Results 251 to 260 of about 960,932 (306)
EconoGNN: A graph neural network framework for temporal economic resilience insights. [PDF]
PLoS OneAraujo M, Rodrigues F, Sousa E.
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Artificial intelligence in financial market prediction: advancements in machine learning for stock price forecasting. [PDF]
Front Artif IntellRohan A +5 more
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Review of Financial Studies, 1992
The authors undertake a comprehensive investigation of price and volume co-movement using daily New York Stock Exchange data from 1928 to 1987. They adjust the data to take into account well-known calendar effects and long-run trends. To describe the process, they use a seminonparametric estimate of the joint density of current price change and volume ...
Gallant, A Ronald +2 more
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The authors undertake a comprehensive investigation of price and volume co-movement using daily New York Stock Exchange data from 1928 to 1987. They adjust the data to take into account well-known calendar effects and long-run trends. To describe the process, they use a seminonparametric estimate of the joint density of current price change and volume ...
Gallant, A Ronald +2 more
+5 more sources
SSRN Electronic Journal, 2010
We study the relation between the ownership structure of financial assets and non-fundamental risk. We define an asset to be fragile if it is susceptible to non-fundamental shifts in demand. An asset can be fragile because of concentrated ownership, or because its owners face correlated or volatile liquidity shocks, i.e., they must buy or sell at the ...
Greenwood, Robin, Thesmar, David
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We study the relation between the ownership structure of financial assets and non-fundamental risk. We define an asset to be fragile if it is susceptible to non-fundamental shifts in demand. An asset can be fragile because of concentrated ownership, or because its owners face correlated or volatile liquidity shocks, i.e., they must buy or sell at the ...
Greenwood, Robin, Thesmar, David
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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 ...
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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 ...
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What moves stock prices? [PDF]
The Journal of Portfolio Management, 1989 This paper estimates the fraction of the variance in aggregate stock returns that can be attributed to various kinds of news. First, we consider macroeconomic news and show that it is difficult to explain more than one third of the return variance from this source. Second, to explore the possibility that the stock market responds to information that is
David M. Cutler +2 more
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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
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Advances in Economics, Management and Political Sciences, 2023
As Apple becomes a world-leading technology company, it is no doubt that its stock has brought a huge amount of profit to its investors. Many investors rely on financial modules to estimate the change in stock values and make the final decision. They contribute significantly to the decision-making of investors. This paper intends to use the composition
openaire +1 more source
As Apple becomes a world-leading technology company, it is no doubt that its stock has brought a huge amount of profit to its investors. Many investors rely on financial modules to estimate the change in stock values and make the final decision. They contribute significantly to the decision-making of investors. This paper intends to use the composition
openaire +1 more source