Stochastic Fuzzy Algorithms for Impairment of Assets Management

The present paper aims to analyze the impairment of tangible assets with the help of artificial intelligence. Stochastic fuzzy numbers have been introduced with a dual purpose: on one hand to estimate the cash flows generated by tangible assets exploitation and, on the other hand, to ensure the value ranges stratifications that define these cash flows. Estimation of cash flows using stochastic fuzzy numbers was based on cash flows generated by tangible assets in previous periods of operation. Also, based on the Lagrange multipliers, were introduced: the objective function of minimizing the standard deviations from the recorded value of the cash flows generated by the tangible assets, as well as the constraints caused by the impairment of tangible assets identification according to which the cash flows values must be equal to the annual value of the invested capital. Within the determination of the impairment value and stratification of the value ranges determined by the cash flows using stochastic fuzzy numbers, the impairment of assets risk was identified. Information provided by impairment of assets but also the impairment risks, is the basis of the decision-making measures taken to mitigate the impact of accumulated impairment losses on company’s financial performance

Detecting financial sustainability risk of the assets using MAMDANI fuzzy controller

The paper aims to develop a MAMDANI fuzzy controller for detecting the financial sustainability risk of the assets owned by the company. This type of risk indicates when an asset no longer produces economic benefits to the company, or the benefits are small enough to no longer justify the asset maintaining in working order. The proposed fuzzy controller has as input variables the asset operating expenses and the variation of this category of expenses from one analysis period to another. The controller's objective function is to keep operating costs at their initial state and thus reducing the financial sustainability risk. The controller's output variable is represented by the economic benefits variation, considered to be an essential component in the financial sustainability risk analysis. The obtained results were interpreted taking into account the objective function of the controller as well as the evolution of the input variables. Two simulations for fuzzy controllers were made, with the mention that the variation ranges for the input variables were delimited. In practice, fuzzy controllers can be generated according to company policies to keep under control the expense categories that accompany the asset exploitation

Optimization of Financial Asset Neutrosophic Portfolios

The purpose of this paper was to model, with the help of neutrosophic fuzzy numbers, the optimal financial asset portfolios, offering additional information to those investing in the capital market. The optimal neutrosophic portfolios are those categories of portfolios consisting of two or more financial assets, modeled using neutrosophic triangular numbers, that allow for the determination of financial performance indicators, respectively the neutrosophic average, the neutrosophic risk, for each financial asset, and the neutrosophic covariance as well as the determination of the portfolio return, respectively of the portfolio risk. There are two essential conditions established by rational investors on the capital market to obtain an optimal financial assets portfolio, respectively by fixing the financial return at the estimated level as well as minimizing the risk of the financial assets neutrosophic portfolio. These conditions allowed us to compute the financial assets’ share in the total value of the neutrosophic portfolios, for which the financial return reaches the level set by investors and the financial risk has the minimum value. In financial terms, the financial assets’ share answers the legitimate question of rational investors in the capital market regarding the amount of money they must invest in compliance with the optimal conditions regarding the neutrosophic return and risk

Modeling the Covariance of Financial Assets Using Neutrosophic Fuzzy Numbers

This paper aims to model the covariance of financial assets using neutrosophic fuzzy numbers. Two main concepts are discussed and used, namely the neutrosophic covariance of the financial assets and the independent neutrosophic portfolios. In terms of methodology, a three-step approach is proposed with the purpose of identifying the independent neutrosophic portfolio return, the independent neutrosophic portfolio risk and the structure of the independent neutrosophic portfolio. For this purpose, neutrosophic fuzzy theory is chosen for this type of approach as it allows a proper modeling of the financial performance indicators by taking into account the probabilities of their achievement. This action is possible even in the situation in which linguistic variables are used for better characterizing the values of the recorded data. Numerical examples are provided in each stage of the methodology description for a better understanding of the proposed approach. The results of the study can be used to substantiate the decisions made by the capital market investors

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

As companies operate in a competitive environment, where the struggle for survival on the market is rather tough, the top management face new challenges to identify methods, and even techniques, which allows it to select from the market those assets that provide an optimal ratio between the acquisition cost and the economic performance. In this context, a fuzzy logic managerial decision tool for the assets acquisition is proposed with the paper. The algorithm has three main components: the matrix of the membership degree of the existing bids to asset selection criteria, using fuzzy triangular numbers; the vector of the global membership degree of the bids to the selection criteria and the maximum of the global membership degree as an inference operator for establishing the validated bids by the algorithm. Two scenarios of asset acquisition were tested. After simulations, it was determined that the proposed fuzzy logic managerial decision tool combines, with very good results, the acquisition cost of the assets with their economic performance

Neutrosophic Portfolios of Financial Assets. Minimizing the Risk of Neutrosophic Portfolios

This paper studies the problem of neutrosophic portfolios of financial assets as part of the modern portfolio theory. Neutrosophic portfolios comprise those categories of portfolios made up of financial assets for which the neutrosophic return, risk and covariance can be determined and which provide concomitant information regarding the probability of achieving the neutrosophic return, both at each financial asset and portfolio level and also information on the probability of manifestation of the neutrosophic risk. Neutrosophic portfolios are characterized by two fundamental performance indicators, namely: the neutrosophic portfolio return and the neutrosophic portfolio risk. Neutrosophic portfolio return is dependent on the weight of the financial assets in the total value of the portfolio but also on the specific neutrosophic return of each financial asset category that enters into the portfolio structure. The neutrosophic portfolio risk is dependent on the weight of the financial assets that enter the portfolio structure but also on the individual risk of each financial asset. Within this scientific paper was studied the minimum neutrosophic risk at the portfolio level, respectively, to establish what should be the weight that the financial assets must hold in the total value of the portfolio so that the risk is minimum. These financial assets weights, after calculations, were found to be dependent on the individual risk of each financial asset but also on the covariance between two financial assets that enter into the portfolio structure. The problem of the minimum risk that characterizes the neutrosophic portfolios is of interest for the financial market investors. Thus, the neutrosophic portfolios provide complete information about the probabilities of achieving the neutrosophic portfolio return but also of risk manifestation probability. In this context, the innovative character of the paper is determined by the use of the neutrosophic triangular fuzzy numbers and by the specific concepts of financial assets, in order to substantiating the decisions on the financial markets

CREATING CAPITAL MARKETS UNION. OPPORTUNITIES AND LIMITATIONS.

