-It has been a stock trader’s dream to do stock trading by switching from one stock to another while buying at bottoms and selling at tops. This paper investigates the effectiveness and the practicability of such a trading model. For a learning system, nothing is more influential than the data to learn. Any data, whether it is in-sample or out-of-sample, is intrinsically particular. It is typic...

This paper investigates the use of influence from foreign stock markets (intermarket influence) to predict the trading signals, buy, hold and sell, of the of a given stock market. Australian All Ordinary Index was selected as the stock market whose trading signals to be predicted. Influence is taken into account as a set of input variables for prediction. Two types of input variables were consi...

This paper aims to apply the neuro-fuzzy technique to refine the Stochastics technical trading rules to forecast the Asian stock market. Essentially in this hybrid technique, fuzzy logic plays the role to formulate the relationship among the Stochastics indicators and stock price changes by using knowledge base. Neural networking is used to tune the formulated knowledge base based on historical...

A KADS based requirement analysis for the management of stock trading portfolios is presented. This provides a theoretical foundation for a stock trading system. This system is designed around portfolio management tasks that include eliciting user profiles, collecting information on the user’s portfolio position, monitoring the environment on behalf of the user, and making decision suggestions ...

Real market institutions, stock and commodity exchanges for example, do not occur in isolation. Company stock is frequently listed on several stock exchanges, and futures exchanges make it possible for dealers in a particular commodity to offset their risks by trading options in that commodity. While there has been extensive research into agent-based trading in individual markets, there is litt...

In investigating the effects of algorithmic trading on stock market liquidity and commonality in liquidity in different market conditions in an electronic limit order market, we find algorithmic trading increases stock liquidity by narrowing quoted and effective bid–ask spreads. Furthermore, algorithmic trading decreases commonality in liquidity; this finding is robust across a variety of liqui...

This article presents a discussion of stock market liquidity and its relation to financial crises. It begins by defining liquidity and explaining possible measures of liquidity and then explores factors influencing liquidity. It also analyzes the liquidity among 11 Asian countries. The empirical findings based on the time-series analysis show a sharp decline in stock liquidity during both the 1...

This article presents a discussion of stock market liquidity and its relation to financial crises. It begins by defining liquidity and explaining possible measures of liquidity and then explores factors influencing liquidity. It also analyzes the liquidity among 11 Asian countries. The empirical findings based on the time-series analysis show a sharp decline in stock liquidity during both the 1...

The dissertation presents Hybrid Intelligent Decision Support Systems (DSS) for the selection of alternatives (companies, stocks, and company groups) in stock trading under uncertainty. This study proposes a framework including three models using Hybrid Intelligent DSS. The framework aims to optimize trading decisions in the selection of appropriate alternatives and reduce risky decisions. This...

Two concepts of virtual reality are competing in the cyber world, virtual reality as total adaptability and virtual reality as the simulation of possible worlds. Virtuality as adaptability in industrial production leads to a closer consideration of individual consumer demand and to de-massified production. It implies a stronger reference of production to the reality of consumer needs. The aesth...