdle rates may switch between two motivations: Take risk actively or follow relative fund performance. The regime of zero federal fund rate could motivate investors with positive hurdle rates to switch from following relative fund performance to active risk-taking. Our empirical results support this prediction. Since 2009, significantly larger inflows into riskier fixed income mutual funds are documented. During the taper tantrum period, although the evidence of significant outflows from fixed income mutual funds following the safe benchmark is consistent with anecdotal evidence, we document significant inflows into fixed income mutual funds following the risky benchmark.
Earnings Management During the Oil Price Crisis

Starting in mid-2014, oil prices began to fall drastically, hereafter this is referred to as the oil price crisis. This paper investigates the impacts of this crisis on earnings management behaviour in Gulf Cooperation Council (GCC) countries. Earnings management is measured in terms of accrual based earning management (AEM) and real activity based earnings management (REM). The modified Jones model is adopted to estimate AEM, and three models from Roychowdhury (2006) are used to estimate REM. The results reveal that companies have tended to use downward REM during the oil price crisis, engaging less with AEM. Control variables covering firm characteristics, including ROA, leverage, growth and OCF exhibit significant relationships with EM. The present study examines EM during the oil price crisis, considering both accrual and real activity earnings management. In contrast to most previous research in this domain which has only considered upward REM, a non-directional approach is used herein whereby the absolute (unsigned) term is applied to capture this metric.
Military Strategy and Asset Management: A Heuristic Way

This work aims to establish a link between military strategy and asset management. This relationship is conceptual, using the principles of Bewegungskrieg: offensive, mobility, speed, surprise and exploration. The work is presented in this way: military thinking and business world, military concepts used and their analysis, the world of asset management; offensive, where is used the Theory of Reflexivity by George Soros; mobility and speed, which is presented time perception by investors and it can be taken advantage, and finally, surprise and exploration, a chapter which presents the fields of Behavioral Finance, in order to interpret the bases of the decision-making process of investors and the consequences thereof. The result is the consistency of the connection of themes which, although appearing to a hard link, it seems useful. This is one area in early development, and as such has the potential for future investigations.
Development of a Framework for Query Translation and Its Ambiguities

Internet usage is increasing at a rapid rate. Anyonecan access all sorts of information from the web at any time. But the language diversity of web pages restricts this access of information. Cross Lingual information Retrieval provides the solution to this problem, by allowing user to post their query in the native language and retrieve the documents in otherlanguages. Machine readable dictionaries are the mosteconomical resource of cross language translation. These dictionaries usually provide more than one translations in target language for source query terms. These translations need to be disambiguated to achieve the best translation for a query word.Once we achieve the correct translations, the cross lingual information system can match the monolingual informationretrieval on performance grade. In this paper we propose a framework for query translation and disambiguation to achieve an efficient cross lingual information system.