Journal entry anomaly detection model

Although numerous scientific papers have been written on deep learning, very few have been written on the exploitation of such technology in the field of accounting or bookkeeping. Our scientific study is oriented exactly toward this specific field. As accountants, we know the problems faced in modern accounting. Although accountants may have a plethora of information regarding technology support, looking for errors or fraud is a demanding and time-consuming task that depends on manual skills and professional knowledge. Our efforts are oriented toward resolving the problem of error-detection automation that is currently possible through new technologies, and we are trying to develop a web application that will alleviate the problems of journal entry anomaly detection. Our developed application accepts data from one specific enterprise resource planning system while also representing a general software framework for other enterprise resource planning developers. Our web application is a prototype that uses two of the most popular deep-learning architectures; namely, a variational autoencoder and long short-term memory. The application was tested on two different journals: data set D, learned on accounting journals from 2007 to 2018 and then tested during the year 2019, and data set H, learned on journals from 2014 to 2016 and then tested during the year 2017. Both accounting journals were generated by micro entrepreneurs.     

Vicarelli’s Keynes (and today’s international disorder)

The article speculates about the legacy of Fausto Vicarelli’s interpretation of John Maynard Keynes’s work in the times of a major global crisis. In particular, it puts an emphasis on those aspects of Keynes’s “method” that Vicarelli rightly considered as revolutionary in his Keynes, of 1977, as well as in other writings. The article then turns to Vicarelli’s reconstruction of Keynes’s early work in international economics (Indian Currency and Finance, Economic Consequences of the Peace) and reflects upon the continuing relevance of the philosophy inspiring Keynes’s plans of global reform in the Forties, also in the light of Vicarelli’s (Keynes-inspired) vision of the problem of policy space at the international level.     

Exploring the effects of leaders’ individualized consideration in extreme contexts

Abstract

Role clarity and trust in leadership are two crucial factors supporting soldiers in coping with uncertainty and imperfect knowledge. The present study examined the effects of leaders’ individualized consideration on both factors in a sample composed of 161 paratroopers from a parachute division of the NATO Airborne Forces. Conditional process modeling revealed that (1) leaders showing individualized consideration increase followers’ role clarity and, in parallel, develop a trusting relationship with them; (2) critical upward communication and perceived workload mediated and moderated these relationships, respectively. The implications of these findings for safety research and their practical applications are outlined.     

Robust martingale selection problem and its connections to the no‐arbitrage theory

We analyze the martingale selection problem of Rokhlin in a pointwise (robust) setting. We derive conditions for solvability of this problem and show how it is related to the classical no‐arbitrage deliberations. We obtain versions of the Fundamental Theorem of Asset Pricing in models spanning frictionless markets, models with proportional transaction costs, and models for illiquid markets. In all these models, we also incorporate trading constraints.     

The economic cost of the Islamic State on the Syrian and Iraqi economies

In this paper, we evaluate the economic cost of the Islamic State on the Syrian and Iraqi economies from 2010 to 2016. To do so, we use the Post-Terrorism Final Economic Damage Simulator—PTFED-Simulator. The PTFED-Simulator assesses the economic damage of terrorism based on ten different indicators: (1) total regional terrorism tension (?T_t); (2) harmonized anti-terrorist strategy (AT₊); (3) war losses from terrorism (?πt); (4) total economic leakage from terrorism (?Ψt); (5) economic desgrowth from terrorism (?δ_t); (6) military dimension of terrorism (MD_t); (7) post-terrorism economic damage (?Π_t); (8) post terrorism economic damage evaluation; (9) post-terrorism reconstruction plan (PTR_t); and (10) terrorism effect on mega-disk networks mapping. Overall, we seek to evaluate the impact of terrorism on economic performance from a multi-dimensional perspective in both the short run and long run.     

Appropriate technology in a Solovian nonlinear growth model

We propose a Solovian growth model with a convex–concaveproduction function and international technological spillovers.We test the empirical implications of the model, analysing theeffects of the productivity slowdown that followed the oil shocksof the 1970s. We argue that this slowdown, altering the worldincome distribution, affected the pattern of international technologicalspillovers, taking the poorest countries further away from thetechnological leaders, and therefore unable to exploit theirtechnologies. The result is the emergence of a poverty trapfor low-income countries.     

R&D and performance persistence: Evidence from the United Kingdom

There is compelling evidence from both the United States and United Kingdom suggesting that R&D investment is positively related to operating and/or market performance. This study extends prior research on R&D and valuation by further examining the sustainability or persistence of operating growth and market performance as a result of R&D investments.We use a large dataset of U.K. companies during the period 1990–2003 and our findings confirm the relation between R&D intensity and consistent growth in Sales and Gross Income, but only in the cases when a firm needs to engage in R&D activity because of the industry in which it operates. Moreover, our evidence indicates not only a positive relation between R&D intensity and subsequent risk-adjusted excess returns among firms that engage in R&D as testified by prior literature, but we also show that R&D intensity improves persistence in excess stock returns: the highest R&D-intensity firms are found to earn higher risk-adjusted excess returns more consistently than the sample median return, compared to lower R&D-intensity firms, as well as firms with no R&D. We interpret this finding as consistent with at least some form of market mispricing.     

An alternative graphical modeling for economics: Econographicology

The rationale of Econographicology revolves around the efficacy of multidimensional graphs as the most effective visual tool to understand any economic phenomenon from a multidimensional view. The main motivation behind the creation of Econographicology is to evaluate multidimensional graphs evolved so far in economics and to develop new type of multidimensional graphs to facilitate the study of economics, as well as finance and business. Thereby, the mission of Econographicology is to offer academics, researchers and policy maker’s an alternative multidimensional graphical modeling approach for the research and teaching–learning process of economics, finance and business from a multidimensional perspective. Hence, this alternative multidimensional graphical modeling approach is offer a set of multi-dimensional coordinate spaces to build different types of multidimensional graphs to study any economic phenomenon. The following new types of multi-dimensional coordinate spaces are presented: the 5-dimensional coordinate space (vertical position and horizontal position), the mega-dynamic disks coordinate space (vertical position and horizontal position), and the mega-disks networks mapping.     

Claims frequency modeling using telematics car driving data

We investigate the predictive power of covariates extracted from telematics car driving data using the speed-acceleration heatmaps of Gao, G. & Wüthrich, M. V. [(2017). Feature extraction from telematics car driving heatmaps. SSRN ID: 3070069]. These telematics covariates include K-means classification, principal components, and bottleneck activations from a bottleneck neural network. In the conducted case study it turns out that the first principal component and the bottleneck activations give a better out-of-sample prediction for claims frequencies than other traditional pricing factors such as driver's age. Based on these numerical examples we recommend the use of these telematics covariates for car insurance pricing.     

Korean unification prospects: an assessment through the BDN-model

The debate on the possible unification of South Korea and North Korea has often been assessed from the economic perspective, which is insufficient since unification entails not only the integration of two economies but political, social and technological integration of two territories. Using the box negotiation diagram model, this paper expands the scope of the study on South Korea and North Korea unification through a multidisciplinary approach encompassing the political, economic, social and technological perspectives. Given the huge imbalanced points of unification drawn from our analysis, we observed more divergence than convergence hence, hinging the possibility of unification of serious negotiation.