Browsing by Tema "Asset (computer security)"

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A proposal for Measuring Value Creation by the intellectual capital in large Colombian companies
(2017) Patrícia González González
The aim of this paper was to evaluate 20 large Colombian companies in order to determine whether they were creating value from intellectual capital and, for this purpose, the Pulic Method was used to calculate the Value Added Intellectual Capital (VAIC). The methodology consisted of taking information from the statements of income of the companies analyzed to calculate the state of Added Value and from this state, calculate the efficiency indicators related to Human Capital, Structural Capital and Employed Capital, which allow the calculation of VAIC. The indices obtained were evaluated from a table of evaluation proposed by Pulic. The grades determined whether the analyzed companies are creating value from intellectual capital. The results show that the observed companies create value from intellectual capital. The level of association of the observed variables is high and the whole model can explain changes in the VAIC. It is concluded that is necessary to complete the companies’ diagnosis with analyzes that do not strictly correspond to the traditional format of financial indicators, but instead to create variants based on such information, as is the case of the Value Added State whereby it can evaluate the company’s intangible asset performance.
An Empirical Assessment of the Success of Road Asset Management System in Tanzania and Its Economic Value in Managing and Planning for Roads Pavement
(Khalsa Publications, 2019) Vitalis Ndume; Majige Selemani; Jesuk Ko
The deployment of Information Communication Technology in the Road sector has contributed positively towards achieving the national goal of ICT for infrastructure development. However, the deployment of ICT software for Road infrastructure in underdeveloped countries has been done with duplication of efforts contributing to software failure. This study aimed in evaluating the effectiveness and economic values of the Road Maintenance Management System in Tanzania. The study deployed System Usability Scale Framework in 26 regions of Tanzania, and Kruskal-Wallis test was used for significance testing. The result indicates positive response of adopting and scaling the Road Maintenance Management System to all 26 regions in the country with R2=0.863. The usability of the system remains steady for almost three years from 2017 to 2019. The economic value of system is found to be above average (61%), while the value for money is found to reach 76.5% of the expectation. It is therefore concluded that the use of ICT in planning for Roads Maintenance increases efficiency in delivery critical factors that facilitated decision making in road planning and also improves specific services delivery in government efficiency.
Asset Liability Management and the Profitability of Listed Banks in Ghana
(RELX Group (Netherlands), 2017) Evans Tee
Bankruptcy, Discharge, and the Emergence of Debtor Rights in Eighteenth-Century England
(Cambridge University Press, 2018) Ann M. Carlos; Edward Kosack; Luis Castro Peñarrieta
Bankruptcy is a precise legal process defining, ex ante , the rules for allocation of assets when debtors fail to repay their legally constituted debts. Ultimately, these rules determine willingness to lend and to borrow, and thus economic growth. In 1706, Parliament in England passed a bankruptcy statute that allowed, for the first time, bankrupts to exit the state of bankruptcy prior to full repayment of all debts. This represented a fundamental change in English bankruptcy rules: creditors could now choose to discharge a bankrupt. Obviously, bankrupts benefitted from such a discharge, but creditors could also benefit from greater asset revelation. We document that discharge was quickly adopted, and estimate that many bankrupts received a second chance in business.
Changes in adult well-being and economic inequalities: An exploratory observational longitudinal study (2002–2010) of micro-level trends among Tsimane’, a small-scale rural society of Indigenous People in the Bolivian Amazon
(Elsevier BV, 2024) Ricardo Godoy; Jonathan Bauchet; Jere R. Behrman; Tomás Huanca; William R. Leonard; Victòria Reyes-García; Asher Y. Rosinger; Susan Tanner; Eduardo A. Undurraga; Ariela Zycherman
Desempeño financiero de las cajas rurales del estado Mérida, Venezuela
(2019) Ismaira Contreras; Alejandro Gutiérrez S.
The objective of the present article is to evaluate the financial performance of Rural Savings Banks (CRs) from Merida State, Venezuela. The methodology used was descriptive and analytical. The sample was composed by fourteen CRs located in eight municipalities. A registration matrix was used to collect the information of the financial states of such savings banksand to calculate the financial indicators. The results report high levels of liquidity, moderate leverage, low turnover of assets, adequate proportion of operating expenses, profitability of the asset andalso of the patrimony superior to that of the industry, increasing financial differential, and high operational self-sufficiency. It was concluded that these CRs must pay close attention to the financial information report, in order to contribute with a successful decision-making.
