Stock exchange

About: Stock exchange is a research topic. Over the lifetime, 39566 publications have been published within this topic receiving 612044 citations.

Is Foreign Exchange Risk Priced in the Japanese Stock Market

Abstract: The exchange rate is an important variable that affects international competitiveness and performance of Japanese firms. We use an unconditional and a conditional multi-factor asset pricing model to examine whether exchange risk is recognized and priced in the Japanese stock market. The results indicate that the exchange risk is generally priced in Japan. More specifically, we provide evidence, in the unconditional model, that the exchange risk is priced in both weak and strong yen periods, when the bilateral yen/U.S. dollar exchange rate measure is used. The results are more mixed when the trade-weighted exchange rate is used. For the conditional model, the exchange risk is priced regardless of the exchange rate measure used. The combined evidence from the two models suggests an interesting observation about the role of the secular exchange rate trend in shaping the perception of exchange risk in the Japanese capital markets.

Hybridization of evolutionary Levenberg-Marquardt neural networks and data pre-processing for stock market prediction

Abstract: Artificial Intelligence models (AI) which computerize human reasoning has found a challenging test bed for various paradigms in many areas including financial time series prediction. Extensive researches have resulted in numerous financial applications using AI models. Since stock investment is a major investment activity, Lack of accurate information and comprehensive knowledge would result in some certain loss of investment. Hence, stock market prediction has always been a subject of interest for most investors and professional analysts. Stock market prediction is a challenging problem because uncertainties are always involved in the market movements. This paper proposes a hybrid intelligent model for stock exchange index prediction. The proposed model is a combination of data preprocessing methods, genetic algorithms and Levenberg-Marquardt (LM) algorithm for learning feed forward neural networks. Actually it evolves neural network initial weights for tuning with LM algorithm by using genetic algorithm. We also use data pre-processing methods such as data transformation and input variables selection for improving the accuracy of the model. The capability of the proposed method is tested by applying it for predicting some stock exchange indices used in the literature. The results show that the proposed approach is able to cope with the fluctuations of stock market values and also yields good prediction accuracy. So it can be used to model complex relationships between inputs and outputs or to find data patterns while performing financial prediction.

Effects of corporate governance on capital structure: empirical evidence from Pakistan

Abstract: Purpose – The aim of this empirical study is to investigate whether corporate governance attributes such as board size, outside directors, ownership concentration, managerial ownership, director remuneration, and CEO duality affect capital structure choices of Pakistani firms.Design/methodology/approach – Multiple regression analysis is used to estimate the relationship between corporate governance measures and capital structure of non‐financial firms listed on the Karachi Stock Exchange, Pakistan, during 2004‐2008.Findings – The results suggest that board size, outside directors, and ownership concentration are positively related to the total debt ratio and the long‐term debt ratio, whereas director remuneration is negatively related. Managerial ownership is negatively related to the long‐term debt ratio. CEO duality is found to be highly insignificant in all regressions. Control variables such as profitability and liquidity are negatively related to the total debt ratio and the long‐term debt ratio, whe...

Impact of capital structure on firm’s value: Evidence from Bangladesh

Abstract: Modigliani & Miller (1958) show the impact of debt-equity ratio on firm value in their capital structure theory. Economist and financial researchers have spent time to develop new thoughts around this theory. Despite their effort the Modigliani & Miller (MM) model is still in vague. In this paper attempt has been made to empirically support the argument of MM. The paper tests the influence of debt-equity structure on the value of shares given different sizes, industries and growth opportunities with the companies incorporated in Dhaka Stock Exchange (DSE) and Chittagong Stock Exchange (CSE) of Bangladesh. For the robustness of the analysis samples are drawn from the four most dominant sectors of industry i.e. engineering, food & allied, fuel & power, and chemical & pharmaceutical to provide a comparative analysis. A strong positively correlated association is evident from the empirical findings when stratified by industry.

Corporations and the Corporate Elite

Abstract: the role of business. In this review, attention is generally restricted to the largest corporations and their corporate elite. At present there are more than two million business enterprises in the US, and nearly all are very small; in 1973, for instance, nine out often companies commanded assets of $1 million or less. Despite their large numbers, however, even in the aggregate these small companies are dwarfed in economic significance by the several thousand largest corporations. This dominance can be ex­ pressed in many ways; one index is the proportion of resources com­ manded by the approximately two thousand firms whose stock is traded on the New York Stock Exchange. These large companies accounte d in 1971 for 40% of all corporate assets, 60% of all corporate revenue, and 88% of all corporate income. 1973, the 1,000 largest industrial firms