我国ETF发展初探

本文简要介绍了ETF的定义与特征及其在我国的发展情况,包括其在我国产生的背景条件、现状与存在问题及其在我国的发展前景.     

股指期货的定价问题

中国金融市场即将推出沪深300股票指数期货。本文吸收和借鉴了国外的研究成果，深入探讨了股指期货的定价问题，包括什么是股指期货的定价模型、股指期货价格均衡的条件、无风险套利的实例分析、股指期货价格背离的原因以及为消除价格背离应采取的若干对策。经过充分的论证，本文明确提出了中国证券市场应尽快推出沪深300指数交易所交易基金（ETF），并适时引入股票卖空机制的建议。     

Neural network copula portfolio optimization for exchange traded funds

This paper attempts to investigate if adopting accurate forecasts from Neural Network (NN) models can lead to statistical and economically significant benefits in portfolio management decisions. In order to achieve that, three NNs, namely the Multi-Layer Perceptron, Recurrent Neural Network and the Psi Sigma Network (PSN), are applied to the task of forecasting the daily returns of three Exchange Traded Funds (ETFs). The statistical and trading performance of the NNs is benchmarked with the traditional Autoregressive Moving Average models. Next, a novel dynamic asymmetric copula model (NNC) is introduced in order to capture the dependence structure across ETF returns. Based on the above, weekly re-balanced portfolios are obtained and compared using the traditional mean–variance and the mean–CVaR portfolio optimization approach. In terms of the results, PSN outperforms all models in statistical and trading terms. Additionally, the asymmetric skewed t copula statistically outperforms symmetric copulas when it comes to modelling ETF returns dependence. The proposed NNC model leads to significant improvements in the portfolio optimization process, while forecasting covariance accounting for asymmetric dependence between the ETFs also improves the performance of obtained portfolios.     

基于上证50ETF期权的“定价核之谜”研究

基于上证50E T F和上证50E TF期权数据,本文经验研究了中国市场是否存在“定价核之谜”,并对“定价核之谜”与市场走势之间的关系进行了探讨。实证结果显示,中国市场存在“定价核之谜”,且“定价核之谜”与下期市场收益率呈显著负向关系、与下期市场振幅呈显著正向关系。本文首次给出了“定价核之谜”在中国金融市场存在的经验证据,并且证实了“定价核之谜”对下期市场走势具有一定的预测作用。     

Volatility index and the return–volatility relation: Intraday evidence from Chinese options market

We use unique intraday data to investigate the validity of the Shanghai Stock Exchange's the revised Chinese implied volatility index (iVX). We find that iVX is an effective barometer for the underlying exchange-traded fund (ETF) market and can be used as a valid “fear index” when there is anxiety over large drops. Furthermore, we use robust quantile regressions and document the asymmetric relation between returns and iVX changes. We also show that behavioral theories offer better explanations for this asymmetric relation than do fundamental theories. More important, we examine the role of iVX in selecting trading strategies.     

New Revolution in Fund Management: ETF/Index Design by Machines

ABSTRACT

Two ETFs were listed to track the secondary-battery industry on 12 September 2018 in the Korea Stock Exchange market. They are virtually identical except that one is designed by humans while the other is made by machines. This paper compares the two ETFs and find little difference in their investment strategies except that machines are more likely to pick high book-to-market stocks than humans. Machines are also more likely to pick past losers and outperform human-designed ETF afterwards. The results suggest that machines can do equally good as humans as ETF/index designers.     

套期保值定期动态调整策略的状态空间模型研究——基于沪深300股指期货对50ETF套期保值的实证

套期保值率的计算影响到套期保值效果,利用变参数状态空间模型及相关的动态调整策略,基于沪深300股指期货对50ETF做套期保值操作,研究结果证明:状态空间模型更能体现动态估计的特点,沪深300股指期货对50ETF有很好的套保效果;对于分散程度较高的上证50ETF应采用定期动态调整策略。     

ETF套利交易中股指期货套期保值理论与对策研究——基于光大证券“8·16乌龙”事件

作为资本市场上重要的基础金融衍生产品,股指期货为投资者应对市场风险提供了不可或缺的对冲工具。本文基于光大证券“8·16乌龙”事件,对ETF套利交易中股指期贷套期保值进行了文献综述和理论分析,最后提出ETF套利交易中股指期货套期保值的操作对策。     

基于时间序列GARCH(1,1)模型的上证50ETF波动率预测

波动率的研究是资产定价方面的一个重要研究方向,其中波动率估计准确与否直接关系到模型运用是否得当,投资的策略是否成立。对于股票、期权、期货、基金等金融资产进行波动率预测不仅是理论研究的重点对象,更是金融市场的热门话题。在1982年,Engle提出了ARCH模型这一想法,这为波动率的研究谱写了新的篇章。而之后在1986年,Bollerslev又在ARCH的基础上将历史波动率加进了ARCH模型中,进一步提出了GARCH模型这一设想,这更好地抓住了股票等金融资产收益波动的长记忆性。如今量化策略越来越普及,中国的金融市场逐渐发展,在2015年2月9日推出了具有划时代意义的上证50ETF期权,对于期权的推出,能够准确预测出作为标的物的上证50ETF波动率对于研究期权具有重大的帮助。文章利用最为普遍的GARCH(1,1)模型,分析从期权推出的那一刻起,到最近的2015年8月9日,整整六个月,123个日收盘价观察值进行实证分析,对上证50ETF进行波动率预测,第四部分为结论。     

Intraday Price Discovery in the DJIA Index Markets

Abstract:  This paper explores the dynamics of price discovery between the Dow Jones Industrial Average (DJIA) index and its three derivative products: the DIAMOND exchange-traded fund (ETF), the floor-traded regular futures, and the electronically traded mini futures. Even though the American Stock Exchange is the primary listing exchange for the ETF, the analysis indicates that the electronically traded ETF on the Archipelago (ArcaEx) electronic communications network dominates the price discovery process for DIAMOND shares. The E-mini futures contribute the most to price discovery, followed by the ArcaEx DIAMOND. The DJIA index and regular futures contribute least to price discovery. The analysis is repeated using the derivatives of the S&P 500 index as a robustness check. The results indicate that multi-market trading ensures greater pricing efficiency. Informed traders favor electronic trading because of immediate and anonymous trade execution.