Union of European Capital Markets is a recent initiative of the European Commission, issued the credit crunch from EU. This paper aims to discuss the advantages and disadvantages of this Union, estimated to be achieved by 2019. At the same time, we intend to analyze the opportunities and limits of achieving this union, its impact on European integration and the Member States, on the expansion possibilities of funding SMEs, on sustainable economic development. In our opinion, the project to union capital markets from the European Union is commendable, following completion of more and more domestic companies could obtain financing from international capital markets

The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy

This paper develops a Mamdani fuzzy logic system (FLS) that has stochastic fuzzy input variables designed to identify cash-flow deficits in bank lending policies. These deficits do not cover the available cash-flow (CFA) resulting from the company’s operating activity. Thus, due to these deficits, solutions must be identified to avoid companies’ financial difficulties. The novelty of this paper lies in its using stochastic fuzzy variables, or those categories of variables that are defined by fuzzy sets, characterized by normally distributed density functions specific to random variables, and characterized by fuzzy membership functions. The variation intervals of the stochastic fuzzy variables allow identification of the probabilistic risk situations to which the company is exposed during the crediting period using the Mamdani-type fuzzy logic system. The mechanism of implementing the fuzzy logic system is based on two stages. The first is based on the determination of the cash-flow requirements resulting from loan reimbursement and interest rates. This stage has the role of determining the need for financial resources to cover the liabilities. The second stage is based on the identification of the stochastic fuzzy variables which have a role in influencing the cash flow deficits and the probability values estimation of these variables taking into account probability calculations. Based on these probabilistic values, using the Mamdani fuzzy logic system, estimations are computed for the available cash-flow (the output variable). The estimated values for CFA are then used to detect probability risk situations in which the company will not have enough resources to cover its liabilities to financial creditors. All the FLS calculations refer to future time periods. Testing and simulating the fuzzy controller confirms its functionality

Modeling the Performance Indicators of Financial Assets with Neutrosophic Fuzzy Numbers

This research sets the basis for modeling the performance indicators of financial assets using triangular neutrosophic fuzzy numbers. This type of number allows for the modeling of financial assets performance indicators by taking into consideration all the possible scenarios of their achievement. The key performance indicators (KPIs) modeled with the help of triangular fuzzy neutrosophic numbers are the return on financial assets, the financial assets risk, and the covariance between financial assets. Thus far, the return on financial assets has been studied using statistical indicators, like the arithmetic and geometric mean, or using the financial risk indicators with the help of the squared deviations from the mean and covariance. These indicators are well known as the basis of portfolio theory. This paper opens the perspective of modeling these three mentioned statistical indicators using triangular neutrosophic fuzzy numbers due to the major advantages they have. The first advantage of the neutrosophic approach is that it includes three possible symmetric scenarios of the KPIs achievement, namely the scenario of certainty, the scenario of non-realization, and the scenario of indecision, in which it cannot be appreciated whether the performance indicators are or are not achieved. The second big advantage is its data series clustering, representing the financial performance indicators by which these scenarios can be delimitated by means of neutrosophic fuzzy numbers in very good, good or weak performance indicators. This clustering is realized by means of the linguistic criteria and measuring the belonging degree to a class of indicators using fuzzy membership functions. The third major advantage is the selection of risk mitigation analysis scenarios and the formation of financial assets’ optimal portfolios

THE INFORMATION CONFIDENTIALITY AND CYBER SECURITY IN MEDICAL INSTITUTIONS

The information confidentiality and cyber security risk affects the right to confidentiality and privacy of the patient, as regulated in Romania by the Law 46/2002. The manifestation of the cyber security risk event affects the reputation of the healthcare institution and is becoming more and more complex and often due to the: development of network technology, the medical equipment connected to wifi and the electronic databases. The databases containing medical records were implemented due to automation. Thus, transforming data into medical knowledge contribute to a better understanding of the disease. Due to these factors, the measures taken by the hospital management for this type of risk are adapted to the cyber changes. The hospital objectives aim: the implementation of a robust information system, the early threats identifications and the incident reporting. Neglecting this type of risk can generate financial loss, inability to continue providing health care services for a certain period of time, providing an erroneous diagnosis, medical equipment errors etc. Thus, in a digital age the appropriate risk management for the information security and cyber risk represent a necessity. The main concern of hospitals worldwide is to align with international requirements and obtain credentials in terms of data security from the International Organisation for Standardization, which regulates the management of this type of risk. Romania is at the beginning in terms of concerns regarding the management, avoidance and mitigation of information security, the health system being most highly exposed to its manifestation. The present paper examines the concerns of the health system to the confidentiality of information and cyber security risk and its management arrangements. Thus, a set of key risk indicators is implemented and monitored for 2011-2013, using a user interface, a Dashboard, which acts as an early warning system of the manifestation of the risk event in a hospital from western Romania