Technological innovations currently alter the traditional value chain in securities trading. Investment companies that used to buy trading services from their brokers are now enabled by technology to emulate core competencies of their brokers themselves. To investigate the adoption decision regarding one of those new technologies – Algorithmic Trading – a survey among the top European buy-side ...

Economists have been promoting water quality (WQ) trading for decades. Over the past few years, many political leaders and upper-level government officials have been joining them. Money has even started to flow from Wash-ington to local trading organizations to help make WQ trading work. However, enthusiasm about WQ trading is based mostly on conceptual arguments about its potential to generate...

This study aims to propose three evaluation methods to evaluate the Tokyo Cap and Trade Program when emissions trading is performed virtually among enterprises, focusing on carbon dioxide (CO2), which is the only emitted greenhouse gas that tends to increase. The first method clarifies the optimum reduction rate for the highest cost benefit, the second discusses emissions trading among enterpri...

In this paper, we are examining the relationship between stock trading costs and commitment components and find both abnormal and normal commitments associated with these costs are associated. Moreover, stock trading costs have a greater influence by both abnormal and normal negative commitments more than positive commitments. Further analysis has shown that in general, investors are unable to ...

Noise traders as one of the key elements of the market play a significant role in determining the market volatilities, returns, and stock market mispricing. Hence, this study attempts to scrutinize the role of noise trading in capital asset pricing. Therefore, by using daily data, samples including 14105 data of 200 companies listed on stock exchange were selected and noise trading index was es...

Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading ...

This study investigates the daily dynamic relation between returns and institutional and individual trades in the TAIEX futures market. I find that both past individual and institutional buys and sells have no predictive power for index returns; both individual and institutional trading activities are strongly related to their own past trades, and individual open-buy trading is also influenced ...

As the Internet helps mediate millions of transactions in electronic markets, research work on automated trading agents is helping humans improve their trading objectives (e.g., finding lower prices and improving delivery options). This chapter presents an overview of the research work on trading agents in the context of the Trading Agent Competition. The Trading Agent Competition is an annual ...

Actionable trading strategies for trading agents determine the potential of the simulated models in real-life markets. The development of actionable strategies is a non-trivial task, which needs to consider real-life constraints and organizational factors in the market. In this paper, we first analyze such constraints on developing actionable trading strategies. Further we propose an actionable...