This thesis consists of four self-contained papers related to the change of market structure and the quality of equity market. In Paper [I] we found, by using of a Flexible Dynamic Component Correlations (FDCC) model, that the creation of a common cross-border stock trading platform has increased the long-run trends in conditional correlations between foreign and domestic stock market returns. ...

Stock market volatility is the systematic risk faced by investors who hold a market portfolio (e.g., a stock market index fund). Schwert (1989b) has undertaken an extensive study of stock market volatility, using historical data back to the 19th century. Some of his major findings are illustrated in Figure 1, which plots quarterly stock market volatility for the post-World War II period.1 The f...

the process of economic globalization and integration has had a tremendous growth in recent years and the convergence of various economic sectors, including the financial markets is increasingly in the spotlight. this increasing trend has strengthened investors' interests in the subject of convergence among the world's stock markets and investors experimentally show a passion for unde...

─Abstract─ This paper proposes an information retrieval method for the economy news. The effect of economy news, are researched in the word level and stock market values are considered as the ground proof. The correlation between stock market prices and economy news is an already addressed problem for most of the countries. The most well-known approach is applying the text mining approaches to ...

This paper surveys recent literature in the area of Neural Network, Data Mining, Hidden Markov Model and Neuro-Fuzzy system used to predict the stock market fluctuation. Neural Networks and Neuro-Fuzzy systems are identified to be the leading machine learning techniques in stock market index prediction area. The Traditional techniques are not cover all the possible relation of the stock price f...

Machine learning is increasingly prevalent in stock market trading. Though neural networks have seen success in computer vision and natural language processing, they have not been as useful in stock market trading. To demonstrate the applicability of a neural network in stock trading, we made a single-layer neural network that recommends buying or selling shares of a stock by comparing the high...

Oil price fluctuations affect equity values in North American, European, and Gulf Cooperation Council (GCC) stock markets, as evidenced by prior studies. However, they only focus on market-wide level analysis. This study, through both market level and sector level analyses, examines the sensitivity of Malaysian stock returns to oil price fluctuations over the period from January 2000 to March 2...