Modelling the behaviour of the new issue market

This paper analyses the time series behaviour of the initial public offering (IPO) market using an equilibrium model of demand and supply that incorporates the number of new issues, average underpricing, and general market conditions. Model predictions include the existence of serial correlation in both the number of new issues and the average level of underpricing, as well as interactions between these variables and the impact of general market conditions. The model is tested using 40 years of monthly IPO data. The empirical results are generally consistent with predictions.

Genetic algorithm-based spinning reserve dispatching in a competitive electricity market

Power systems rely greatly on ancillary services in maintaining operation security. As one of the most important ancillary services, spinning reserve must be provided effectively in the deregulated market environment. This paper focuses on the design of an integrated market for both electricity and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the ISO's total payment while ensuring system security. Genetic algorithms are used in the finding of the global optimal solutions for this dispatching problem. Case studies and corresponding analyses haw been carried out to demonstrate and discuss the efficiency and usefulness of the proposed market.

Market reaction to takeover rumour in internet discussion sites

We examine the market reaction to takeover rumour postings in the Hotcopper Internet Discussion Site (IDS). Results from the interday analysis show abnormal returns and trading volumes on the day before and the day of the posting. Results of the intraday analysis show abnormal returns and trading volumes during the 10 min posting interval and abnormal trading volume during the 10 min interval immediately preceding it. Sensitivity analyses indicate that the results are robust to concerns regarding potential confounds, credibility and bid–ask spread bias. Taken together, these findings are consistent with the market reacting to the posting of takeover rumours in IDS.

A genetic algorithm based method for deregulated electricity market dispatch

In a deregulated electricity market, optimizing dispatch capacity and transmission capacity are among the core concerns of market operators. Many market operators have capitalized on linear programming (LP) based methods to perform market dispatch operation in order to explore the computational efficiency of LP. In this paper, the search capability of genetic algorithms (GAs) is utilized to solve the market dispatch problem. The GA model is able to solve pool based capacity dispatch, while optimizing the interconnector transmission capacity. Case studies and corresponding analyses are performed to demonstrate the efficiency of the GA model.

Optimal dispatch of spinning reserve in a competitive electricity market using genetic algorithms

Ancillary service plays a key role in maintaining operation security of the power system in a competitive electricity market. The spinning reserve is one of the most important ancillary services that should be provided effectively. This paper presents the design of an integrated market for energy and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the cost of service while maintaining system security. Genetic algorithms (GA) are used for finding the global optimal solutions for this dispatch problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed method.