3,413 research outputs found
Operational risk management and new computational needs in banks
Basel II banking regulation introduces new needs for computational schemes. They involve both optimal stochastic control, and large scale simulations of decision processes of preventing low-frequency high loss-impact events. This paper will first state the problem and present its parameters. It then spells out the equations that represent a rational risk management behavior and link together the variables: Levy processes are used to model operational risk losses, where calibration by historical loss databases is possible ; where it is not the case, qualitative variables such as quality of business environment and internal controls can provide both costs-side and profits-side impacts. Among other control variables are business growth rate, and efficiency of risk mitigation. The economic value of a policy is maximized by resolving the resulting Hamilton-Jacobi-Bellman type equation. Computational complexity arises from embedded interactions between 3 levels: * Programming global optimal dynamic expenditures budget in Basel II context, * Arbitraging between the cost of risk-reduction policies (as measured by organizational qualitative scorecards and insurance buying) and the impact of incurred losses themselves. This implies modeling the efficiency of the process through which forward-looking measures of threats minimization, can actually reduce stochastic losses, * And optimal allocation according to profitability across subsidiaries and business lines. The paper next reviews the different types of approaches that can be envisaged in deriving a sound budgetary policy solution for operational risk management, based on this HJB equation. It is argued that while this complex, high dimensional problem can be resolved by taking some usual simplifications (Galerkin approach, imposing Merton form solutions, viscosity approach, ad hoc utility functions that provide closed form solutions, etc.) , the main interest of this model lies in exploring the scenarios in an adaptive learning framework ( MDP, partially observed MDP, Q-learning, neuro-dynamic programming, greedy algorithm, etc.). This makes more sense from a management point of view, and solutions are more easily communicated to, and accepted by, the operational level staff in banks through the explicit scenarios that can be derived. This kind of approach combines different computational techniques such as POMDP, stochastic control theory and learning algorithms under uncertainty and incomplete information. The paper concludes by presenting the benefits of such a consistent computational approach to managing budgets, as opposed to a policy of operational risk management made up from disconnected expenditures. Such consistency satisfies the qualifying criteria for banks to apply for the AMA (Advanced Measurement Approach) that will allow large economies of regulatory capital charge under Basel II Accord.REGULAR - Operational risk management, HJB equation, Levy processes, budget optimization, capital allocation
Algebraic dependences of meromorphic mappings in several complex variables
We give some theorems on algebraic dependence of meromorphic mappings in several complex variables into complex projective spaces.Наведено деякі теореми про алгебраїчну залежність мероморфних відображень для багатьох комплексних змінних на комплексні проективні простори
Commutative algebraic groups and -adic linear forms
Let be a commutative algebraic group defined over a number field that
is disjoint over to and satisfies the condition of
semistability. Consider a linear form on the Lie algebra of with
algebraic coefficients and an algebraic point in a -adic neighbourhood
of the origin with the condition that does not vanish at . We give a
lower bound for the -adic absolute value of which depends up to an
effectively computable constant only on the height of the linear form, the
height of the point and .Comment: This is a preprint of the Materials accepted for publication in "Acta
Arithmetica
Changes of benthic macroinvertebrates in Thi Vai River and Cai Mep Estuaries under polluted conditions with industrial wastewater
The pollution on the Thi Vai River has been spreading out rapidly over the two lasted decades caused by the wastewater from the industrial parks in the left bank of Thi Vai River and Cai Mep Estuaries. The evaluation of the benthic macroinvertebrate changes was very necessary to identify the consequences of the industrial wastewater on water quality and aquatic ecosystem of Thi Vai River and Cai Mep Estuaries.
In this study, the variables of benthic macroinvertebrates and water quality were investigated in Thi Vai River and Cai Mep Estuaries, Southern Vietnam. The monitoring data of benthic macroinvertebrates and water quality parameters covered the period from 1989 to 2015 at 6 sampling sites in Thi Vai River and Cai Mep Estuaries. The basic water quality parameters were also tested including pH, dissolved oxygen (DO), total nitrogen, and total phosphorus. The biodiversity indices of benthic macroinvertebrates were applied for water quality assessment.
