Article terms can move stock prices. By analyzing verbs in financial news articles and coupling their usage with a discrete machine learning algorithm tied to stock price movement, we can build a model of price movement based upon the verbs used, to not only identify those terms that can move a stock price the most, but also whether they move the predicted price up or down.

Financial firms make up a substantial fraction of the domestic equity market. A number of studies subsequently used different conceptual and methodological approaches to model equity return of financial services firms. Movement of the stock price as the consequence of the movement of the micro and macroeconomic factors is strongly supported by the literature review. Amman Stock Exchange in Jord...

We use recent developments on threshold autoregressive models that allow deriving endogenously threshold effects to analyse the evolution of the US stock price–dividend relation over the period 1871 to 2004. More specifically, a mean-reverting dynamic behaviour of the stock price–dividend ratio should be expected once such threshold is reached. Our empirical results showed that significant adju...

One of the most important methods of opacity accounting information by management is to accelerate the identification of good news versus delaying the identification of bad news on profits, but there is always a final level of accumulation of bad news in the company, and by reaching that its final level, these bad news will be released, which will lead to a Stock Price Crash Risk. In fact, stoc...

The study investigates the effect of macroeconomic determinants on the performance of the Indian Stock Market using monthly data over the period January 1991 to December 2011 for eight macroeconomic variables, namely, Interest Rate, Inflation, Exchange Rate, Index of Industrial Production, Money Supply, Gold Price, Silver Price & Oil Price, and two stock market indices namely Sensex and S&P CNX...

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market ...

We consider the problem of stock repurchase over a finite time horizon. We assume that a firm has a reservation price for the stock, which is the highest price that the firm is willing to pay to repurchase its own stock. We characterize the optimal policy for the trader to maximize the total number of shares he can buy over a fixed time horizon. In particular, we study a greedy policy, which in...

Stock Exchange Share Price is very hard to predict since there are no significant rules to estimate or predict that. Stock price prediction is one of the emerging field of research and many methods like technical analysis, statistical analysis, time series analysis etc are used for this purpose. Artificial Neural Network is a popular technique for the stock price prediction. Here we use Multila...

We consider the problem of stock repurchase over a finite time horizon. We assume that a firm has a reservation price for the stock, which is the highest price that the firm is willing to pay to repurchase its own stock. We characterize the optimal policy for the trader to maximize the total number of shares he can buy over a fixed time horizon. In particular, we study a greedy policy, which in...