Do Ipos Affect the Prices of Other Stocks? Evidence from Emerging Markets
(RELX Group (Netherlands), 2009) Matías Braun; Borja Larraín
We show that the introduction of a large asset permanently affects the prices of existing assets in a market. Using data from 254 initial public offerings (IPOs) in 22 emerging markets, we find that portfolios that covary highly with the IPO experience a decline in prices relative to other portfolios during the month of the issue. The effects are stronger when the IPO is issued in a market that is less integrated internationally and when the IPO is bigger. This evidence is consistent with the idea that shocks to asset supply have a significant effect on asset prices.
Evaluating Asset Pricing Anomalies: Evidence from Latin America
(RELX Group (Netherlands), 2023) Luis Berggrun; Emilio Cardona; Edmundo R. Lizarzaburu
Excess Asset Returns Predictability in an Emerging Economy: The Case of Colombia
(2023) Martha López; Eduardo Sarmiento G.
We examine the extent in which the ratios of book-to-market and earnings-to-price predict excess asset returns in an emerging market economy like Colombia. We want to find the magnitude in which these ratios help to forecast excess returns and if there is any evidence that one of the ratios outperforms the other. In addition, we want to address the impact of the spread between the domestic and the foreign policy interest rate in the excess asset returns. Using Bayesian techniques, we find that the magnitude of the effect is similar for both ratios and that the impact is slightly higher in the case of firms with higher book-to-market ratios. Moreover, we find evidence that the spread of interest rates explains the excess returns in a way according to the Uncovered Interest Parity theory.
Financial Contractability and Asset Hardness
(RELX Group (Netherlands), 2005) Matías Braun
From Data Assets to Value Creation: Competitive Advantage in the AI Age
(2025) FRANKLIN ORE ARECHE; Silvia Hypatia Sarabia Cansaya; Anna Di Laura
The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed how organizations create and sustain competitive advantage. In contemporary business environments, data is no longer treated merely as a supporting asset but has emerged as a primary source of value creation. This article examines how data-driven approaches, enabled by AI technologies, generate competitive advantage through enhanced decision-making, personalization, and operational efficiency. Using a conceptual research method, this study synthesizes findings from international peer-reviewed journals to analyze the mechanisms through which data becomes economic value. The Results and Discussion section elaborates on three core dimensions: the transformation of data into value generators, the economic characteristics of data in AI-driven markets, and the strategic logic of value creation through data–algorithm–context alignment. The findings indicate that data-driven competitive advantage is contingent not only on data volume but also on data quality, governance, and organizational capability. This article contributes to the growing body of literature on AI-enabled strategy by offering an integrated framework for understanding data as a strategic source of competitive advantage.
Heterogeneidad de cartera y riesgo sistémico: micro-fundamentación para el diseño del colchón de capital anti-cíclico y la política macro-prudencial en la banca boliviana
(2026) Saulo A. Mostajo Castelú; Walter Morales Carrasco
This paper examines how loan portfolio heterogeneity shapes the build-up of systemic risk and the design of the countercyclical capital buffer (CCyB) in an emerging, bank-based economy. Using Bolivia as a case study, we show that a uniform CCyB calibrated on the credit-to-GDP gap fails to reflect banks’ differentiated sensitivity to the cycle and may induce moral hazard, competitive distortions and weaker macroprudential effectiveness. We propose a micro-foundation for macroprudential policy by modelling each bank’s loan book as a risky asset in a CAPM-type framework without a risk-free asset. In this setting, the “loan beta” with respect to real GDP growth summarizes the systematic risk taken by each institution and its propensity to amplify or dampen the business cycle. Using quarterly data for 16 banks, we estimate contemporaneous and lagged betas and relate them to business models, portfolio composition and asset quality. The financial cycle lags the real cycle by around four quarters and pro-cyclicality is heterogeneous: universal banks cluster around a beta of one, the SME-oriented banks display betas above two, and microfinance institutions show much lower or even cyclical sensitivities. These results support a proportional, segmented CCyB design, where activation and calibration are anchored in portfolio betas and business models rather than applied uniformly across institutions, thereby strengthening the link between micro-level risk-taking and macroprudential objectives. The framework is tractable and can be generalized to other concentrated banking systems.
MONO+KM: Knowledge Management in Collaborative Project Development
(2016) Oscar González-Rojas; Gilberto Pedraza Garcia; Darío Correal; Guillermo Beltrán
In the dynamics of collaborative project management, participating organizations make great efforts and provide technical, technological and human resources to achieve a product they can hardly develop individually.Although there are tools to integrate, monitor and manage processes for such projects, it is not uncommon to find technological support to manage the knowledge generated during their execution. Usually this knowledge is part of the experience of participants but it is not recovered or documented nor is it used an organizational level, thus losing an important asset.In this study, we propose a technique in which a knowledge management approach is applied to the management of collaborative projects and where knowledge is expressed in terms of decisions.This is achieved through the analysis of verbal interactions that occur among participants in these projects, the identification and recovery of decisions Grounded Theory Method (GTM) techniques, and the specification of a set of concrete usage scenarios.The technique was applied in MONO, a framework for integration, control and optimization of production processes in which digital content companies in the creative industry work collaboratively.The study provides an annotation model, which, without being intrusive, allows for the recovery and structuring of knowledge expressed as decisions, thus making possible its replication in other domains.