The results showed that pH ranged from 6.4 – 7.6 during the monitoring. The DO concentrations were in between 0.20 – 6.70 mg/L. The concentrations of total nitrogen and total phosphorous ranged from 0.03 – 5.70 mg/L 0.024 – 1.380 mg/L respectively. Macroinvertebrate community in the study area consisted of 36 species of polychaeta, gastropoda, bivalvia, and crustacea, of which, species of polychaeta were dominant in species number. The benthic macroinvertebartes density ranged from 0 – 2.746 individuals/m2 with the main dominant species of Neanthes caudata, Prionospio malmgreni, Paraprionospio pinnata, Trichochaeta carica, Maldane sarsi, Capitella capitata, Terebellides stroemi, Euditylia polymorpha, Grandidierella lignorum, Apseudes vietnamensis. The biodiversity index values during the monitoring characterized for aquatic environmental conditions of mesotrophic to polytrophic. Besides, species richness positively correlated with DO, total nitrogen, and total phosphorus. The results confirmed the advantage of using benthic macroinvertebrates and their indices for water quality assessment
The DKAP Project The Country Report of Vietnam
Viet Nam is at the beginning of the Fourth Industrial Revolution. In order to grasp the opportunities that the revolution has brought about, and to successfully build the society of digital citizens, there must be the demand of enhancing the capacity and capability for students to meet international standards in terms of Information and Communications Technology (ICT) skills. Viet Nam was selected as one of the four countries (Viet Nam, Bangladesh, Fiji, and the Republic of Korea) to join UNESCO Bangkok’s “Digital Kids Asia Pacific (DKAP)” project, a comparative cross-national study with the aim to seek the understanding and address children’s ICT practices, attitudes, behaviors, and competency levels within an educational context. Thanks to the project, the Vietnamese research team completely conducted the survey in twenty (20) schools from five (5) provinces in Viet Nam. With the data on the digital citizenship competency levels of 1,061 10th grade students, the research team discovered the valuable findings to draw an initial big picture for Vietnamese policy makers, educators, and teachers about digital citizenship competencies of 15-year-old Vietnamese students
Influence of water temperature and salinity on pH during dry season in lower Dong Nai river system, Vietnam
This paper uses the gvSIG 2.2.0 software, IDW interpolation method, river and stream network data, and 36 sampling sites to build the maps of three monitored parameters such as pH, water temperature, and salinity in the Lower Dong Nai River system (2009–2010) in dry season. Based on an analysis of these maps and statistical assessment by using the R software, the correlations between pH, temperature, and salinity are clarified. The results show that the pH and temperature values have a tendency to decrease, whereas the salinity tends to increase annually. The pH value has good and significant correlations with the water temperature and salinity in both simple and multiple linear regression models. The results aim to provide a scientific reference for further research on the water environment in this area
Self-healing composites: A review
Self-healing composites are composite materials capable of automatic recovery when damaged. They are inspired by biological systems such as the human skin which are naturally able to heal themselves. This paper reviews work on self-healing composites with a focus on capsule-based and vascular healing systems. Complementing previous survey articles, the paper provides an updated overview of the various self-healing concepts proposed over the past 15 years, and a comparative analysis of healing mechanisms and fabrication techniques for building capsules and vascular networks. Based on the analysis, factors that influence healing performance are presented to reveal key barriers and potential research directions
The bees algorithm: Modelling nature to solve complex optimisation problems
The Bees Algorithm models the foraging behaviour of honey bees in order to solve optimisation problems. The algorithm performs a kind of exploitative neighbourhood search combined with random explorative search. This paper describes the Bees Algorithm and presents two application examples: the training of neural networks to predict the energy efficiency of buildings, and the solution of the protein folding problem. The Bees Algorithm proved its effectiveness and speed, and obtained very competitive modelling accuracies compared with other state-of-the-art methods
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