我国ETF跟踪误差比较及对策研究

文章以我国A股市场上全部5只ETF为研究对象,采用回归拟合和定量计算的计量方法,实证分析了ETF上市后的跟踪误差及业绩对比,认为ETF在牛市中的表现优于熊市,既而深入探讨跟踪误差产生及波动的成因,最后结合我国实情提出改善ETF跟踪绩效的建议。     

Do different time horizons in the volatility of the US stock market significantly affect the China ETF market?

This article investigates the linear, nonlinear and time-varying Granger causality between different time horizons in the volatility of US stock market and the China Exchange-Traded Fund (ETF) market. We find evidence of linear causality from the US stock market to the China ETF market, with a bilateral nonlinear causal relationship in the longer term. Bootstrap rolling causality analysis indicates high rejection rates of a noncausal relationship running from the US stock market to the China EFT market. The causality linkage from the China ETF market to the US stock market was determined to be time-horizon-dependent, and the null hypothesis rejection rate of non-Granger causality increased in the longer term.     

ETF产品组合与股指期货的复合期现套利机制研究

2010年4月16日股指期货上市交易,中国进入了金融期货时代。鉴于目前我国还没有推出沪深300ETF,针对股指期货的套利交易不能找到直接对应的现货。本文建造ETF组合最大限度地拟合沪深300期指现货,找到利用ETF组合和股指期货的最佳复合期现套利机制。     

Climate change shocks and socially responsible investments

Climate change's impact on investor behavior is a scantly investigated area in finance. This paper examines the performance of socially responsible exchange trade funds (ETFs) concerning conventional ETFs, in response to climate change events. We proxy climate change signals with a list of natural disaster events that NASA scientists relate to climate change. We contribute to existing literature, by using a very extensive information set of ETF strategies, not influenced by rating agencies' subjective evaluation policies, and covering almost 90% of the universe of worldwide sustainability thematic-oriented ETFs. This sample allows us to identify the socially responsible investment behavior in response to unpredictable climate change shocks. Our identification strategy accounts for endogeneity concerns and relies on two-stage least square (2SLS) approach finding that responsible investors react to climate change events by purchasing socially responsible investments. The relationship between climate change signals and return of investment in themes linked to the development of sustainability is positive. Interestingly enough, the sign of this relationship is different, when we disentangle the empirical results according to the asset type, confirming that investors shift their investments from equity funds to bond funds when market sentiment worsens. Our results indicate that policymakers should increase the support of firms adopting environmentally conscious business practices, while managers should boost a sustainable business strategy.     

Jump dynamics,spillover effect and option valuation

In this paper, we propose an affine discrete-time model that incorporates the jump process and spillover effect for valuing the 50 ETF options in China. Based on the proposed model, a closed-form solution is also derived for the new dynamics of underlying asset, which facilitates option pricing. The empirical results show that the proposed model offers greater economic benefit with reduced pricing errors than the traditional benchmark models, including the popular HNGARCH model of Heston and Nandi (2000), GARV model of Christoffersen et al. (2014), and BPJVM model of Christoffersen et al. (2015). Our finding is important for financial risk management and investment in Chinese derivatives market.     

Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market

This study examines the Chinese implied volatility index (iVIX) to determine whether jump information from the index is useful for volatility forecasting of the Shanghai Stock Exchange 50ETF. Specifically, we consider the jump sizes and intensities of the 50ETF and iVIX as well as cojumps. The findings show that both the jump size and intensity of the 50ETF can improve the forecasting accuracy of the 50ETF volatility. Moreover, we find that the jump size and intensity of the iVIX provide no significant predictive ability in any forecasting horizon. The cojump intensity of the 50ETF and iVIX is a powerful predictor for volatility forecasting of the 50ETF in all forecasting horizons, and the cojump size is helpful for forecasting in short forecasting horizon. In addition, for a one-day forecasting horizon, the iVIX jump size in the cojump is more predictive of future volatility than that of the 50ETF when simultaneous jumps occur. Our empirical results are robust and consistent. This work provides new insights into predicting asset volatility with greater accuracy.