Article history: Received 31 July 2008 Received in revised form 27 July 2009 Accepted 29 April 2010 Available online 16 May 2010 Complex networks are constructed to study correlations between the closing prices for all US stocks that were traded over two periods of time (from July 2005 to August 2007; and from June 2007 toMay 2009). The nodes are the stocks, and the connections are determined b...

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 ...

This article investigates the impact of terrorist attacks on global capital markets. We find economic consequences of terrorist attacks spillover through trading partners. When a bigger economy (measured by GDP) is targeted, the spillover is specifically prominent for economically smaller trading partners. Such partners see a -2.5% reduction in national stock indices. Odds for smaller trading p...

Stock markets strive to provide an efficient trading platform for investors. Trading rules and mechanisms issued to accomplish this differ among stock markets, and are subject to modification over time. Furthermore, market participants assume a broad range of roles and trading strategies. Such variation poses problems to those involved in the study of market dynamics, when developing an artific...

This paper analyzes the stability of the exchange rate in an economy with noise traders. Noise trading is restricted to agents investing in the domestic stock market. The agents pricing foreign exchange hold rational expectations. Monetary policy is affected by the behavior of investors in the domestic stock market and in turn affects fundamental stock evaluations as well as noise trading. We s...

A number of published techniques have emerged in the trading community for stock prediction tasks. Among them is neural network (NN). In this paper, the theoretical background of NNs and the backpropagation algorithm is reviewed. Subsequently, an attempt to build a stock buying/selling alert system using a backpropagation NN, NN5, is presented. The system is tested with data from one Hong Kong ...

We examined the effects of trading volume on the persistence of the time-varying conditional volatility of returns and the dynamic relations between trading volume and returns (and volatility) for both domestic and cross-country markets. We considered daily prices and trading volume in four Asian stock exchanges (Korea, Japan, China, and Hong Kong). For the analysis, we used the GARCH model, wh...

Stock trading is an important financial activity of human society. Machine learning techniques are adopted to provide trading decision support by predicting the stock price or trading signals of the next day. Decisions are made by analyzing technical indices and fundamental analysis of companies. There are two major machine learning research problems for stock trading decision support: classifi...

This paper develops a model of trading in stock and stock index security markets in the presence of transaction costs. We show that the introduction of stock index market improves the dissemination of market-wide information and index trading is more informative about stock market price movements than stock trading. The model generates rich implications on the informativeness of the stock index...