On the Existence of Equilibrium with Incomplete Markets and Non-Monotonic Preferences
(2008) Andrés Carvajal; John Geanakoplos; Álvaro Riascos
We provide a shorter proof than Geanakoplos and Polemarchakis (1986) of the existence of equilibrium in an incomplete ﬁnancial market economy with numeraire assets, under the weak assumption that asset returns are non-negative. Furthermore, we relax the strict monotonicity assumption on preferences and as an application we prove the existence of equilibrium when agents may disagree on zero probability events but do not plan to go bankrupt in any state.
Parametric vs. non-parametric methods for estimating option implied risk-neutral densities: the case of the exchange rate Mexican peso – US dollar
(Universidad Autónoma de Nuevo León, 2008) Guillermo Benavides Perales; Israel Felipe Mora Cuevas
This research paper presents statistical comparisons between two methods that are commonly used to estimate option implied Risk-Neutral Densities (RND). These are: 1) mixture of lognormals (MXL); and, 2) volatility function technique (VFT). The former is a parametric method whilst the latter is a non-parametric approach. The RNDs are extracted from over-thecounter European-style options on the Mexican Peso–US Dollar exchange rate. The non-parametric method was the superior one for out-of-sample evaluations. The implied mean, median and mode were, in general, statistically different between the competing approaches. It is recommended to apply the VFT instead of the MXL given that the former has superior accuracy and it can be estimated when there is a relatively short crosssection of option exercise price range. The results have implications for financial investors and policy makers given that they could use the information content in options to analyze market’s perceptions about the future expected variability of the financial asset under study. Clasificación JEL: C14, C52, F31, G13.
Planificación estratégica de los recursos humanos: inherencia en la calidad de la educación
(2006) Mariela Sáez Briceño; Efrén José Pérez Nácar
The changes of educational policies worldwide create the necessity for educators to be aware of the technological processes to be able to innovate in his/her area of knowledge. Therefore, there is a need, to strategically plan the educational preparation policy of human resources in the educational level, since there is a direct relationship between this aspect and the initial and permanent preparation of the educators which demand the educational centers. It is prudent to emphasize that human resources, regardless the area, have become the greatest asset of any organization, since they guarantec the achievement of mission and * Recibido: Enero – 2006 Aprobado: Mayo – 2006 18 goal. Human resources are, then, of outmost importance in the educational system. Some authors argue that they are vital for the prosperity, survival and quality of education they agree that human resources are a key factor in the effectiveness and quality of education, as weir as a way to influence direct and effectively in the acquisition of a learning more social productive and culturally pertinent. The main purpose of this research is to accomplish a theorical approach of the influence that strategic planning of human resources may have on improving education quality, in doing so a descriptive bibliography methodology has been applied
Short-Term Production Prediction in Real Time Using Intelligent Techniques
(2013) A.. Al-Jasmi; H. K. Goel; Hatem N. Nasr; M.. Querales; Jordani Rebeschini; M.. Villamizar; G. A. Carvajal; S. Knabe; Francklin Rivas; Luigi Saputelli
Abstract Intelligent digital oilfield operations collect real-time data from an operating asset and transform that raw data into information through intelligent, automated work processes, which assist engineers with key well operations and monitoring, improving their productivity and decision-making. A major oil and gas operator in the Middle East is developing a set of intelligent workflows for key activities and processes for its production operations, with the ultimate goal of improved asset performance. Real-time surveillance and monitoring of production operation processes have proven to be operationally and economically important for managing complex, high-cost reservoirs. However, predicting short-term production and production interruptions—for example, related to pump settings—has posed a tremendous challenge. While operators routinely forecast production for the next 60 to 90 days, sophisticated tools such as full-field numerical simulation models are of limited use in predicting short-term production of 30 days. Similarly, while nodal analysis can estimate current operating conditions, it cannot be used for prediction. Because of its simplicity, rapid training, and demonstrated results, a prediction technique using neural networks (NN) has emerged as a solution that can predict short-term well production behavior with acceptable accuracy. This paper presents a case study using NNs to predict liquid rate and water cut performance in a mature reservoir with more than 20% water cut. The NN was trained using available surface and down-hole, real-time production data, time-dependent data, and completion design data. The time-dependent data are included as time series configured to let users generate scenarios by changing well operations. This approach not only provides a base-case prediction but also simulates results after making adjustments in control variables, such as tubing head pressure (THP) and pump frequency. Changing THP and frequency lets users model production to predict and circumvent negative well pump events. This project was implemented in a mature carbonate oil reservoir under waterflood in the Middle East. Despite limited reservoir data, the results show that the NN is a powerful and rapid tool that predicts liquid rate and water cut with acceptable accuracy, helping engineers make prompt decisions to prevent and reduce downtime.
