Results 251 to 260 of about 1,334,088 (306)
Some of the next articles are maybe not open access.
Stock price synchronicity and stock price crash risk
China Finance Review International, 2016Purpose– The purpose of this paper is to empirically analyze the effects of stock price synchronicity and herding behavior of qualified foreign institutional investors (QFII) on stock price crash risk, especially the mediating effect of herding behavior of QFII on the relation of stock price synchronicity and stock price crash risk.Design/methodology ...
Yonghong Jin +3 more
openaire +1 more source
International Review of Economics & Finance, 2021
Abstract We apply concepts form machine learning to forecast stock prices. First, we introduce the general (3 by 3) forecasting model, in which the financial markets are populated by three types of stocks: Overpriced stocks, underpriced stocks and fairly priced stocks.
Arie Harel, Giora Harpaz
openaire +1 more source
Abstract We apply concepts form machine learning to forecast stock prices. First, we introduce the general (3 by 3) forecasting model, in which the financial markets are populated by three types of stocks: Overpriced stocks, underpriced stocks and fairly priced stocks.
Arie Harel, Giora Harpaz
openaire +1 more source
Finance and Credit, 2022
Subject. This article deals with stock pricing factors. Objectives. The article aims to identify factors affecting the share prices of Russian companies. Methods. For the study, I used content, logical, and comparative analyses. Results. The article describes the factors that influence the price of a company's shares, but are not always directly ...
openaire +1 more source
Subject. This article deals with stock pricing factors. Objectives. The article aims to identify factors affecting the share prices of Russian companies. Methods. For the study, I used content, logical, and comparative analyses. Results. The article describes the factors that influence the price of a company's shares, but are not always directly ...
openaire +1 more source
Forecasting Stock Market Prices
The Journal of Finance, 1977building techniques to publicly available information could have permitted an investor to earn a portfolio return in excess of the return which was commensurate with the portfolio risk. The question of equity market efficiency over time is an area of constant disagreement, especially between practitioners and theoreticians. The disagreement is really a
openaire +1 more source
Stock Prices and Heteroscedasticity
The Journal of Business, 1976This paper provides evidence that the variance of returns on common stocks is not constant through time but is related to the volume of shares traded. In other words, returns on stocks are heteroscedastic. The work extends the approaches of Osborne, Granger and Morgenstern, and Clark.' Distributions of returns are known to be leptokurtic.
openaire +1 more source
2023
In this study, the last two years' hourly opening and closing prices of the banks' stocks traded on BIST-30 were used as the dataset. The research is aimed to predict the closing prices of these stocks in the light of machine learning. In this context, the authors propose a new method containing ensemble learning algorithms and fuzzy clustering ...
Ahmet Tezcan Tekin +2 more
openaire +1 more source
In this study, the last two years' hourly opening and closing prices of the banks' stocks traded on BIST-30 were used as the dataset. The research is aimed to predict the closing prices of these stocks in the light of machine learning. In this context, the authors propose a new method containing ensemble learning algorithms and fuzzy clustering ...
Ahmet Tezcan Tekin +2 more
openaire +1 more source
Physical Review E, 2004
We show that the dynamics of stock prices can be accurately described as a continuous time random walk with a time dependent diffusion coefficient. The time evolution of the diffusion coefficient can be derived from tick by tick databases provided the stock price is characterized in terms of a couple of values describing the best ask and the best bid ...
openaire +3 more sources
We show that the dynamics of stock prices can be accurately described as a continuous time random walk with a time dependent diffusion coefficient. The time evolution of the diffusion coefficient can be derived from tick by tick databases provided the stock price is characterized in terms of a couple of values describing the best ask and the best bid ...
openaire +3 more sources
Proceedings of the 2018 2nd International Conference on Cloud and Big Data Computing, 2018
Stock price forecasting has tremendous importance, it is one of the most challenging tasks due to the high volatility of stock market data. Share market investment is often risky, hence the need for an accurate forecasting model to minimize this risk. This article aims to present a new model for forecasting stock prices for a given horizon.
Yassine Touzani +2 more
openaire +1 more source
Stock price forecasting has tremendous importance, it is one of the most challenging tasks due to the high volatility of stock market data. Share market investment is often risky, hence the need for an accurate forecasting model to minimize this risk. This article aims to present a new model for forecasting stock prices for a given horizon.
Yassine Touzani +2 more
openaire +1 more source
eLearning and Software for Education, 2020
E-learning, in most contexts, is becoming a more accessible and efficient method of training through which people could acquire new knowledge. Due the difference between epochs, reading and analysing the growing flow of information has become a very challenging task for financial professionals.
openaire +1 more source
E-learning, in most contexts, is becoming a more accessible and efficient method of training through which people could acquire new knowledge. Due the difference between epochs, reading and analysing the growing flow of information has become a very challenging task for financial professionals.
openaire +1 more source
SSRN Electronic Journal, 2015
A kinetic model of stock price returns is presented for the description of the stock price dynamics through an impact of the information signals on investor behaviours. The model incorporates behavioural processes of the influence of the private or public information on the exchange of cash and shares flows.
openaire +1 more source
A kinetic model of stock price returns is presented for the description of the stock price dynamics through an impact of the information signals on investor behaviours. The model incorporates behavioural processes of the influence of the private or public information on the exchange of cash and shares flows.
openaire +1 more source