上证50ETF和上证180ETF跟踪误差的比较分析

上证50ETF和上证180ETF无论从指数编制还是从指数特征来看都极其相似,因此本文拟选择上证50ETF和上证180ETF作为实证研究对象,通过三种方法,实证分析了两者对其目标指数即上证50指数和上证180指数的跟踪误差状况,并在两者比较分析的基础上探讨造成上证50ETF和上证180ETF之间的跟踪误差不同的原因。     

上证红利ETF跟踪误差实证分析

交易型开放式指数证券投资基金(ETF)投资目标是跟踪复制标的指数收益与风险,所以在分析ETF基金投资绩效时跟踪误差的分析对ETF收益显得格外重要.目前我国上市的ETF中比较活跃、有代表性的有上证50ETF、上证180ETF、深圳100ETF、上证红利ETF、深圳中小板ETF,由于许多文章都通过抽样数据对前三种ETF进行了比较多的研究分析,所以本文以上证红利ETF为研究对象,通过运用数据定量的方法对其进行分析.     

ETF投资功能分析

ETF是"交易型开放式指数证券投资基金"(Exchange Traded Fund,以下缩写ETF)的简称,又称"交易所交易基金",它跟踪"标的指数"的变化且在证券交易所上市交易,其交易价格、基金份额净值走势与所跟踪的指数基本一致,基金份额用组合证券进行申购、赎回.ETF是近年来全球市场发展最迅速的金融产品之一,自1993年推出至今总资产规模达到3600亿美元.国内首只ETF产品--华夏上证50ETF于2005年2月设立,2006年,深圳100ETF、上证180ETF又接连发行.ETF为什么有如此强大的生命力?本文结合ETF产品特征和交易机制,对ETF的主要投资功能进行分析探讨.     

ETF跟踪误差实证分析

ETF自1993年在美国推出后,迅速在美国乃至全球发展起来。ETF是一种指数化投资基金,而指数化投资基金运行业绩的一个重要的指标是追踪误差。本文将对中国市场上目前交易的四支基金上证50ETF、深证100ETF、上证180ETF和中小板ETF的追踪误差进行实证分析,并对这四支ETF的投资业绩给予综合的评价。     

ETF跟踪误差实证分析

ETF自1993年在美国推出后,迅速在美国乃至全球发展起来.ETF是一种指数化投资基金,而指数化投资基金运行业绩的一个重要的指标是追踪误差.本文将对中国市场上目前交易的四支基金上证50ETF、深证100ETF、上证180ETF和中小板ETF的追踪误差进行实证分析,并对这四支ETt的投资业绩给予综合的评价.     

上证180指数ETF套利研究

金融创新商品为投资人增加了投资、投机、套利和避险等交易工具。上海证券交易所今年推出以上证180指数为标的的交易所交易基金(ETF)的可能性很大。在没有推出以上证180指数和ETF衍生金融工具的情况下,EIF二级市场价格与基金净值之间的套利是涉及ETF唯一的一种套利。我们对这种套利进行研究,为机构投资者捕捉其中的套利机会提供参考。     

上证180指数对标的股票流动性的影响

上证180指数的成立事件对不同的流动性指标有相反的效果：一方面促进了成分股价差水平和交易信息对称程度的改善，另一方面又促使交易深度水平和交易活跃性的降低。这些流动性效应是由于机构投资者对上证180成分股偏好所造成的，机构投资者增加了上证180成分股的需求的同时减少了供给，导致了交易深度和活跃性的降低。机构投资者作为相对知情交易者，它们的偏好增加了市场的需求竞争程度，从而降低了交易者之间的信息不对称程度以及改善了市场价差水平。本文还建议创立上证180指数ETF，因为根据国外的经验，ETF可以有效地增强市场交易深度，从而弥补上证180指数在市场交易深度方面的负面影响。     

