scholarly journals Fuzzy Portfolio Selection Problem with Different Borrowing and Lending Rates

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Chen ◽  
Yiping Yang ◽  
Hui Ma
Keyword(s):  
Interest Rates ◽  
Portfolio Selection ◽  
Theory And Practice ◽  
Optimal Decision ◽  
Fuzzy Variables ◽  
Portfolio Problem ◽  
Possibility Distributions ◽  
Optimal Decision Making ◽  
The Impact ◽  
Mean Variance

As we know, borrowing and lending risk-free assets arise extensively in the theory and practice of finance. However, little study has ever investigated them in fuzzy portfolio problem. In this paper, the returns of each assets are assumed to be fuzzy variables, then following the mean-variance approach, a new possibilistic portfolio selection model with different interest rates for borrowing and lending is proposed, in which the possibilistic semiabsolute deviation of the return is used to measure investment risk. The conventional probabilistic mean variance model can be transformed to a linear programming problem under possibility distributions. Finally, a numerical example is given to illustrate the modeling idea and the impact of borrowing and lending on optimal decision making.

Model Analysis of Optimal Pollution Tax under Environment Rent Philosophy

2012 ◽  
Vol 524-527 ◽  
pp. 3411-3415
Author(s):  
Miao Sheng Chen ◽  
Hui Ling Lu
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Model Analysis ◽  
Optimal Decision ◽  
Pollution Tax ◽  
Mathematical Equations ◽  
Pollution Taxation ◽  
Optimal Decision Making ◽  
The Impact

This paper uses the concept of environment rent philosophy to explain rationale for government taxation and principles of taxation, and uses mathematical models to specifically discuss practical problems of government pollution taxation under this philosophy. The model provides mathematical equations for optimal decision-making by consumers, producers, and government and analyzes the impact of changes in taxation rates on the three parties.

scholarly journals Optimal Decision Making in Electrical Systems Using an Asset Risk Management Framework

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4987
Author(s):  
David L. Alvarez ◽  
Diego F. Rodriguez ◽  
Alben Cardenas ◽  
F. Faria da da Silva ◽  
Claus Leth Leth Bak ◽  
...  
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Power Transformer ◽  
Risk Index ◽  
Mathematical Optimization ◽  
Optimal Decision ◽  
Health Index ◽  
Electrical Systems ◽  
Optimal Decision Making ◽  
The Impact

In this paper, a methodology for optimal decision making for electrical systems is addressed. This methodology seeks to identify and to prioritize the replacement and maintenance of a power asset fleet optimizing the return of investment. It fulfills this objective by considering the risk index, the replacement and maintenance costs, and the company revenue. The risk index is estimated and predicted for each asset using both its condition records and by evaluating the consequence of its failure. The condition is quantified as the probability of failure of the asset, and the consequence is determined by the impact of the asset failure on the whole system. Failure probability is estimated using the health index as scoring of asset condition. The consequence is evaluated considering a failure impact on the objectives of reliability (energy not supplied -ENS), environment, legality, and finance using Monte Carlo simulations for an assumed period of planning. Finally, the methodology was implemented in an open-source library called PywerAPM for assessing optimal decisions, where the proposed mathematical optimization problem is solved. As a benchmark, the power transformer fleet of the New England IEEE 39 Bus System was used. Condition records were provided by a local utility to compute the health index of each transformer. Subsequently, a Monte Carlo contingency simulation was performed to estimate the energy not supplied for a period of analysis of 10 years. As a result, the fleet is ranked according to risk index, and the optimal replacement and maintenance are estimated for the entire fleet.

scholarly journals Dynamic Optimal Mean-Variance Portfolio Selection with a 3/2 Stochastic Volatility

Risks ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 61
Author(s):  
Yumo Zhang
Keyword(s):  
Stochastic Volatility ◽  
Portfolio Selection ◽  
Stock Price ◽  
Backward Stochastic Differential Equation ◽  
Time Inconsistency ◽  
Optimal Time ◽  
Model Parameters ◽  
Mean Variance Portfolio ◽  
The Impact ◽  
Mean Variance

This paper considers a mean-variance portfolio selection problem when the stock price has a 3/2 stochastic volatility in a complete market. Specifically, we assume that the stock price and the volatility are perfectly negative correlated. By applying a backward stochastic differential equation (BSDE) approach, closed-form expressions for the statically optimal (time-inconsistent) strategy and the value function are derived. Due to time-inconsistency of mean variance criterion, a dynamic formulation of the problem is presented. We obtain the dynamically optimal (time-consistent) strategy explicitly, which is shown to keep the wealth process strictly below the target (expected terminal wealth) before the terminal time. Finally, we provide numerical studies to show the impact of main model parameters on the efficient frontier and illustrate the differences between the two optimal wealth processes.

