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Many market technicians claim that technical rules are effective more in bear markets than in bull markets. Using the 2008 financial crisis as the backdrop for testing, this study investigates how effective they are in the stock markets of Hong Kong, Korea, Singapore and Taiwan. Accordingly, this study performs three tasks. First, it examines the transmission mechanism of stock market movements between the U.S. market and the four Asian markets using vector autoregression. Second, it employs three technical rules - simple moving average, dual moving average, and trading range break - and evaluates their effectiveness in the four markets. Third, it uses the bootstrap method for statistical inferences about the returns from using these technical rules. This study concludes with some important policy implications for the four Asian markets. [ABSTRACT FROM AUTHOR]

Previous options studies typically assume that the dynamics of the underlying asset price follow a geometric Brownian motion (GBM) when pricing options on stocks, stock indices, currencies or futures. However, there is mounting empirical evidence that the volatility of asset price or return is far from constant. This article, in contrast to studies that use parametric approach for option pricing, employs nonparametric kernel regression to deal with changing volatility and, accordingly, prices options on stock index. Specifically, we first estimate nonparametrically the volatility of asset return in the GBM based on the Nadaraya–Watson (N–W) kernel estimator. Then, based on the N–W estimates for the volatility, we use Monte Carlo simulation to compute option prices under different settings. Finally, we compare the index option prices under our nonparametric model with those under the Black–Scholes model and the Stein–Stein model. [ABSTRACT FROM PUBLISHER]