Some covariance inequalities for non-monotonic functions with applications to mean-variance indifference curves and bank hedging
(Taylor & Francis, 2015) Martín Egozcue
In several problems of decision-making under uncertainty, it is necessary to study the sign of the covariance between marginal utilities. All of the works that study the covariance signs are based on Chebyschev’s integral inequality. However, this inequality requires that both functions be monotonic. There are many cases, originated basically by new alternative theories, which assume that the marginal utilities of interest are non-monotonic. Thus, we cannot use Chebyschev’s result as it relies on monotonic functions. In this article, I derive some new covariance inequalities for utility functions which have non-monotonic marginal utilities. I also apply the theoretical results to two problems in economics: First, I study some properties of the indiference curve in the mean-variance space for Prospect Theory and for Markowitz utility functions. Second, I analyze the asset hedging policies of a bank that behaves as predicted by Prospect Theory.
State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey
(Society of Petroleum Engineers, 2013) César Bravo; Luigi Saputelli; Francklin Rivas; Anna Gabriela Pérez; Michael Nikolaou; Georg Zangl; Neil de Guzmán; S. Mohaghegh; Gustavo Núñez
Summary Artificial intelligence (AI) has been used for more than 2 decades as a development tool for solutions in several areas of the exploration and production (E&P) industry: virtual sensing, production control and optimization, forecasting, and simulation, among many others. Nevertheless, AI applications have not been consolidated as standard solutions in the industry, and most common applications of AI still are case studies and pilot projects. In this work, an analysis of a survey conducted on a broad group of professionals related to several E&P operations and service companies is presented. This survey captures the level of AI knowledge in the industry, the most common application areas, and the expectations of the users from AI-based solutions. It also includes a literature review of technical papers related to AI applications and trends in the market and in research and development. The survey helped to verify that (a) data mining and neural networks are by far the most popular AI technologies used in the industry; (b) approximately 50% of respondents declared they were somehow engaged in applying workflow automation, automatic process control, rule-based case reasoning, data mining, proxy models, and virtual environments; (c) production is the area most affected by the applications of AI technologies; (d) the perceived level of available literature and public knowledge of AI technologies is generally low; and (e) although availability of information is generally low, it is not perceived equally among different roles. This work aims to be a guide for personnel responsible for production and asset management on how AI-based applications can add more value and improve their decision making. The results of the survey offer a guideline on which tools to consider for each particular oil and gas challenge. It also illustrates how AI techniques will play an important role in future developments of information-technology (IT) solutions in the E&P industry.
Stochastic Asset Models for Actuarial Use in Ghana
(RELX Group (Netherlands), 2017) Evans Tee; Eric Ofosu-Hene
The need for stochastic asset models has evolved from a common global standard for risk management in the Solvency II regime in Europe, IAIS Common Principles, Global ORSA standards NAIC, EIOPA, and OSFI. But the challenges in developing markets such as; lack of good quality data, inconsistent data coverage, market data not having long enough history, and lack of liquidity in certain parts of asset market have caused the absence of such models in Ghana. There have been a number of actuarial stochastic asset models designed for simulating future economic and investment conditions in several parts of the world. This study has discussed three of such models and determined which best fits the Ghanaian economic data. The data used for the empirical analysis in this study were taken from the Bank of Ghana database and the Ghana Stock Exchange. The study re-calibrated the models to derive the parameter set then compared the model results numerically after running 10000 simulations for 50 horizons. Investigations about the basic statistics of the simulated results for all the models are compared. The analysis revealed that all of the Ghanaian investment series used in the stochastic investment modeling are non-stationary in their mean, variance and auto-covariance. The study then found that the “Wilkie linear model” produced simulated values with similar characteristics to the historical data whiles the Whitten & Thomas TAR model produced simulated values with minimal forecast error. The study therefore suggests that since the “Wilkie linear model” has a relatively better parsimony, ready economic interpretation and its ability to mimic some important features of the Ghanaian economic series it deserves the attention of the actuary seeking to model jointly the behavior of asset returns and economic variables that matter in economic capital determination of insurance and pension business in Ghana.