Topic
Stock exchange
About: Stock exchange is a research topic. Over the lifetime, 39566 publications have been published within this topic receiving 612044 citations.
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15 Sep 1982
TL;DR: In this article, an automated stock exchange in which a computer matches buy and sell orders for a plurality of stocks is simulated through two stages, the first stage is an order accumulation period which is continuously in operation except for one stock in the second stage.
Abstract: An automated stock exchange in which a computer matches buy and sell orders for a plurality of stocks. An open board simultaneous trading environment is simulated through two stages. The first stage is an order accumulation period which is continuously in operation except for one stock in the second stage. The second stage is an extremely rapid sequential call through. All orders for a given stock are available to customers during the first stage. During the second stage market orders are matched with market orders, then market orders are traded against limit orders as the trading price changes within controlled ranges. The system will also process stop orders, and other specialized transactions.
573 citations
TL;DR: In this article, the authors employ extreme value theory, focusing exclusively on the larger observations in order to assess the tail shape within a unified framework, which enables one to generate robust probabilities on large returns, which put the recent stock market swings into historical perspective.
Abstract: textNumerous articles have investigated the distribution of share prices, and find that the returns are fat tailed. Nevertheless, there is still controversy about the amount of probability mass in the tails, and hence about the most appropriate distribution to use in modeling returns. This controversy has proven hard to resolve, as the alternatives are non-nested. We employ extreme value theory, focusing exclusively on the larger observations in order to assess the tail shape within a unified framework. We find that at least the first two moments exist. This enables one to generate robust probabilities on large returns, which put the recent stock market swings into historical perspective.
573 citations
26 Mar 2014
TL;DR: Results obtained revealed that the ARIMA model has a strong potential for short-term prediction and can compete favourably with existing techniques for stock price prediction.
Abstract: Stock price prediction is an important topic in finance and economics which has spurred the interest of researchers over the years to develop better predictive models. The autoregressive integrated moving average (ARIMA) models have been explored in literature for time series prediction. This paper presents extensive process of building stock price predictive model using the ARIMA model. Published stock data obtained from New York Stock Exchange (NYSE) and Nigeria Stock Exchange (NSE) are used with stock price predictive model developed. Results obtained revealed that the ARIMA model has a strong potential for short-term prediction and can compete favourably with existing techniques for stock price prediction.
569 citations
TL;DR: The authors examined the effect of real activity news on proxies for expected cash flows and equity discount rates and found that when the economy is strong the stock market responds negatively to news about higher real economic activity.
Abstract: Previous research finds that fundamental macroeconomic news has little effect on stock prices. We show that after allowing for different stages of the business cycle, a stronger relationship between stock prices and news is evident. In addition to stock prices, we examine the effect of real activity news on proxies for expected cash flows and equity discount rates. We find that when the economy is strong the stock market responds negatively to news about higher real economic activity. This negative relation is caused by the larger increase in discount rates relative to expected cash flows. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
568 citations
TL;DR: A phenomenological study of stock price fluctuations of individual companies, which finds that the tails of the distributions can be well described by a power-law decay, well outside the stable Lévy regime.
Abstract: We present a phenomenological study of stock price fluctuations of individual companies. We systematically analyze two different databases covering securities from the three major U.S. stock markets: ~a! the New York Stock Exchange, ~b! the American Stock Exchange, and ~c! the National Association of Securities Dealers Automated Quotation stock market. Specifically, we consider~i! the trades and quotes database, for which we analyze 40 million records for 1000 U.S. companies for the 2-yr period 1994‐95; and ~ii! the Center for Research and Security Prices database, for which we analyze 35 million daily records for approximately 16 000 companies in the 35-yr period 1962‐96. We study the probability distribution of returns over varying time scales Dt, where Dt varies by a factor of ’10 5 , from 5 min up to ’4 yr. For time scales from 5 min up to approximately 16 days, we find that the tails of the distributions can be well described by a power-law decay,
557 citations