We analyze the joint inventory and pricing decisions of a firm when demand depends on not only the current selling price but also a memory-based reference price and customers are loss averse. The presence of reference price effect leads to a non-concave one-period expected revenue in price and reference price. We introduce a transformation technique that allows us to prove under some mild assum...

The aim of this research is to analyze the connection between dividend announcement and stock price on Croatian capital market using event study methodology. Research period was the period from the year 2007 to the year 2009. Results have confirmed that dividend change has statistically significant value for investors. Dividend increase and dividend decrease resulted with statistically signific...

Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock ...

A simple model that is commonly used to interpret movements in corporate common stock. price indexes asserts that real stock prices equal the present value of rationally expected or optimally forecasted future real dividends discounted by a constant real discount rate. This valuation model (or variations on it in which the real discount rate is not constant but fairly stable) is often used by e...

The application of AI techniques for stock price prediction leads to voluminous growth of wealth of investors with the advent of technology. Several prediction and estimations are coming up for almost all sectors of the market. Particularly any kind of stock price prediction is not at all possible without excessive data manipulation which can be done effectively only thru data mining. The syste...

An optimal selling strategy for stock trading is presented in this paper. An investor with a long position in one stock decides to close the position before a given time. The investor continuously observes the stock price performance and has to determine the point in time to close out the position (selling strategy) so that the stock price is as close as possible to the maximum price. The proba...

Recently, numerous investigations for stock price prediction and portfolio management using machine learning have been trying to develop efficient mechanical trading systems. But these systems have a limitation in that they are mainly based on the supervised leaming which is not so adequate for leaming problems with long-term goals and delayed rewards. This paper proposes a method of applying r...

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock pr...

We investigated the inter-day effects of price limits policies that are employed in agent-based simulations. To isolate the impact of price limits from the impact of other factors, we built an artificial stock market with higher frequency price limits hitting. The trading mechanisms in this market are the same as the trading mechanisms in China's stock market. Then, we designed a series of simu...

there are two major methods in predincing the pattern of share value in the stock market: fundamental analysis and technical analysis. i this study we developed a novel model for fundamental analysis of share price and validated it by predicting the behavior of phrama share price in tehran stock market. the efficiency of the fundamental method was compared with that of indicator-based technical...