Arbitrage-free interval of American contingent claims under proportional transaction cost

In a general continuous-time market model with proportional transaction costs, we derive the range of arbitrage-free prices of American contingent claims. Using a martingale approach, we obtain the upper and the lower hedging price of American contingent claims.     

Arbitrage-free interval of American contingent claims under proportional transaction cost

In a general continuous-time market model with proportional transaction costs, we derive the range of arbitrage-free prices of American contingent claims. Using a martingale approach, we obtain the upper and the lower hedging price of American contingent claims.     

Experiences in the pricing of trivariate contingent claims with finite difference methods on a massively parallel computer

Finite difference schemes have proved to be very flexible numerical methods for the pricing of contingent claims with one and two underlying state variables. This flexibility and the steady stream of new complex financial instruments imply that finite difference schemes for the valuation of contingent claims with three underlying state variables can supposedly be very useful. In this paper, two such schemes are developed and tested. For practical purposes, numerical valuation of contingent claims with three underlying state variables by means of finite difference methods is probably too laborious computationally to be performed on a single processor computer. Many calculations can, however, be performed in parallel. Therefore, the methods are well suited to be executed on a massively parallel computer, like the Connection Machine CM-200, which is used in this paper. The accuracy of the schemes proposed in this paper suggests that valuation of multivariate contingent claims with the help of finite difference methods on a massively parallel computer can be a useful approach for academics as well as practitioners.     

Integrated use of fuzzy c-means and convex programming for capacitated multi-facility location problem

In this study a fuzzy c-means clustering algorithm based method is proposed for solving a capacitated multi-facility location problem of known demand points which are served from capacitated supply centres. It involves the integrated use of fuzzy c-means and convex programming. In fuzzy c-means, data points are allowed to belong to several clusters with different degrees of membership. This feature is used here to split demands between supply centers. The cluster number is determined by an incremental method that starts with two and designated when capacity of each cluster is sufficient for its demand. Finally, each group of cluster and each model are solved as a single facility location problem. Then each single facility location problem given by fuzzy c-means is solved by convex programming which optimizes transportation cost is used to fine-tune the facility location. Proposed method is applied to several facility location problems from OR library (Osman & Christofides, 1994) and compared with centre of gravity and particle swarm optimization based algorithms. Numerical results of an asphalt producer’s real-world data in Turkey are reported. Numerical results show that the proposed approach performs better than using original fuzzy c-means, integrated use of fuzzy c-means and center of gravity methods in terms of transportation costs.     

A mixed integer nonlinear programming model and heuristic solutions for location,inventory and pricing decisions in a closed loop supply chain

We analyze a network design problem for a closed-loop supply chain that integrates the collection of the used products with the distribution of the new products. We present a mixed integer nonlinear facility location-inventory-pricing model to decide on the optimal locations of the facilities, inventory amounts, prices for new products and incentive values for the collection of right amount of used products in order to maximize the total supply chain profit. We develop heuristics for the solution of this model and analyze the effectiveness of these heuristics and the effects of the parameters on this system through numerical experiments.     

The value of modeling with reference effects in stochastic inventory and pricing problems

We analyze a periodic review inventory system in which the random demand is contingent on the current price and the reference price. The reference price captures the price history and acts as a benchmark against which the current price is compared. The randomness is due to additive and multiplicative random terms. The objective is to maximize the discounted expected profit over the selling horizon by dynamically deciding on the optimal pricing and replenishment policy for each period. We study three key issues using numerical computation and simulation. First, we study the effects of reference price mechanism on the total expected profit. It is shown that high dependence on a good history increases the profit. Second, we investigate the value of dynamic programming and show that the firm that ignores the dynamic structure suffers from the revenue. Third, we analyze the value of estimating the correct demand model with reference effects. We observe that this value is significant when the inventory related costs are low.     

Causal attributions of success and failure made by undergraduate students in an introductory-level computer programming course

The purpose of this research is to identify the causal attributions of business computing students in an introductory computer programming course, in the computer science department at Notre Dame University, Louaize. Forty-five male and female undergraduates who completed the computer programming course that extended for a 13-week semester participated. Narrative interviews were conducted to obtain their perceptions. While some research confirmed that the four most responsible causes for success and failure in achievement contexts are ability, effort, task difficulty, and luck, this research shows that in its context ‘ability’ and ‘luck’ were absent, and ‘task difficulty’ and ‘effort’ were almost absent. In all, participants made 10 causal attributions that were either cultural or specific to computer programming. The 10 causal attributions are ‘learning strategy’, ‘lack of study’, ‘lack of practice’, ‘subject difficulty’, ‘lack of effort’, ‘appropriate teaching method’, ‘exam anxiety’, ‘cheating’, ‘lack of time’, and ‘unfair treatment’. All high achievers cited appropriate ‘learning strategy’.     

A study of the relationships among learning styles, participation types, and performance in programming language learning supported by online forums

This study is focused on the relationships among learning styles, participation types, and learning performance for programming language learning supported by an online forum. Kolb’s learning style inventory was used in this study to determine a learner’s learning type: ‘Diverger’, ‘Assimilator’, ‘Converger’, and ‘Accommodator’. Social Learning Theory was also used to define four participation types. These types in turn were used to describe the learning associated with the use of online forums: ‘Replier’, ‘Asker’, ‘Watcher’, and ‘No activity’.A total of 144 students participated in this experiment as part of a half semester ASP.NET programming language learning courses. The course contained an online forum for supporting the students’ social activities and participation. In this study, ‘learning score’ and ‘satisfaction’ were used to measure learning performance.The results of this study were the following: (1) different learning styles were associated with significantly different learning scores and that the ‘Accommodator’ style was associated with superior learning scores; (2) participation types were also associated with significantly different learning scores and that the ‘Replier’ type is associated with superior learning scores; (3) learning satisfaction is not significantly different among the different learning styles or different participation types, but the average is significantly higher than average values (3.5) of 7-point Likert scale; (4) there is no significant association between learning styles and participation types. Explanations and discussions of these results are offered.Based on the results of this study, we propose that programming language learning, supported with online forums and students’ active participation, increases learning performance as measured by student learning scores.