A New Solvable Weak Priority Structure

2018 ◽  
Author(s):  
Jingsheng Yu ◽  
Jun Zhang
Keyword(s):  
Priority Structure

Volatility and the Priority Structure of Corporate Debt

2016 ◽  
Author(s):  
Dominique C. Badoer ◽  
Evan Dudley ◽  
Christopher M. James
Keyword(s):  
Corporate Debt ◽  
Priority Structure

scholarly journals Debtholder Monitoring Incentives and Bank Earnings Opacity

2020 ◽  
pp. 1-38
Author(s):  
Piotr Danisewicz ◽  
Danny McGowan ◽  
Enrico Onali ◽  
Klaus Schaeck
Keyword(s):  
Real Estate ◽  
Information Disclosure ◽  
Quality Of Information ◽  
Legislative Changes ◽  
Priority Structure ◽  
Real Estate Loan

Abstract We exploit exogenous legislative changes that alter the priority structure of different classes of debt to study how debtholder monitoring incentives affect bank earnings opacity. We present novel evidence that exposing nondepositors to greater losses in bankruptcy reduces earnings opacity, especially for banks with larger shares of nondeposit funding, listed banks, and independent banks. The reduction in earnings opacity is driven by a lower propensity to overstate earnings and is more pronounced among larger banks and in banks with more real estate loan exposure. Our findings highlight the importance of creditors’ monitoring incentives in improving the quality of information disclosure.

Priority structure in fuzzy goal programming

1986 ◽  
Vol 19 (3) ◽  
pp. 251-259 ◽  
Author(s):  
R.N. Tiwari ◽  
S. Dharmar ◽  
J.R. Rao
Keyword(s):  
Goal Programming ◽  
Fuzzy Goal Programming ◽  
Fuzzy Goal ◽  
Priority Structure

scholarly journals A Multi-Objective Decision-Making Approach For Mutual Fund Portfolio

2011 ◽  
Vol 4 (6) ◽  
Author(s):  
Hari P. Sharma Hari P. Sharma ◽  
Dinesh K. Sharma
Keyword(s):  
Decision Making ◽  
Mutual Fund ◽  
Investment Decision ◽  
Optimal Solution ◽  
Ideal Solution ◽  
Font Size ◽  
Distance Method ◽  
Multi Objective ◽  
Fund Portfolio ◽  
Priority Structure

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: Times New Roman;"><span style="font-size: 10pt; mso-bidi-font-style: italic;">Investment decision-making problems ar</span><span style="font-size: 10pt;">e<span style="mso-bidi-font-style: italic;"> generally multi-objective in nature such as minimization of the risk and maximization of the expected return.<span style="mso-spacerun: yes;">&nbsp; </span>These problems can be solved efficiently and effectively using multi-objective decision making (MODM) tools such as a lexicographic goal programming (LGP).<span style="mso-spacerun: yes;">&nbsp; </span>This paper applies the LGP model for selecting an optimum mutual fund portfolio for an investor, while taking into account specific parameters including risk, return, expense ratio and others.<span style="mso-spacerun: yes;">&nbsp; </span>Sensitivity analysis on the assigned weights in a priority structure of the goals identifies all possible solutions for decision-making.<span style="mso-spacerun: yes;">&nbsp; </span>The Euclidean distance method is then used, to measure distances of all possible solutions from the identified ideal solution.<span style="mso-spacerun: yes;">&nbsp; </span>The optimal solution is determined by the minimum distance between the ideal solution and other possible solutions of the problem. The associated weights with the optimal solution will be the most appropriate weights in a given priority structure.<span style="mso-spacerun: yes;">&nbsp; </span>The effectiveness and applicability of the LGP model is demonstrated via a case example from broad categories of mutual funds.</span></span></span></p>

scholarly journals On the Axiomatizability of Priority

2006 ◽  
Vol 13 (1) ◽  
Author(s):  
Luca Aceto ◽  
Taolue Chen ◽  
Willem Jan Fokkink ◽  
Anna Ingólfsdóttir
Keyword(s):  
Process Algebra ◽  
Sufficient Conditions ◽  
Equational Theory ◽  
Complete Axiomatization ◽  
Bisimulation Equivalence ◽  
Arbitrary Collection ◽  
Infinite Set ◽  
Priority Structure

This paper studies the equational theory of bisimulation equivalence over the process algebra BCCSP extended with the priority operator of Baeten, Bergstra and Klop. It is proven that, in the presence of an infinite set of actions, bisimulation equivalence has no finite, sound, ground-complete equational axiomatization over that language. This negative result applies even if the syntax is extended with an arbitrary collection of auxiliary operators, and motivates the study of axiomatizations using conditional equations. In the presence of an infinite set of actions, it is shown that, in general, bisimulation equivalence has no finite, sound, ground-complete axiomatization consisting of conditional equations over the language studied in this paper. Finally, sufficient conditions on the priority structure over actions are identified that lead to a finite, ground-complete axiomatization of bisimulation equivalence using conditional equations.

scholarly journals Dependent-Chance Goal Programming for Water Resources Management under Uncertainty

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Haiying Guo ◽  
Honghua Shi ◽  
Xiaosheng Wang
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Goal Programming ◽  
Uncertain Variable ◽  
Uncertain Measure ◽  
Unknown Parameters ◽  
Uncertainty Distribution ◽  
Resources Management ◽  
Objective Event ◽  
Priority Structure

Without sufficient data, consulting experts is a good way to quantify unknown parameters in water resources management which will result in human uncertainty. The aim of this paper is to introduce a new tool-uncertainty theory to deal with such uncertainty which is treated as uncertain variable with uncertainty distribution. And a dependent-chance goal programming (DCGP) model is provided for water resources management under such circumstance. In the model uncertain measure is used to measure possibility that an event will occur which is maximized by minimizing the deviation (positive or negative deviation) from target of objective event under a given priority structure. In the end, the developed model is applied to a numerical example to illustrate the effectiveness of the model. The result obtained contributes to the desired water-allocation schemes for decision-markers.

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