Yen-Hsien Lee

Examining market efficiency for large- and small-capitalization of TOPIX and FTSE stock indices

This article uses parametric and nonparametric Variance Ratio (VR) tests of Lo and Mackinlay (1988) and Wright (2000) to re-examine the weak-form Efficient Market Hypothesis (EMH) for the large- and small-capitalization stock indices of TOPIX (Tokyo Stock Price Index) and FTSE (Financial Times Stock Exchange). Unlike the previous studies, the multiple VR test of Chow and Denning (1993) is the first extended to the nonparametric VR test of Wright (2000) as suggested by Luger (2003). The empirical results show that the weak-form EMH is supported for large-cap stock indices, but rejected for small-cap ones. This conclusion is further confirmed by using a rolling multiple VR tests.

Friends or enemies? Foreign investors in Taiwan

This study investigates how foreign investors impact the Taiwanese stock market using the AutoRegressive Jump Intensity (ARJI) model proposed by Chan and Maheu (2002), in which stock volatility in Taiwan is classified as either normal or abnormal and the net purchases of foreign investors, together with the classified volatilities, are included in the bivariate Vector Autoregression (VAR) model for further analyses. The sample period comprises of two parts, namely before and after relaxation of the restrictions on Qualified Foreign Institutional Investor (QFII) investors on 2 October 2003 (pre- and post-QFII). The forecast error variance decompositions and impulse–response functions are obtained via simulating the VAR model. Our results indicate why previous studies, in which abnormal volatilities were not taken into account, confronted biased and inconsistent results. Biased results from previous studies tend to be caused by not differentiating between normal and abnormal volatilities, and the results of this study provide a valuable reference for efforts to end conflicting arguments for whether destabilizing or stabilizing stock markets of foreign investor transactions. Furthermore, the study results also indicate why Taiwan was less affected during the Asian financial crisis.

Nonlinear adjustment of short-term deviations impacts on the US real estate market

This study examines whether nonlinear adjustment of short-term deviations impacts US real estate market returns by applying an exponential smooth transition threshold error-correction model with Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) (ESTECM-GARCH). Empirical results demonstrate that the ESTECM-GARCH captures the dynamics of returns more effectively than the Error-Correction Model (ECM) and Exponential Smooth Transition Error-Correction Model (ESTECM). Consequently, the nonlinear behaviour of returns is driven by momentum noise traders and heterogeneous arbitrageurs in Real Estate Investment Trust (REIT) markets.

Structural changes in foreign investors’ trading behavior and the corresponding impact on Taiwan's stock market

Abstract This study investigates the impact of the expected and unexpected trading behavior of foreign investors on return volatilities during structural change periods. And the jump intensity model pinpoints crucial events that have influenced the stock market. The empirical results find that there has been a stabilizing effect of foreign investment on Taiwans stock market as restrictions on foreign trading have been gradually relaxed, as opposed to there being a complete relaxation of the restrictions imposed on Qualified Foreign Institutional Investors (QFIIs).

Arbitrage behaviour in the exchange rates of Taiwan and Japan: applying the smooth transition vector error correction model with GJR-GARCH and spillover volatility

This study utilizes a Smooth Transition Vector Error Correction Model (STVECM) with Glosten–Jagannathan–Runkle-Generalized Autoregressive Conditional Heteroscedasticity (GJR-GARCH) and spillover volatility to investigate the changes in short-run return dynamics when a deviation from the comovement equilibrium between the prices of New Taiwan Dollar (NTD) and Japan Yen (JPY) exists. Empirical results demonstrated that both exchange rates have a nonlinear relationship with the comovement equilibrium, which was captured by the Logistic Smooth Transition Vector Error Correction Model with GJR-GARCH and Spillover Volatility (LSTVECM-GJR-GARCH-SV). Both exchange rates will quickly reverse to equilibrium when there are large deviations between the two exchange rates, implying that information traders obtain profit in two markets, and then both exchange rates continue to deviate from equilibrium when small deviations exist from comovement, owing to noise trader to expand mispricing. Moreover, small and large deviations may have obvious differences and adjustment speeds when reverting to equilibrium for large negative and large positive deviations. Thus, this study applied LSTVECM-GJR-GARCH-SV to elucidate arbitrage behaviour.

Causes and Impacts of Foreign and Domestic Institutional Investors’ Herding in the Taiwan Stock Market

ABSTRACT This study examines whether herding exists among foreign institutional investors (FIIs), what is the cause of their herding, and whether both foreign and domestic institutional investors are more likely to follow their similar types in the Taiwan stock market. By testing the cross-sectional dependence for FIIs’ stocks in two adjacent months, we demonstrate that the FIIs’ cascades mainly result from their herding. We find little evidence that FIIs’ herding behavior is driven by habit investing. The momentum trading of FIIs is found to account for little of their herding. Moreover, investigative herding, rather than informational cascades is the main reason for FIIs’ herding. One of our contributions may be to find that FIIs’ cascades mainly resulting from their herding does not change in the bullish and bearish Taiwan stock market. This study further finds that FIIs and dealers are more likely to follow similar-type institutions than different-type institutions, respectively.

Analysis of price discovery and non-linear dynamics between volatility index and volatility index futures

ABSTRACT This study utilises a smooth transition vector error correction model with a Generalised AutoRegressive Conditional Heteroskedasticity GARCH model to investigate the price-discovery and non-linear dynamics at different times when a deviation occurs in the co-movement equilibrium between the spot volatility index (VIX) and futures. Our results show support for relative price-discovery contribution from both VIX spot and VIX futures markets. Moreover, we provide evidence that information traders obtain profits by exhibiting more confidence in exploiting large deviations from the equilibrium in these two markets, whereas noise traders expand their mispricing behaviour. Both VIX spot and VIX futures in turn continue to deviate from equilibrium with the existence of large deviations from the co-movement.

Does the US Fear Gauge Impact on the Investor Fear Gauge in the Emerging Markets

This article investigates the investor fear gauge linkages among the American and emerging markets, such as, India (India volatility index (IVIX)), South Korea (Volatility Korea Composite Stock Price Index (VKSOPI)), South Africa (South African Volatility Index (SAVI)) and Russian (Russian Volatility Index (RTSVX)). This article further captures the diffusion and jump relationships between the volatility indices (VIXs) in US and emerging markets by applying the correlated bivariate Poisson (CBP) jump model. The empirical result found that the change in the VIX in the US has a substantial impact over the change in the VIXs of emerging markets. The changes in the VIXs exhibit individual jump behaviour. Finally, this article found the time-varying joint jump intensity between the VIXs in US and emerging markets. JEL Classification: C32, C5