Understanding User Decision Making and the Value of Improved Precipitation Forecasts: Lessons From a Case Study

2004 ◽  
Vol 85 (2) ◽  
pp. 223-236 ◽  
Author(s):  
Thomas R. Stewart ◽  
Roger Pielke ◽  
Radhika Nath
Keyword(s):  
Decision Making ◽  
New York ◽  
New York State ◽  
Holistic Approach ◽  
Optimal Decision ◽  
Weather Information ◽  
Optimal Decision Making ◽  
Decision Making Model ◽  
The Impact

A case study of the impact of improved precipitation forecasts on the snow-fighting operations of the New York State Thruway is reported. The goal was to use currently available data and literature on forecast process, communication, and use in conjunction with observations and interviews with key decision makers to derive a model that yields estimates of value to users based on a model of their decision processes rather than an optimal decision-making model. That goal proved too ambitious due to limitations in available data. A major lesson learned from this research is the importance of improved, ongoing data collection to support studies of use and value of weather information. A more holistic approach to understanding and realizing forecast value is needed, that is, one in which information (both of forecast skill and usage) centered on the decision process is collected in a much more intensive manner than is presently the case.

scholarly journals A MONETARY ANALYSIS OF GHANA: EXAMINING THE IMPACT AND THE CAUSAL RELATIONSHIP BETWEEN MONETARY POLICY AND INFLATION IN GHANA

2020 ◽  
Vol 4 (1) ◽  
pp. 1-14
Author(s):  
Edmund Obeng Amaning ◽  
Ali Napari Seidu
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Causal Relationship ◽  
Money Supply ◽  
Time Series Data ◽  
Positive Impact ◽  
Negative Relationship ◽  
Theory And Practice ◽  
Series Data ◽  
The Impact

Purpose: The main objective of the study was to examine the impact and the causal relationship between monetary policy and inflation in Ghana.Methodology: Annual time series data spanning from 1985 to 2017 with Auto Regressive Distributed Lagged (ARDL) model were employed for the analysis.Findings: The outcome from the study shows that, monetary policy rate had insignificant negative relationship with inflation in both the short and the long run. Again, interest rate, domestic investment and money supply were found to have significant positive impact on inflation in both the long and the short run for a specific period chosen for the study.The causal relationship shows that monetary policy rate granger causes money supply within the period understudyUnique contribution to theory and practice: The study recommends that policy makers need to keenly consider the levels of money supply in Ghana so as to ensure a stable retail price levels. The Government of Ghana needs to evaluate the prevailing levels of retail prices and set the interest rates on the 91-day Treasury bills because they are majorly treated as risk free rate hence determines other interest rates and inflation levels in Ghana.

scholarly journals Risk and Financial Management Practice in the Construction Sector in Nigeria, System Thinking Perspective

2014 ◽  
Vol 41 ◽  
pp. 165-175
Author(s):  
Samuel B. Ekung
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Financial Management ◽  
Construction Projects ◽  
Management Practice ◽  
System Thinking ◽  
Optimal Decision ◽  
Optimal Decision Making ◽  
The Individual ◽  
The Impact

Risk and financial management of construction projects have been widely studied using different approaches and systems. Three basic frontiers underpin project management research in this area: normative; descriptive; and instrumental. The descriptive approach deals with how project managers perceive and represent risks that is, risk analysis. Instrumental approach study’s the impact of risk management on projects and the organisation. This perspective informs the premise in which studies that seek to justify the need for risk management are based. The normative approach identifies the moral and ethical linkages between the individual, organisations and supra system and risk management practice. While a vast of number of studies have been descriptive and instrumental, very few however address systemic issues impacting risk and financial management practice. This paper sets out to reflect on the risk and financial management practice in Nigeria using system approaches. It is a critical appraisal involving SLEEPT, Multiple goal and the GESTALT theories. In reprising the problem, the report assessed the national economy of Nigeria using SLEEPT, with a view to establishing whether it is situated in extremistan or mediocristan. The organisation, a sub-system of the supra system is evaluated to establish its links with the supra system using GESTALT. A refinement is carried out based on these analyses in order to achieve congruence and to establish a baseline upon which risk and financial can be improved. The analysis reveals social, political, environmental and economic context of the supra system are in extremistan while the legal and technology are in mediocristan. The linkage in the different systems is anchored on decision making by the individual. Optimal decision making is therefore formulated using interactive framework.

scholarly journals Five Steps Towards Avoiding Narrative Traps in Decision-Making

2021 ◽  
Vol 12 ◽  
Author(s):  
Paul Dolan ◽  
Amanda Henwood
Keyword(s):  
Decision Making ◽  
Optimal Decision ◽  
Uncertain Environment ◽  
Simple Rules ◽  
Optimal Decision Making ◽  
Dominant Narratives ◽  
The Impact ◽  
High Uncertainty

Narratives provide simple rules about how we ought to live and what our priorities ought to be. They are especially appealing in times of high uncertainty. Using the uncertainty surrounding Covid-19 as an illustration, we show how a narrative to preserve life has become dominant, and we illustrate how it has been reinforced by several behavioural biases. We argue that being able to identify and critically evaluate the impact of dominant narratives is vital to ensuring optimal decision-making. To facilitate this, we offer five recommendations—the ABCDE of decision-making—that can help to reduce the “narrative trap” in decision-making in any uncertain environment.

scholarly journals Geospatial Analysis and Mapping Strategies for Fine-Grained and Detailed COVID-19 Data with GIS

2021 ◽  
Vol 10 (9) ◽  
pp. 602
Author(s):  
Angel Miramontes Carballada ◽  
Jose Balsa-Barreiro
Keyword(s):  
Geospatial Analysis ◽  
Optimal Decision ◽  
Sensitive Information ◽  
Fine Grained ◽  
Health Authorities ◽  
Public Health Authorities ◽  
The Face ◽  
Predictive Risk ◽  
Optimal Decision Making ◽  
The Impact

The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects.

Sign in / Sign up

Export Citation Format

Share Document