The objective of the paper is to investigate whether price indices of different European stock markets display a common long-run trending behaviour. Using cointegration analysis, we provide empirical evidence of common stochastic trends among five important European stock markets over the period 1975-1991.
Stock returns series generally exhibit time-varying volatility. Therefore, one can cast doubt on the way abnormal returns are calculated and consequently interpreted in traditional event studies. In this paper we apply a market model which accounts for GARCH effects leading to more efficient estimators. Using a sample of divestitures, we empirically investigate how this adjustment affects the magnitude of the abnormal returns associated with an event.
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AbstractThis article examines the long run performance of initial public offerings (IPOs) in Malaysia over the four-year period between 1992 and 1996. In particular, the study investigates whether the growth/value effect exists. By analysing the sample of 258 IPOs, it can be concluded that IPOs tend to outperform the market with a positive cumulative adjusted market return (CAR) of 41.7% over three years from the listing day. The results are contradictory to general empirical findings in other countries. As expected, growth IPOs underperform value IPOs when the IPOs are sorted using book-to-market equity ratio (B/M), earnings-to-price ratio (E/P) and cashflows-to-price ratio (C/P). Nonetheless, it should be pointed out that both value and growth IPOs generate higher returns than the market. The regression results indicate positive relationship between CAR and book-tomarket equity (B/M). Similar results are derived for earnings-to-price (E/P) and cashflows-to-price (C/P). In addition to this, the size of an IPO is found to be inversely related to CAR.
This paper attempts to model the distributional properties of daily stock returns on several European Stock Exchanges. The empirical findings reveal the presence of non‐linear dependencies that cannot be captured by the random walk model. A model of return‐generating process that fit the data empirically is the Generalized Autoregressive Conditional Heteroskedastic GARCH (1,1) process with a conditional student‐t distribution.
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