In this study, we explored data from StockTwits, a microblogging platform exclusively dedicated to the stock market. We produced several indicators and analyzed their value when predicting three market variables: returns, volatility and trading volume. For six major stocks, we measured posting volume and sentiment indicators. We advance on the previous studies on this subject by considering a l...

The increased popularity of financial time series forecasting in recent times lies to its great importance in predicting the best stock market timing. In this paper, we develop the concept of a pattern modeling and recognition system for predicting future behavior of time series using local approximation. In order to improve the performance of this system, we propose a systematic and automatic ...

Predictability of the return on the market portfolio is a well established fact. This study shows that predictability is a more general phenomenon and it extends to return indices of the U.S. states. At the state level, the consumption trend deviation of Lettau and Ludvigson, and the collateral ratio of Lustig and Van Nieuwerburgh can predict short-term and long-term state-level returns. The st...

We seek to forecast sector stock returns using established predictor variables. Existing empirical evidence focuses on market level data, and thus, data provide fertile ground for research. In addition in-sample predictive regressions, we consider recursive rolling forecasts whether such can be used successfully in a rotation portfolio. The results ten sectors eleven variables highlight that tw...

Stock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become significant. Many people use the share price movement process when com-paring different stocks while investing, and also want to pred...

Stock market prediction is an attractive research problem to be investigated. News contents are one of the most important factors that have influence on market. Considering the news impact in analyzing the stock market behavior, leads to more precise predictions and as a result more profitable trades. So far various prototypes have been developed which consider the impact of news in stock marke...

In this paper, we model a stock dynamic using Hidden Markov Model (HMM) where weekly return is normally distributed with mean and variance depending on the hidden random variable representing the stock trend. Using Expectation-Maximization algorithm, we estimate all the parameters and design a simple trading strategy based on it. We then compare its performance with Buy and Hold and Resistance ...

Sales forecasting is a starting point of supply chain management, and its accuracy influences business management significantly. In industries, how to improve forecasting accuracy such as sales, shipping is an important issue. In this paper, a hybrid method is introduced and plural methods are compared. Focusing that the equation of exponential smoothing method (ESM) is equivalent to (1,1) orde...

This paper deals with the application of a well-known neural network technique, multi-layer back-propagation (BP) neural network, in financial data mining. A modified neural network forecasting model is presented, and an intelligent mining system is developed. The system can forecast the buying and selling signs according to the prediction of future trends to stock market, and provide decision-...