Results 251 to 260 of about 2,297,891 (304)
Some of the next articles are maybe not open access.
Noisy Stock Prices and Corporate Investment
The Review of financial studies, 2018Firms significantly reduce their investment in response to non-fundamental drops in the stock price of their product-market peers. We argue that this result arises because of managers' limited ability to filter out the noise in stock prices when using ...
Olivier Dessaint +3 more
semanticscholar +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
Option Prices as Predictors of Equilibrium Stock Prices
The Journal of Finance, 1982ABSTRACTThe Black‐Scholes option pricing model, modified for dividend payments, is used to calculate jointly implied stock prices and implied standard deviations. A comparison of the implied stock prices with observed stock prices reveals that the implied prices contain information regarding equilibrium stock prices that is not fully reflected in ...
Manaster, Steven +1 more
openaire +1 more source
Energy Economics, 2018
We assess the impact of quantile price movements in oil, gas, coal and electricity on the quantiles of clean energy stock returns using a multivariate vine-copula dependence setup.
J. Reboredo, A. Ugolini
semanticscholar +1 more source
We assess the impact of quantile price movements in oil, gas, coal and electricity on the quantiles of clean energy stock returns using a multivariate vine-copula dependence setup.
J. Reboredo, A. Ugolini
semanticscholar +1 more source
Stock Price Synchronicity and Liquidity
SSRN Electronic Journal, 2008Abstract We argue and provide evidence that stock price synchronicity affects stock liquidity. Under the relative synchronicity hypothesis, higher return co-movement (i.e., higher systematic volatility relative to total volatility) improves liquidity.
Chan, K., Hameed, A., Kang, W.
openaire +2 more sources
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
On the increments distribution of stock prices
Applied Mathematics-A Journal of Chinese Universities, 2001The authors construct the models of increment distributions of stock prices in two approaches. The first approach is based on limit theorems of random summation. The second is based on the statistical analysis of increment distributions of the logarithms of stock prices.
Korolev, V. Yu. +2 more
openaire +1 more source
Insider Trading and Stock Prices
SSRN Electronic Journal, 2011Abstract We examine the informational content of insider trades and its value to market investors using a US dataset. Overall, our results support the view that insider actions have positive predictive power for future returns. However, these results may come with some caveats.
Manouchehr Tavakoli +2 more
openaire +1 more source
THE DISTRIBUTION OF RETURNS OF STOCK PRICES
International Journal of Theoretical and Applied Finance, 2000We perform a phenomenological study of stock price fluctuations of individual companies. We systematically analyze two different databases covering securities from the three major US stock markets. We consider (i) the trades and quotes (TAQ) database, for which we analyze 40 million records for 1000 US companies for the 2-year period 1994–95, and (ii)
Amaral, Luís A. N. +4 more
openaire +2 more sources
The analysis and prediction of stock price
2013 IEEE International Conference on Granular Computing (GrC), 2013Nowadays, the stock market has attracted more and more people's attention with its high risk and high returns, and forecasting method of stock price also emerge in an endless stream, such as nonlinear regression. In this paper, we introduce a kind of method based on Hidden Markov Model to forecast stock price trend. Which is different from the existing
Tao Xing, Yuan Sun, Qian Wang, Guo Yu
openaire +1 more source