Forecasting financial markets is an important issue in finance area and research studies. On one hand, the importance of prediction, and on the other hand, its complexity, have led to huge number of researches which have proposed many forecasting methods in this area. In this study, we propose a hybrid model including Wavelet Transform, ARMA-GARCH and Artificial Neural Network (ANN) for single-...

We present a behavioral stock market model in which traders are driven by greed and fear. In general, the agents optimistically believe in rising markets and thus buy stocks. But if stock prices change too abruptly, they panic and sell stocks. Our model mimics some stylized facts of stock market dynamics: (1) stock prices increase over time, (2) stock markets sometimes crash, (3) stock prices s...

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...

We present a multiperiod agency model of stock-based executive compensation in a speculative stock market, where investors have heterogeneous beliefs and stock prices may deviate from underlying fundamentals and include a speculative option component. This component arises from the option to sell the stock in the future to potentially overoptimistic investors. We show that optimal compensation ...

The long-run risks model of asset prices explains stock price variation as a response to persistent ‡uctuations in the mean and volatility of consumption growth, by a representative agent with a high elasticity of intertemporal substitution. This paper documents that the model fails to …t aggregate asset prices in several important ways. The model implies that long-run consumption growth should...

This paper presents a type of stock models for uncertain markets by using uncertainty theory. Firstly, a brief history of stock models and some methodologies are reviewed. Next, some useful concepts and properties about uncertain process are recalled. Then, a stock model for uncertain markets is formulated by the tool of uncertain differential equation. Some option pricing formulas on the prop...

One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock exchange market. This research proposes a smart algorithm by means of valuable big data that is generated by stock exchange market and different kinds of methodology to present a smart model.In this paper, we investigate relationships between the data and access to their lat...

this world; though all the discussions are focused on the causal relationships in allthe scientific arguments. One of the methods to study the designed causal relationshipsobjectively is Granger causality test. This paper aims to investigate the longtermcausal relationship between the stock price and dividends. The statisticalpopulation includes 180 active companies in Stock Exchange of Tehran ...

the purpose of this research is investigation of application of the arbitrage pricing theory and effect of unanticipated changes in a set of macroeconomic variables such as inflation rate, money supply, exchange rate, oil price, term structure and industrial production on expected security return in tehran stock exchange. in this research, data are analyzed quarterly for the period of 1997-2008...