Ioannis N. Grigoriadis, Instilling Religion in Greek and Turkish Nationalism: A”Sacred Synthesis”

Book Revie

Time and volume based optimal pricing strategies for telecommunication networks

In the recent past, there have been several initiatives by major network providers such as Turk Telekom lead the industry towards network capacity distribution in Turkey. In this study, we use a monopoly pricing model to examine the optimal pricing strategies for “pay-per-volume” and “pay-per-time” based leasing of data networks. Traditionally, network capacity distribution includes short/long term bandwidth and/or usage time leasing. Each consumer has a choice to select volume based pricing or connection time based pricing. When customers choose connection time based pricing, their optimal behavior would be utilizing the bandwidth capacity fully therefore it can cause network to burst. Also, offering pay-per-volume scheme to the consumer provides the advantage of leasing the excess capacity for other potential customers for network provider. We examine the following issues in this study: (i) What are the extra benefits to the network provider for providing the volume based pricing scheme? and (ii) Does the amount of demand (number of customers enter the market) change? The contribution of this paper is to show that pay-per-volume is a viable alternative for a large number of customers, and that judicious pricing for pay-per-volume is profitable for the network provider

Performance Analysis for Mesh and Mesh-Spectral Archetype Applications

This document outlines a simple method for benchmarking a parallel communication library and for using the results to model the performance of applications developed with that communication library. We use compositional performance analysis - decomposing a parallel program into its modular parts and analyzing their respective performances - to gain perspective on the performance of the whole program. This model is useful for predicting parallel program execution times for different types of program archetypes, (e.g., mesh and mesh-spectral) using communication libraries built with different message-passing schemes (e.g., Fortran M and Fortran with MPI) running on different architectures (e.g., IBM SP2 and a network of Pentium personal computers)

The effects of qos level degradation cost on provider selection and task allocation model in telecommunication networks

Firms acquire network capacity from multiple suppliers which offer different Quality of Service (QoS) levels. After acquisition, day-to-day operations such as video conferencing, voice over IP and data applications are allocated between these acquired capacities by considering QoS requirement of each operation. In optimal allocation scheme, it is generally assumed each operation has to be placed into resource that provides equal or higher QoS Level. Conversely, in this study it is showed that former allocation strategy may lead to suboptimal solutions depending upon penalty cost policy to charge degradation in QoS requirements. We model a cost minimization problem which includes three cost components namely capacity acquisition, opportunity and penalty due to loss in QoS

Proceedings of the Conference on Emerging Economic Issues in a Globalizing World

In this paper, we empirically examine the short term overreaction effect in the Istanbul Stock Exchange using daily stock data from January 1999 to December 2003. The study period covers the pre- and post- Turkish financial crisis period. Consistent with other prior studies on other markets, we find evidence of short term overreaction effect in the Istanbul Stock Exchange prior and post financial crisis. Our analysis highlights that stocks that display a large price increase (winners) show an evidence of overreaction in the short run, however, stocks that display a large price decline (losers) indicate no significant evidence. We also find the price reversal for winners in pre-crisis period is more pronounced than in post-crisis period. These results indicate a diminished degree of overreaction after the crisis period which may be attributable to the behaviors of traders.short term overreaction effect, Istanbul Stock Exchange

Do Farmers Hedge Optimally or by Habit? A Bayesian Partial-Adjustment Model of Farmer Hedging

Hedging is one of the most important risk management decisions that farmers make and has a potentially large role in the level of profit eventually earned from farming. Using panel data from a survey of Georgia farmers that recorded their hedging decisions for 4 years on four crops, we examine the role of habit, demographics, farm characteristics, and information sources on the hedging decisions made by 57 different farmers. We find that the role of habit varies widely and that estimation of a single habit effect suffers from aggregation bias. Thus, modeling farmer-level heterogeneity in the examination of habit and hedging is crucial.Bayesian econometrics, habit formation, hedging decisions, information sources, Agribusiness, Agricultural Finance, Farm Management, Financial Economics, Labor and Human Capital, Production Economics, Productivity Analysis, Research Methods/ Statistical Methods, C11, Q12, Q14,

Components of Grain Futures Price Volatility

We analyze the determinants of daily futures price volatility in corn, soybeans, wheat, and oats markets from 1986 to 2007. Combining the information from simultaneously traded contracts, a generalized least squares method is implemented that allows us to clearly distinguish among time-to-delivery effects, seasonality, calendar trend, and volatility persistence. We find strong evidence of time-to-delivery (Samuelson) effects and systematic seasonal components with volatility increasing prior to harvest times— an indirect confirmation of the theory of storage.futures markets, Samuelson effect, seasonality, time to maturity, volatility, Crop Production/Industries, Risk and Uncertainty,

Statistical Learning in Automated Troubleshooting: Application to LTE Interference Mitigation

This paper presents a method for automated healing as part of off-line automated troubleshooting. The method combines statistical learning with constraint optimization. The automated healing aims at locally optimizing radio resource management (RRM) or system parameters of cells with poor performance in an iterative manner. The statistical learning processes the data using Logistic Regression (LR) to extract closed form (functional) relations between Key Performance Indicators (KPIs) and Radio Resource Management (RRM) parameters. These functional relations are then processed by an optimization engine which proposes new parameter values. The advantage of the proposed formulation is the small number of iterations required by the automated healing method to converge, making it suitable for off-line implementation. The proposed method is applied to heal an Inter-Cell Interference Coordination (ICIC) process in a 3G Long Term Evolution (LTE) network which is based on soft-frequency reuse scheme. Numerical simulations illustrate the benefits of the proposed approach.Comment: IEEE Transactions On Vehicular Technology 2010 IEEE transactions on vehicular technolog

Do Farmers Hedge Optimally or by Habit? A Bayesian Partial-Adjustment Model of Farmer Hedging

Hedging is one of the most important risk management decisions that farmers make and has a potentially large role in the level of profit eventually earned from farming. Using panel data from a survey of Georgia farmers that recorded their hedging decisions for four years on three crops we examine the role of habit, demographics, farm characteristics, and information sources on the hedging decisions made by 106 different farmers. We find that the role of habit varies widely. Information sources are shown to have significant and large effects on the chosen hedge ratios. The farmer's education level, attitude toward technology adoption, farm profitability, and the ratio of acres owned to acres farmed also play important roles in hedging decisions.Bayesian econometrics, hedging decisions, habit formation, information sources, Agricultural Finance,