Potential gains from sector timing in Taiwan

The dominance of the electronic sector in the Taiwanese stock market and the relatively low historical correlation between the Taiwanese electronic and financial sector indexes call for the exploration of sector diversity in the Taiwanese stock market. This study investigates the effectiveness of sector timing in Taiwan by evaluating the likely outcomes from switching between the electronic and the financial indexes for data spanning the period December 1999 through December 2012. The proposed sector timing strategy could be implemented using Taiwanese sector index futures. The market timer is assumed to have different timing abilities in the electronic-dominant market and the financial-dominant market. The main results of the research include that when transaction costs are taken into consideration, significant sector timing ability is required to beat the sector benchmark; and it is more important to improve the ability in timing the financial-dominant market in Taiwan.International Bibliography of Social Science

The Information Content of Implied Volatility in the Hong Kong and Singapore Covered Warrants Markets

This paper examines the informational content and predictive power of implied volatility over different forecasting horizons in a sample of European covered warrants traded in the Hong Kong and Singapore markets. The empirical results show that time-series-based volatility forecasts outperform implied volatility forecast as a predictor of future volatility. The finding also suggests that implied volatility is biased and informationally inefficient. The results are due to the fact in Hong Kong and Singapore the covered warrants markets are dominated by retail investors, who tend to use covered warrants’ leverage to speculate on the price movements of the underlying rather than to express their view on volatility.

Modeling Financial Time Series with Artificial Neural Networks

Financial time series convey the decisions and actions of a population of human actors over time. Econometric and regressive models have been developed in the past decades for analyzing these time series. More recently, biologically inspired artificial neural network models have been shown to overcome some of the main challenges of traditional techniques by better exploiting the non-linear, non-stationary, and oscillatory nature of noisy, chaotic human interactions. This review paper explores the options, benefits, and weaknesses of the various forms of artificial neural networks as compared with regression techniques in the field of financial time series analysis.CELEST, a National Science Foundation Science of Learning Center (SBE-0354378); SyNAPSE program of the Defense Advanced Research Project Agency (HR001109-03-0001

Behavior and Effects of Equity Foreign Investors on Emerging Markets

This paper analyzes empirically the behavior of foreign investors on emerging equity markets in a cross-country setting, including 14 emerging markets from the year 2000 to 2005. We could find little evidence that these investors have brought problems to local emerging markets. Foreign investors seem to build and unwind their positions on emerging stock markets slowly enough to avoid problems as price pressure or volatility and kurtosis upswings on the stock market. Also, no negative effects on the foreign exchange market could be found. Regarding feedback trading, we support two hypotheses: positive feedback trading by hedged investors and negative feedback trading by unhedged investors. The latter has stronger statistical evidence and is more likely to occur in the real world. We conclude that there is no reason to impose long-term restrictions to foreign flows.

Macroeconomic Volatility and Stock Market Volatility, World-Wide

Notwithstanding its impressive contributions to empirical financial economics, there remains a significant gap in the volatility literature, namely its relative neglect of the connection between macroeconomic fundamentals and asset return volatility. We progress by analyzing a broad international cross section of stock markets covering approximately forty countries. We find a clear link between macroeconomic fundamentals and stock market volatilities, with volatile fundamentals translating into volatile stock markets.Financial market, equity market, asset return, risk, variance, asset pricing

Risk Characteristics of Real Estate Related Securities--An Extension of Liu and Mei (1992)

This study extends from Liu and Mei (1992) by further investigation of assets, real estate related securities, which includes both equity and mortgage real estate investment trusts (REITs), the stocks of builder- and owner-companies, and mortgage-backed securities (MBSs). There are five major findings. First, expected excess returns of real estate related securities are more predictable than the expected excess returns of value-weighted stocks and bonds. Second, right market timing is important to investors since evidence shows that the risk premiums of real estate related securities vary substantially over time. Third, real estate market conditions significantly influence bonds and MBSs. Fourth, MBSs are more similar to bonds than mortgage REITs. In addition, returns on mortgage REITs resemble both stocks and bonds. Finally, real estate stocks have a very high sensitivity toward stock market portfolio. This suggests that real estate stocks are not good instruments to help diversify stock risk.

Measuring financial asset return and volatility spillovers : with application to global equity markets

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non-crisis and crisis episodes, including trends and bursts in spillovers, and both turn out to be empirically important. In particular, in an analysis of sixteen global equity markets from the early 1990s to the present, we find striking evidence of divergent behavior in the dynamics of return spillovers vs. volatility spillovers: Return spillovers display a gently increasing trend but no bursts, whereas volatility spillovers display no trend but clear bursts. JEL Classification: F30, G15, F3

Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non-crisis and crisis episodes, including trends and bursts in spillovers, and both turn out to be empirically important. In particular, in an analysis of sixteen global equity markets from the early 1990s to the present, we find striking evidence of divergent behavior in the dynamics of return spillovers vs. volatility spillovers: Return spillovers display a gently increasing trend but no bursts, whereas volatility spillovers display no trend but clear bursts.Asset Market, Asset Return, Stock Market, Emerging Market, Market Linkage, Financial Crisis, Herd Behavior, Contagion