Impact of the Level of Disclosure of Financial Information on the Pricing of Shares in the Context of Adverse Selection: an experimental research

Managers know more about the performance of the organization than investors, which makes the disclosure of information a possible strategy for competitive differentiation, minimizing adverse selection. This paper's main goal is to analyze whether or not an entity's level of diclosure may affect the risk perception of individuals and the process of evaluating their shares. The survey was carried out in an experimental study with 456 subjects. In a stock market simulation, we investigated the pricing of the stocks of two companies with different levels of information disclosure at four separate stages. The results showed that, when other variables are constant, the level of disclosure of an entity can affect the expectations of individuals and the process of evaluating their shares. A higher level of disclosure by an entity affected the value of its share and the other company's.

International energy outlook /

Latest issue consulted: 1993.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume II: simulation analysis using the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

A simulation analysis of the market effect of the Australian Broadcasting Corporation

In this paper we utilise a stochastic address model of broadcast oligopoly markets to analyse the Australian broadcast television market. In particular, we examine the effect of the presence of a single government market participant in this market. An examination of the dynamics of the simulations demonstrates that the presence of a government market participant can simultaneously generate positive outcomes for viewers as well as for other market suppliers. Further examination of simulation dynamics indicates that privatisation of the government market participant results in reduced viewer choice and diversity. We also demonstrate that additional private market participants would not result in significant benefits to viewers.

Energy derivative market and derivative pricing via simulation

The deregulation of power industry worldwide has delivered the efficiency gains to the society; meanwhile, the intensity of competition has increased uncertainty and risks to market participants. Consequently, market participants are keen to hedge the market risks and maintain a competitive edge in the market; and this is a good explanation to the flourish of electricity derivative market. In this paper, the authors gave a comprehensive review of derivative contract pricing methods and proposed a new framework for energy derivative pricing to suit the needs of a deregulated electricity market

Optimal track access rights allocation for agent negotiation in an open railway market

In open railway access markets, a train service provider (TSP) negotiates with an infrastructure provider (IP) for track access rights. This negotiation has been modeled by a multi-agent system (MAS) in which the IP and TSP are represented by separate software agents. One task of the IP agent is to generate feasible (and preferably optimal) track access rights, subject to the constraints submitted by the TSP agent. This paper formulates an IP-TSP transaction and proposes a branch-and-bound algorithm for the IP agent to identify the optimal track access rights. Empirical simulation results show that the model is able to emulate rational agent behaviors. The simulation results also show good consistency between timetables attained from the proposed methods and those derived by the scheduling principles adopted in practice.

Service bid comparisons by fuzzy ranking in open railway market timetabling

In an open railway access market, the Infrastructure Provider (IP), upon the receipts of service bids from the Train Service Providers (TSPs), assigns track access rights according to its own business objectives and the merits of the bids; and produces the train service timetable through negotiations. In practice, IP chooses to negotiate with the TSPs one by one in such a sequence that IP optimizes its objectives. The TSP bids are usually very complicated, containing a large number of parameters in different natures. It is a difficult task even for an expert to give a priority sequence for negotiations from the contents of the bids. This study proposes the application of fuzzy ranking method to compare and prioritize the TSP bids in order to produce a negotiation sequence. The results of this study allow investigations on the behaviors of the stakeholders in bid preparation and negotiation, as well as evaluation of service quality in the open railway market.

Intelligent negotiation behaviour model for an open railway access market

In an open railway access market, the provisions of railway infrastructures and train services are separated and independent. Negotiations between the track owner and train service providers are thus required for the allocation of the track capacity and the formulation of the services timetables, in which each party, i.e. a stakeholder, exhibits intelligence from the previous negotiation experience to obtain the favourable terms and conditions for the track access. In order to analyse the realistic interacting behaviour among the stakeholders in the open railway access market schedule negotiations, intelligent learning capability should be included in the behaviour modelling. This paper presents a reinforcement learning approach on modelling the intelligent negotiation behaviour. The effectiveness of incorporating learning capability in the stakeholder negotiation behaviour is then demonstrated through simulation.

Conflict resolution through negotiation in a railway open access market : a multi-agent system approach

Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.

Scheduling coordination through negotiation between train service providers in an open railway access market

A schedule coordination problem involving two train services provided by different operators is modeled as an optimization of revenue intake. The coordination is achieved through the adjustment of commencement times of the train services by negotiation. The problem is subject to constraints regarding to passenger demands and idle costs of rolling-stocks from both operators. This paper models the operators as software agents having the flexibility to incorporate one of the two (and potentially more) proposed negotiation strategies. Empirical results show that agents employing different combination of strategies have significant impact on the quality of solution and negotiation time.

