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IPO (Initial Public Offerings) pricing is a systematic and complicated task that directly determines whether the capital market is able to function in a healthy way. As China's stock market goes through ups and downs, China Securities Regulatory Commission generally adopts a positive strategy. Therefore, to weaken the policy factors, 48 cases of IPO companies dated from January 2014 to February 2014...
Stock market dynamics is of great importance to researchers from diverse fields. Network Analysis of stock data can play an important role in the study of stock market. In this paper, network based data mining of stock market is done to identify crucial players. Stock market network in United States created based on dynamics of stocks over one year captured as daily time series, is used for the analysis...
Continuous haze in China has become a social concern that affects people's moods and behavior. This paper uses GARCH model to examine whether air quality can be a proxy variable of emotion to affect stock market. The paper compounds national Air Quality Index (AQI) weighted by the proportion of investors in certain regions, as well as taking in all available data that ranges from January 1, 2014 to...
Previous studies have shown that changes in human emotions or public opinions can have an impact on volatility of stock market. In this paper, we make use of the unstructured comments data from the stock forum on the Shanghai Composite Index to generate the structural emotion time series of the stock market based on a series of methods including word segmentation, feature extraction, machine learning...
The Detrending Moving Average (DMA) algorithm can be implemented to estimate the Shannon entropy of a long-range correlated sequence which will be shown to be of particular relevance for its significance in finance. The entropy is written as the sum of two terms corresponding respectively to power-law (ordered) and exponentially (disordered) distributed blocks (clusters). Interestingly, the behaviour...
There are many similarities on fluctuations between clothing styles and finance so that many theorists approach to analyze the relationship of them, the best known of which is the Hemline Index Theory. When the economy is flourishing, hemlines increase, and when the economic situation is deteriorating, the hemlines drop, perhaps even to the floor. In contrast with measuring the illustrations from...
The emergence of computing power and the abundance of data have made it possible to assist human decisions, especially in the stock markets, in which the ability to predict future values would lower the risk of investing. In this paper, we present a new approach for identifying the predictive power of public emotions extracted from various sections of daily news articles on the movements of stock...
Twitter has transformed from an online platform for communication to a mega content generator for all kinds of topics. The topic of posts (or tweets) generated on Twitter cover diverse topics of interests. For example, politics, public personalities, events and corporate organizations. In this study, we analysed if tweets related to corporate organizations can predict the financial market. Our analysis...
Forecasting volatility in the stock market is an important research topic that has been immensely reviewed over the years. However, in Sri Lankan context this research topic is studied by only few researchers and they did not incorporate the day of the week effect in their studies. Therefore, this study examines the impact of the day of the week effect on All Share Price Index (ASPI) of Colombo Stock...
Investing in stocks is one of the most popular approaches for money investment. This paper aims to predict short-term stock prices of SET50 of Stock Exchange of Thailand (SET). The proposed method is called CARIMA (Cross Correlation Autoregressive Integrated Moving Average. The basic idea of CARIMA is to find the most highly correlated s tock t o predict the target one in addition to ARIMA predicted...
In this study, we used the Google Trends as a prediction tool to predict the investors' behavior and its impact on stock market. In the behavior and social perspective, more and more Internet users use Google Trends as the search engine to surf on the websites every day. Therefore, these search actions can be seen as personal votes because Internet users often search items they are interested in....
The Chinese stock market is ever changing and will play an increasingly important role in the global financial system. By analyzing topological properties of this market and temporal changes, this paper investigates network dynamics of this market by emphasizing interdependencies between stocks. This study partially selects 176 constituent stocks of CSI 300 index during the period of January 2009...
By conducting a word frequency statistics in the posing on Eastmoney forum bar about SSE Composite Index from January 7, 2010 to August 30, 2013, we establish a set of keyword dictionary to measure investor sentiment effectively, and accordingly to study the mutual relations between the abnormal investor sentiment based on the network forums and the abnormal trading volume in the trading market. The...
This paper proves the China stock market to be a chaotic system and establishes a nonlinear dynamical model for it based on the study on the nonlinear dynamical properties of Shanghai stock composite index sequence by using chaos and fractal theory. The phase space of the stock sequence is reconstructed and the correlation dimension is analyzed, which indicate that the dynamical system has finite...
In recent years, researches on stock price behavior after factor driven major price shocks have raised more attention. In this paper, investors' under-reaction (overreaction) to information is regarded as an interpretation of momentum (reversal). Using analyst reports as a proxy, we compare post-event stock returns evolution of stocks with information and without information after major price shocks...
In the capital market, the stocks which have more impact on the other stocks, are called “influential stocks.” If we can find the influential stocks of market, we can analyze present and future status of the market only by investigating them. This paper proposes a method for determining the influential stocks and estimating the market index using them. The influential stocks are recognized based on...
In this paper we present a model to predict the stock trend based on a combination of sequential chart pattern, K-Means and AprioriAll algorithm. The stock price sequence is truncated to charts by sliding window. Then the charts are clustered by K-Means algorithm to form chart patterns. Therefore, the charts form chart pattern sequences, and frequent patterns in the sequences can be extracted by AprioriAll...
The volatility of Shanghai A shares stock market is studied based on the econometric model. Moreover, the stastical characters of the volatility of Shanghai A shares is studied based on ARCH model on this paper, which help invester to judge the trend and development of Shanghai A shares stocket market.
This paper modeled the evolution of the contagious severity of the stock markets combing with the cross-market correlation coefficients, the market capitalizations and the functions of self-remedy into the time-varying coefficients of the epidemic kinetics model. Then we used the data of United States, Russia, Australia, Brazil, China, India, Hong Kong and Japan during the 2007-2009 stock market crisis...
In this paper, we propose a novel approach for decomposing financial market returns into observable risk factors and idiosyncratic risk. We utilize a vector stochastic-volatility model to extract the potentially time-varying exposure of low frequency hedge fund performance on high frequency data. By making use of a particle filter with Rao-Blackwellization, we reduce the dimension of the space where...
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