During the past two years, Chinese joint-stock companies have been converting nontradable stock held by the state and state-controlled institutions, which constitute twothirds of all stock in Chinese firms, into stock that can trade on local exchanges. This ownership reform reduces direct state control over industrial enterprises. It also greatly increases the supply of stock, which threatens t...

a r t i c l e i n f o Keywords: Subtractive clustering Adaptive network-based fuzzy inference system Technical indicators Adaptive learning Genetic algorithm Technical analysis is one of the useful forecasting methods to predict the future stock prices. For professional stock analysts and fund managers, how to select necessary technical indicators to forecast stock trends is important. Traditio...

The option-pricing problem is always an important part in modern finance. Assuming that the stock diffusion is a constant, some literature has introduced many stock models and given corresponding option pricing formulas within the framework of the uncertainty theory. In this paper, we propose a new stock model with uncertain stock diffusion for uncertain markets. Some option pricing formulas on...

Mamer & McBride recently introduced a new decomposition algorithm for linear programming. They call this decomposition algorithm decomposition-based pricing. Our paper applies decomposition-based pricing to integer programs. For integer programs, we show that decomposition-based pricing produces tighter bounds than other common decomposition algorithms. We use the classic one-dimension cutting ...

Stock market represents an essential part of the economy in the Middle East, it is significant for shareholders and investors to estimate the stock price and select the best trading opportunity accurately in advance. This paper utilizes artificial neural network in the modeling of stock market exchange prices. The network was trained using supervised learning. Simulation was conducted for seven...

Structural shifts characterize the volatility of the Korean stock and foreign exchange markets during the 1997 Asian financial crisis. This paper employs an unrestricted bivariate GARCH-M model of stock market returns to investigate empirically the effects of daily currency depreciation on Korean stock market returns. The evidence shows that currency depreciation significantly affects stock mar...

Authors present the stock price prediction algorithm by using Bayesian network. The present algorithm uses the network twice. First, the network is determined from the daily stock price and then, it is applied for predicting the daily stock price which was already observed. The prediction error is evaluated from the daily stock price and its prediction. Second, the network is determined again f...

This paper investigates the relationship between aggregate stock market trading volume and the serial correlation of daily stock returns. For both stock indexes and individual large stocks, the first-order daily return autocorrelation tends to decline with volume. The paper explains this phenomenon using a model in which risk-averse "market makers" accommodate buying or selling pressure from "l...

The paper examines risk spillover among major European, American and Japanese stock exchanges using daily stock prices from 1998 to 2011 period. More specifically, we focus more on risk spillover among major north-western stock markets (i.e. France, Germany, and United Kingdom) and southern European stock markets (Greece, Italy, Portugal, and Spain). The main motivation of the study is to use t...

One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock market data to give individuals or institutions useful information about the market behavior for investment decisions. The enormous amount of valuable data generated by the stock market has attracted researchers to explore this problem domain using different methodologies. This pa...