This thesis proposes an Artificial Neural Network (ANN) enhanced decision support system for financial risk management. The decision support system allows hedgers to maximise their expected return while practising the hedge against financial risks. The importance of the research stems from the fact that it can be used to reduce the risk associated with adverse price movements in the stock marke...

this research analyze the resource and structure of cross-autocorrelation in returns and volatility of stocks that listed in the tehran stock exchange during the period farvardin 1382–eisfand 1386, with employing the garch model. at the first, the results show that, in down(bear) market, return on high trading volume portfolio lead return on low trading volume portfolio, when controlled for fir...

This paper uses the concept of possibilistic risk aversion to propose a new approach for portfolio selection in fuzzy environment. Using possibility theory, the possibilistic mean, variance, standard deviation and risk premium of a fuzzy number are established. Possibilistic Sharpe ratio is defined as the ratio of possibilistic risk premium and possibilistic standard deviation of a portfolio. T...

We test the hypothesis that investment constraints in delegated portfolio management may distort demand for stocks, leading to price underreaction to news and stock return predictability. We find that institutions tend not to buy more of a stock with good news that they already overweight; they are reluctant to sell a stock with bad news that they already underweight. Stocks with good news over...

The purpose of resent research is to analysis and compares performance evaluation models of selected investment companies in Tehran Stock Exchange Market in the field of their portfolio management. The duration of research was between years 2009-2014. Statistical society the research is consisting of all active investment companies in in Tehran Stock Exchange Market which were 30 companies. Vol...

In mathematical finance, backtest overfitting connotes the usage of historical market data to develop an investment strategy, where too many variations of the strategy are tried, relative to the amount of data available. Backtest overfitting is now thought to be a primary reason why investment models and strategies that look good on paper often disappoint in practice. Models and strategies suff...

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...