The problem of optimal portfolio selection has attracted a great attention in the finance and optimization field. The future stock price should be predicted in an acceptable precision, and a suitable model and criterion for risk and the expected return of the stock portfolio should be proposed in order to solve the optimization problem. In this paper, two new criterions for the risk of stock pr...

the aim of this paper is analyzing the role of psychology of numbers in financial markets and in this area, investigates the price clustering phenomenon in trading prices of tehran stock exchange. price clustering is one of anomalies that have been observed in financial markets that representative psychological biases or tendency to specific numbers in the market. this phenomenon includes of de...

While explicitly assuming that stock price conveys valuable information to the management, we show that the value loss from diversification is a function of the stock price informativeness. More informed stock trading leads to a more efficient investment and a smaller diversification discount. © 2007 Elsevier B.V. All rights reserved.

Monthly price and stock data are used to test the influence of Philippine government buffer-stock programs on seasonal and annual variability of producer and consumer rice prices. The period examined is 1974-1990. NFA stock changes are shown to have had some stabilizing influence on seasonal and annual price changes, but the magnitude is small and not statistically significant.

In this study, a model of Bayesian Dynamic Stochastic General Equilibrium (DSGE) from Real Business Cycles (RBC) approach with the aim of identifying the factors shaping price bubbles of Tehran Stock Exchange (TSE) was specified. The above-mentioned model was conducted in two scenarios. In the first scenario, the baseline model with sentiment shock was examined. In this model, stock price bubbl...

The stock market is a complex system that affects economic and financial activities around the world. Analysis of stock price data can improve our understanding of the past price movements of stocks. In this work, we develop a method to determine the highly interconnected subsystems of the stock market. Our method relies on a k-core decomposition scheme to analyze large networks. Our approach i...

Stock market plays a vital role in a country’s economy and it is an important consideration in all the fields due to its potential financial gain. Using Data mining future stock price, whether stock price go high or low can be predicted. There are two types of stock market predictions, fundamental analysis based on unstructured data and technical analysis based on structured data. In this paper...

This article uses an e ent study to e aluate the anticipated results of the Uruguay Round on U.S. industry. Economists commonly use computable general equilibrium ( ) CGE models to predict the net economic efficiency effects of trade agreements. The e ent study method represents a complementary approach that relies on stock price mo ements to assess how in estors predict that an e ent, in this ...

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...

This paper employs a general non-linear analysis tool to analyse the nature of time series associated with the price (returns) of a particular company in Tehran Stock Exchange. It is shown that the behavior of the process associated with the price (returns) time-series of this company is weakly chaotic, and due to the non-random behavior of the process, short term prediction of stock price is p...