2 research outputs found
Testing for efficient market hypothesis on Malaysian’s stock market: does crisis regime matter?
No full textIn the context of the recent financial crisis, there has been growing questions about improving the efficiency of the stock market through liberalization. Although many researchers have studied the empirical effects of financial liberalization on stock market efficiency, consistent conclusions remain elusive. This paper aims to study the long and short-run relationship between financial liberalization and stock market efficiency before and after the global crisis strike in Malaysia. Specifically, Autoregressive Distributed Lag (ARDL) is the main econometric technique applied to explore this study. This study uses quarterly time series data over the period from 1998Q1 to 2020Q4. The findings revealed that financial openness and trade openness affect the stock market positively in the short and long term. In conclusion, these results indirectly support the efficient market hypothesis in Malaysia. Findings provide some policy implications in which the country should reinforce the prerequisites of openness to avoid the potential of initial crisis by equipping in an appropriate manner to minimize the short-term costs of liberalization to achieve long-term benefits.</p
Unit Root Tests and Mean Shifts
No full textA mean shift can cause tests for a unit root to erroneously fail to reject the null hypothesis of the existence of a unit root. Perron (1990) and Hendry and Neale (1991) provide simulation evidence of this for (augmented) Dickey-Fuller tests in models without a time trend. This paper extends these analyses by considering a wider range of test statistics (including statistics proposed by Bhargava (1986)) applied to models (possibly including a time trend) subject to a shift in mean. Our simulation results show that, at least for alternatives close to the unit root, either an appropriate Bhargava test statistic or the suitably normalised OLS estimator of the unit root has higher power than the Dickey-Fuller or augmented Dickey-Fuller t-tests. In particular, in models with a trend, an increase in the mean shift does not reduce the power of Bhargava's R2 test as much as it reduces the power of the other tests. Estimated response surfaces summarise the likely power loss due to any particular mean shift