ETF苦乐不均 流动性成生命线

新年伊始,黄金ETF国债ETF渐行渐近.ETF基金为资本市场的活跃起着非常重要的作用.而在刚刚过去的2012年,ETF产品开发得到了突破性提升,股市回暖也创造了不少交易机会,全年ETF市场迅速扩张.据银河证券统计,截至2012年12月31日,ETF资产净值规模占公募基金的比例为5.61％,较2011年上升2.09个百分点;从指数基金的构成看,ETF的资产净值规模占指数基金的35.99％,2011年、2010年的占比分别为25.33％、20.85％,占比快速提升. 千亿成交量是大型ETF的标志.2012年有3只ETF的成交量突破千亿,它们是——易方达深证100ETF、华夏上证50ETF和华泰沪深300ETF.其中,老牌的深证100ETF和上证50ETF均已是连续4年成交额突破千亿.     

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。     

离差交易的实证研究与探讨

离差策略是一种对冲交易策略，它是利用股指期权和一揽子股票期权（或部分成分股构成的ETF期权）之间的隐含相关系数，获悉市场成分股期权和股指期权波动率高低的相对关系，再在成分股期权和股指期权建立相反的头寸。离差交易策略选择暴露的风险因子就是隐含相关系数，离差交易使用的是对冲的平价跨式期权交易。选用2006年5月18日至2014年7月17日前复权的沪深300股指、上证50指数和上证180指数作为样本，进行实证检验。虽然结果显著性较强，但不排除存在模型不稳定性以及由于数据不充分造成对相关系数及波动率估计的偏误。同时，离差交易使用的是对冲的平价跨式期权交易，所以组合暴露较小的Delta风险。若离差交易涉及较大的资金量时，则需要用标的资产对组合进行动态Delta中性对冲。     

A comprehensive study on smart beta strategies in the A-share market

In this article, we explore how smart beta strategies are applied in the Chinese A-share market. Specifically, we empirically examine several popular smart beta strategies, including mean-variance optimization, minimum-variance portfolio, equal weighting, risk parity strategy, and fundamental indexation, and we do so using the Shanghai Stock Exchange (SSE) 50 index and SSE sector indices as our comparison benchmarks. We find that all smart beta strategies outperform these benchmarks from year 2006 to year 2015, and that all smart beta strategies outperform the SSE 50 index by an average of 2.57% per year. In turn, these strategies improve the Sharpe Ratio by 46.2% on average.     

An analysis of the spillover effects of exchange-traded funds

This article used the Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (GARCH-ARMA) and the exponentially Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (EGARCH-ARMA) models to study the impact of the spillover and the leverage effects on returns and volatilities of stock index and Exchange Trade Fund (ETF) for developed and emerging markets. Previous unexpected returns for developed and emerging markets which have an opposite influence pattern on ETFs’ returns were identified. The spillover effects from returns are excellent for Hong Kong, followed by Singapore. Meanwhile, Taiwan's stock index return was recorded to have a strong negative impact on ETF return. Notably, this article shows that the spillover effects on stock index and ETF volatilities existed with bilateral influences. Despite a strong positive asymmetric volatility effect in Korea's ETF market, the leverage effect appears to play important roles in the explanation of both stock index and ETF returns.     

Short selling and exchange-traded funds returns: evidence from the London Stock Exchange

An exchange-traded fund (ETF) is a security that tracks a basket of stocks. An ETF investor gains immediate exposure to the basket, by taking either a long or short position on this instrument. Both hedgers and speculators can short ETFs, making the informational content of increases in ETF short interest difficult to interpret. Using high-frequency (daily) short-interest data for ETFs traded on the London Stock Exchange between June 2006 and April 2010, we examine the price impact on ETFs of increases in short interest. Contrary to most of the previous empirical evidence for individual stocks, we find that large increases in ETF short interest are associated with subsequent over-performance relative to a benchmark index and this pattern is most pronounced during pre-financial crisis period.     

