nep-fmk New Economics Papers
on Financial Markets
Issue of 2005‒02‒06
three papers chosen by
Erik Schloegl
School of Mathematical Sciences University of Technology

  1. Sources of Predictability of European Stock Markets for High-Technology Firms By Christian Pierdzioch; Andrea Schertler
  2. Financial Integration for India Stock Market, a Fractional Cointegration Approach By Wing-Keung Wong; Aman Agarwal; Jun Du
  3. A better asymmetric model of changing volatility in stock returns: Trend-GARCH By Christian Bauer

  1. By: Christian Pierdzioch; Andrea Schertler
    Abstract: We study return predictability of stock indexes of blue chip firms and smaller hightechnology firms in Germany, France, and the United Kingdom during the second half of the 1990s. We measure return predictability in terms of first-order autocorrelation coefficients, and find evidence for return predictability of stock indexes of smaller hightechnology firms, but no evidence for return predictability of stock indexes of blue chip firms. Our findings suggest that a leading candidate for explaining the economic sources of return predictability of stock indexes of smaller high-technology firms is transaction
    Keywords: Stock markets; Return predictability; High-technology firms
    JEL: G14 N24
    Date: 2005–01
  2. By: Wing-Keung Wong (National University of Singapore); Aman Agarwal (GGS Indraprastha University); Jun Du (National University of Singapore)
    Abstract: The Indian stock market is one of the earliest in Asia being in operation since 1875, but remained largely outside the global integration process until the late 1980s. A number of developing countries in concert with the International Finance Corporation and the World Bank took steps in the 1980s to establish and revitalize their stock markets as an effective way of mobilizing and allocation of finance. In line with the global trend, reform of the Indian stock market began with the establishment of Securities and Exchange Board of India in 1988. This paper empirically investigates the long-run equilibrium relationship and short-run dynamic linkage between the Indian stock market and the stock markets in major developed countries (United States, United Kingdom and Japan) after 1990 by examining the Granger causality relationship and the pairwise, multiple and fractional cointegrations between the Indian stock market and the stock markets from these three developed markets. We conclude that Indian stock market is integrated with mature markets and sensitive to the dynamics in these markets in a long run. In a short run, both US and Japan Granger causes the Indian stock market but not vice versa. In addition, we find that the Indian stock index and the mature stock indices form fractionally cointegrated relationship in the long run with a common fractional, nonstationary component and find that the Johansen method is the best reveal their cointegration relationship.
    Keywords: unit root test, cointegration, Error Correction Model, Vector Autoregression Model, Johansen Multivariate Cointegration, Fractional Cointegration
  3. By: Christian Bauer
    Abstract: In this paper we consider the theoretical and empirical relevance of a new family of conditionally heteroskedastic models with a trend dependent conditional variance equation: the Trend-GARCH model. The interest in these models lies in the fact that modern microeco- nomic theory often suggests the connection between the past behavior of time series and the subsequent reaction of market individuals and thereon changes in the future characteristics of the time series. Our results reveal important properties of these models, which are con- sistent with stylized facts in ?financial data sets. They can also be employed for model identifi?cation, estimation, and testing. The em- pirical analysis of a broad variety of asset prices signi?ficantly supports the existence of trend effects. The Trend-GARCH model proves to be superior to alternative models such as EGARCH, AGARCH, or TGARCH in replicating the leverage effect in the conditional variance and in fi?tting the news impact curve.
    Keywords: GARCH, trend, volatility, news impact curve
    JEL: C22 C52 G12
    Date: 2005–02

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