A simulation study of unified GPS and roadside ranging technologies for vehicle positioning

The future vehicle navigation for safety applications requires seamless positioning at the accuracy of sub-meter or better. However, standalone Global Positioning System (GPS) or Differential GPS (DGPS) suffer from solution outages while being used in restricted areas such as high-rise urban areas and tunnels due to the blockages of satellite signals. Smoothed DGPS can provide sub-meter positioning accuracy, but not the seamless requirement. A disadvantage of the traditional navigation aids such as Dead Reckoning and Inertial Measurement Unit onboard vehicles are either not accurate enough due to error accumulation or too expensive to be acceptable by the mass market vehicle users. One of the alternative technologies is to use the wireless infrastructure installed in roadside to locate vehicles in regions where the Global Navigation Satellite Systems (GNSS) signals are not available (for example: inside tunnels, urban canyons and large indoor car parks). The examples of roadside infrastructure which can be potentially used for positioning purposes could include Wireless Local Area Network (WLAN)/Wireless Personal Area Network (WPAN) based positioning systems, Ultra-wide band (UWB) based positioning systems, Dedicated Short Range Communication (DSRC) devices, Locata’s positioning technology, and accurate road surface height information over selected road segments such as tunnels. This research reviews and compares the possible wireless technologies that could possibly be installed along roadside for positioning purposes. Models and algorithms of integrating different positioning technologies are also presented. Various simulation schemes are designed to examine the performance benefits of united GNSS and roadside infrastructure for vehicle positioning. The results from these experimental studies have shown a number of useful findings. It is clear that in the open road environment where sufficient satellite signals can be obtained, the roadside wireless measurements contribute very little to the improvement of positioning accuracy at the sub-meter level, especially in the dual constellation cases. In the restricted outdoor environments where only a few GPS satellites, such as those with 45 elevations, can be received, the roadside distance measurements can help improve both positioning accuracy and availability to the sub-meter level. When the vehicle is travelling in tunnels with known heights of tunnel surfaces and roadside distance measurements, the sub-meter horizontal positioning accuracy is also achievable. Overall, simulation results have demonstrated that roadside infrastructure indeed has the potential to provide sub-meter vehicle position solutions for certain road safety applications if the properly deployed roadside measurements are obtainable.

Simulation of plant cell shrinkage during drying : A SPH–DEM approach

Plant based dried food products are popular commodities in global market where much research is focused to improve the products and processing techniques. In this regard, numerical modelling is highly applicable and in this work, a coupled meshfree particle-based two-dimensional (2-D) model was developed to simulate micro-scale deformations of plant cells during drying. Smoothed Particle Hydrodynamics (SPH) was used to model the viscous cell protoplasm (cell fluid) by approximating it to an incompressible Newtonian fluid. The visco-elastic characteristic of the cell wall was approximated to a Neo-Hookean solid material augmented with a viscous term and modelled with a Discrete Element Method (DEM). Compared to a previous work [H. C. P. Karunasena, W. Senadeera, Y. T. Gu and R. J. Brown, Appl. Math. Model., 2014], this study proposes three model improvements: linearly decreasing positive cell turgor pressure during drying, cell wall contraction forces and cell wall drying. The improvements made the model more comparable with experimental findings on dried cell morphology and geometric properties such as cell area, diameter, perimeter, roundness, elongation and compactness. This single cell model could be used as a building block for advanced tissue models which are highly applicable for product and process optimizations in Food Engineering.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Influencing factors of successful transitions towards product-service systems: A simulation approach

Product-Service Systems (PSS) are new business strategies moving and extending the product value towards its functional usage and related required services. From a theoretical point of view the PSS concept is known since a decade and many Authors reported reasonable possible success factors: higher profits over the entire life-cycle, diminished environmental burden, and localization of required services. Nevertheless the PSS promises remain quantitatively unproven relaying on a simple theory that involves a few constructs with some empirical grounding, but that is limited by weak conceptualization, few propositions, and/or rough underlying theoretical logic. A plausible interpretation to analyze the possible evolution of a PSS strategy could be considering it as a new business proposition competing on a traditional Product-Oriented (PO) market, assumed at its own equilibrium state at a given time. The analysis of the dynamics associated to a possible transition from a traditional PO to a PSS strategy allows investigating the main parameters and variables influencing an eventual successful adoption. This research is worthwhile because organizations undergoing fundamental PSS strategy are concerned about change and inertia key processes which, despite equilibrium theory and because of negative feedback loops, could undermine, economically, the return of their PSS proposition. In this paper Authors propose a qualitative System Dynamics (SD) approach by considering the PSS as a perturbation of an existing PO market featured by a set of known parameters. The proposed model incorporates several PSS factors able to influence the success of a PSS proposition under a set of given and justified assumptions, attempting to place this business strategy in a dynamic framework.