Robustness of sunspot equilibria

Summary. A sunspot equilibrium (SSE) is based on some extrinsic randomizing device (RD). We analyze the robustness of SSE. (1) We say that an SSE allocation is robust to refinements if it is also an SSE allocation based on any refinement of its RD. (2) We introduce two core concepts for analyzing the robustness of SSE in the face of cooperative-coalition formation. In the first, the blocking allocations are based on the RD that defines the SSE. In the second (stronger) core concept, coalitions select their own RDs. For the convex economy with restricted market participation, SSE allocations are robust under each of the definitions and the cores converge on replication of the economy to the set of SSE allocations. For the economy with an indivisible good, SSE allocations are not always robust. We provide examples of each of the following: (i) an SSE allocation that is not robust to refinement, (ii) an SSE allocation that is in neither core, (iii) an SSE allocation that is in the first core, but not in the second, and (iv) a core that does not converge upon replication to the set of SSE allocations. Received: July 31, 1995; revised version August 30, 1996     

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.     

Investment performance of shorted leveraged ETF pairs

We analyze investment strategies involving triple-leveraged and inverse triple-leveraged ETF pairs by simulating daily returns over a 48-year period. Our results show that many such strategies significantly outperform the S&P 500 on a risk-adjusted basis. For example, when shorting the bear triple-leveraged ETF and the bull triple-leveraged ETF in a 2:1 proportion (while going long Treasuries), we find that the average annual Sharpe ratio is more than four times higher than for the S&P 500 and that the strategy outperforms the S&P 500 in 43 of the 48 years. Our results are robust to variations in bear/bull proportions, rebalance thresholds, and underlying parameters.     

The heterogeneous volume-volatility relations in the exchange-traded fund market: Evidence from China

We decompose the trading volume of exchange-traded funds (ETFs) into specific components according to different triggers of trades: (i) private information, (ii) disagreement among investors due to their different opinions on public information or having different information, and (iii) investor impatience. Then we examine the particular impact of each type of ETF trade on the market volatility of the tracked index. Focusing on the three ETFs tracking the CSI 300, we show that ETF trades stemming from investor disagreement are a key determinant of CSI 300 volatility, dominating other factors considered. Liquidity ETF trades can partially explain CSI 300 volatility. However, little evidence supports a significant correlation between privately informed trades of ETFs and CSI 300 volatility.     

Modelling the implied volatility surface based on Shanghai 50ETF options

We develop a dynamic factor model to forecast the implied volatility surface (IVS) of Shanghai Stock Exchange 50ETF options. Based on the assumption that dynamic change in IVS is mean-reverting and Markovian, we use a state space model to capture the dynamics of IVS, and set the latent factors to be the Ornstein–Uhlenbeck processes. We obtain the optimal estimations of parameters using the Kalman filter algorithm. Empirical results show that our model performs better than the traditional IVS model in terms of fitting ability and prediction performance.     

噪声交易与市场渐进有效性

投资者的非理性行为在市场渐进有效的进程中扮演了怎样的角色-现有文献并没有给出直接的研究和明确的结论.本文对上证50指数所代表的子市场的噪声交易情况进行了度量,同时构建状态空间方程并采用Kalman滤波法测度了该市场的渐进有效性,进而研究投资者噪声交易对我国市场渐进有效性的水平及其波动的影响.研究发现,我国市场整体上趋于有效,噪声交易的平均水平在各时期比较平稳;噪声交易会起到微弱的降低市场有效性水平的作用,增加渐进有效性的短期波动,但是从长期看并不能影响市场趋于有效的趋势.本文结论说明,投资者的非理性行为并不是造成我国资本市场非有效的根本原因,但是非理性行为也在短期内给市场的有效性进程造成阻滞.     

Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S.

We propose three Realized-GARCH-Kernel-type models which do not make the distribution assumptions on the return disturbance terms. We use this type of model to predict the return volatilities of the 50ETF in China and the S&P500 index in the U.S. The semiparametric kernel density estimator of our models, which captures the skewness, asymmetry and fat-tail of financial assets, performs well both statistically and economically. Our models have more predictive power than other eight comparable volatility models that need to pre-specify the distribution of the disturbance terms. Our results are robust to eight measures of realized volatility. Using option straddle strategies, we show that our models generate larger trading profits and greater Sharpe ratios than the other competing models.