Showing papers on "Market capitalization published in 1989"
TL;DR: In this article, the authors investigated the international transmission mechanism of stock market movements by estimating a nine-market vector autoregression (VAR) system and found that a substantial amount of multi-lateral interaction is detected among national stock markets.
Abstract: This paper investigates the international transmission mechanism of stock market movements by estimating a nine-market vector autoregression (VAR) system. Using simulated responses of the estimated VAR system, we (i) locate all the main channels of interactions among national stock markets, and (ii) trace out the dynamic responses of one market to innovations in another. Generally speaking, a substantial amount of multi-lateral interaction is detected among national stock markets. Innovations in the U.S. are rapidly transmitted to other markets in a clearly recognizable fashion, whereas no single foreign market can significantly explain the U.S. market movements. Also, the dynamic response pattern is found to be generally consistent with the notion of informationally efficient international stock markets.
1,517 citations
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TL;DR: This paper found that the U.S. stock market has better predictive power than the Canadian market for long periods of time, especially for long samples that begin in 1891 or 1921.
Abstract: Changes in real stock-market prices have a lot of explanatory value of the growth rate of U.S. aggregate business investment, especially for long samples that begin in 1891 or 1921. Moreover, for the period since 1921 where data on a q-type variable are available, the stock market dramatically outperforms q. The change in real stock prices also retains its predictive value in the presence of a cash-flow variable, such as after-tax corporate profits. Basically similar results apply to Canadian investment, except that the U.S. stock market turns out to have move predictive power than the Canadian market. I discuss some possible explanations for this puzzling finding, but none of the explanations seem all that convincing.
601 citations
TL;DR: In this paper, the authors present a forecast of economic growth from the bond and stock markets for the next five years, based on economic growth in the United States and the Eurozone.
Abstract: (1989). Forecasts of Economic Growth from the Bond and Stock Markets. Financial Analysts Journal: Vol. 45, No. 5, pp. 38-45.
372 citations
TL;DR: In this paper, the impact of particular dates and periods of the civil year and stock exchange calendars on stock price changes to test the existence of information inefficiencies is analyzed based on the Milan Stock Exchange's "MIB storico" stock index with reference to the period 2 January 1975 - 22 August 1989.
Abstract: After describing the various concepts of efficiency (information, valuation, full-insurance and functional) with special reference to the Italian stock market, the paper analyzes the impact of particular dates and periods of the civil year and stock exchange calendars on stock price changes to test the existence of information inefficiencies. The analysis is based on the Milan Stock Exchange's "MIB storico" stock index with reference to the period 2 January 1975 - 22 August 1989. The events tested for systematic anomalies include weekend and public holidays, the end of the calendar and stock exchange months, and the end of the year. The results obtained are in line with those found for the US market, with evidence of anomalous changes, though not all are stable over time.
171 citations
01 Jan 1989
TL;DR: For example, the authors pointed out that very large increases or decreases would always be possible even if changes in stock prices were normally distributed, but they would occur only rarely and that the variation of stock prices does not nicely match the familiar bell-shaped normal distribution.
Abstract: MOST PEOPLE AGREE that stock prices sometimes behave in strange ways. Going beyond this simple observation typically proves more difficult. For at least the past quarter century, economists have been well aware that the variation of stock prices does not nicely match the familiar bell-shaped normal distribution.1 The problem is too many extreme movements. Very large increases or decreases would always be possible even if changes in stock prices were normally distributed, but they would occur only rarely. By contrast, actual stock prices rise or fall by large percentage amounts fairly often-certainly often enough to raise serious doubts that the usual normal distribution provides a useful way to think about how they vary. Economists and other analysts of the stock market have tended to react to this problem in either of two ways. The most common approach is simply to ignore it and go ahead to analyze changes in stock prices as
146 citations
TL;DR: In this article, the results of two nonlinearity tests on 27 stock market prices traded on five world stock exchanges are reported and bilinear time series models are fitted to the stock return data.
26 citations
3 citations