组合预测模型在股指短期预测中的应用——以上证综合指数为例的实证分析

本文分析了自回归移动平均模型(ARIMA)与BP神经网络模型在预测方面的特性和模型各自的优缺点,在此基础上尝试建立了ARIMA和BP神经网络的股指组合预测模型。ARIMA与BP神经网络组合使用的基本原理是股指时间序列数据可分解为线性部分和非线性残差部分。本文以上证综合指数为例,首先采用ARIMA预测上证综合指数的线性变化趋势,然后采用BP神经网络对上证综合指数的非线性趋势进行拟合,最后整合两种模型的预测结果。仿真结果表明:组合模型提高了对上证综合指数的预测精度,证实了组合模型在股指预测方面的有效性。     

浅谈GARCH模型下股指期货和股票市场的波动性关系

对于沪深300股指期货来讲,近些年来,日益受到关注和青睐,本文主要以2005年4月8日至2011年9月13日沪深300指数收盘价为关键性的时间点,总共选取的数据样本为1606个,来试图对股指期货在上市运行之后,所能够对现货市场的波动性产生的实际影响进行分析,在此研究目标之上,本文主要采用了计量经济学的方式,来对股票指数的波动性特征以及在股指期货推出之后所能够对指数波动产生的影响进行了实证分析,通过GARCH模型的建立,体现了我国股市波动性的具体实际情况。     

沪深300指数的ARCH效应

股价指数的收益率序列具有时变波动性、厚尾特征、波动性群集等特点,传统的计量分析无法刻画这些特点。通过对即将推出的股指期货的标的指数-沪深300指数的收益率序列进行AR-CH效应分析．采用ARCH模型及其扩展形式对沪深300指数的波动性进行实证分析,结果表明沪深300指数的收益率序列是有偏的,并具有尖峰厚尾的特点。同时也具有波动的群集性和不对称性的特点。     

我国股指期货收益波动预警的实证分析

本文介绍了股指期货概念及MS-GARCH模型,选择沪深300指数期货从2011年4月16日到2014年7月22日的样本数据,利用MS-GARCH模型进行实证分析,对其对数收益率波动预警序列不符合正态假定,通过模型结果显示,其在收益率序列的波动预警特征上有更强的说服力和解释力。     

基于多维动态模型的中国股指相关性预测研究

运用时间序列的ADCC(Asymmetric Dynamic Conditional Correlation)多维GARCH模型和CCC(Constant Conditional Correlation)多维GARCH模型对中国主要股指之间的相关性进行预测,并对预测结果进行评价和比较,结果表明ADCC多维GARCH模型拟合和预测中国股指相关性较好,这为投资组合管理和风险管理提供了理论支持。     

基于波动阶段划分的我国期铜市场长期记忆性实证研究

金融市场通常由于波动结构性突变的存在而出现伪长记忆性现象。运用ICSS算法寻找方差突变点进行阶段划分，运用V／S分析法对我国期铜市场波动阶段前后的长期记忆性进行检测和比较，并利用FIGARCH模型对波动序列的长期记忆性进行建模估计。研究结果表明，我国期铜市场存在全程长期记忆性；阶段划分后序列的长期记忆性显著降低；期铜波动的FIGARCH模型具有更优的拟舍效果和预测能力。     

期货和期权市场与中国股票市场波动关联研究

股指期货和期权作为衍生产品的一种,对股票市场的波动性有着很大的影响。股指期货和期权对现货市场的波动性既有放大的"杠杆"效果,又有"对冲"的效果。那么股指期货和期权对现货市场的影响实际上是怎么样的仍需要进一步验证。本文从理论和实证分析对上面议题进行了研究。使用了GARCH模型和加入了一个虚拟的哑变量来研究股指期货和期权推出前后股票市场指数的波动率是否有改变。本文得出的结论是,无论是沪深300指数,上证50指数还是中证500指数,在它们相对应的股指期货或期权推出之后的很长时间之内,股票指数的波动性确实是降低的。另外,这个证据也有力地表明,股指期权期货的推出在中国是成功的,对市场是起到"稳定"的作用的。     

股指期货推出对现货市场价格影响探讨

以我国沪深300股指期货以及期货标的物沪深300指数的数据作为研究样本,以股指期货正式推出时间(2012年4月)为分割点,结合ARCH、GARCH、EGARCH、TGARCH模型,对比分析了股指期货推出前后30个月的现货市场的波动性、丛聚效应、杠杆效应,得出以下结论:我国股指期货的推出对现货市场有着积极的影响,表现在现货市场的波动率有所下降,丛聚性现象得到一定的缓解,杠杆效应有所减弱。     

基于GARCH变点模型的上证收益率伪波动持续性研究

股指收益率序列具有时变性,其波动特征可由GARCH模型来反映,若忽视了序列的结构性变点进行建模分析,所得到的结果不仅在精度上有问题,而且也会导致伪波动持续性。通过利用ICSS算法,结合具体历史背景,检测并确定了2005年～2009年的上证股指收益率的3个变点。通过分段建模,所得的结果不仅消除了伪波动性,而且也反映了波动的其他特征。     

股指期货与股票市场波动性关系的实证研究

以日本的N225指数期货、韩国KOSPI200指数期货和我国台湾地区证交所加权指数(TWSE)期货作为样本,通过GARCH模型的序列建模,从样本总体和分阶段子样本分别对其股指期货推出与股票市场波动性的关系进行实证检验。结果表明,台湾地区的股票市场引入股指期货后现货市场的波动性并未受到影响,而日本和韩国股票市场在引入股指期货之后其波动性加剧,但这种波动性的加剧仅仅是短期性的,长期内并无影响。     

Does Index Futures Trading Reduce Volatility in the Chinese Stock Market? A Panel Data Evaluation Approach

This study investigates the effect of introducing index futures trading on the spot price volatility in the Chinese stock market. We employ a recently developed panel data policy evaluation approach (Hsiao, Ching, and Wan, 2011) to construct counterfactuals of the spot market volatility, based mainly on cross‐sectional correlations between the Chinese and international stock markets. This new method does not need to specify a particular regression or a time‐series model for the volatility process around the introduction date of index futures trading, and thus avoids the potential omitted variable bias caused by uncontrolled market factors in the existing literature. Our results provide empirical evidence that the introduction of index futures trading significantly reduces the volatility of the Chinese stock market, which is robust to different model selection criteria and various prediction approaches. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 33:1167–1190, 2013     

Effects of monetary policy news on financial assets: Evidence from Brazil on a bivariate VAR-GARCH model (2006–17)

The impact of news releases related to the inflation targeting regime on the financial market is analyzed by estimating a bivariate VAR GARCH-BEKK-in-mean model. We use daily data, from January 2006 to May 2017, of stock prices index (IBOVESPA), exchange rate (BRL/USD) and interbank deposit rate (DI360). We developed a positive and negative news index to measure the impact of news releases based on Caporale et al. (2016) and Caporale et al. (2018). Although the literature on the subject is vast, this paper fills relevant gaps in three ways. First, we investigate the bidirectional relationship between monetary policy related news releases and the behavior of asset prices before and after the 2008 crisis in Brazil. Second, we consider the relationship between the second moments of the variables of interest, using the conditional volatility as a proxy for uncertainty. Third, we provide a time series approach to measure the effect of macroeconomic related news releases on financial asset returns. The results indicate there are mean spread effects from news for the exchange rate and the Brazilian stock index: (i) the GARCH-in-mean parameter is statistically significant for positive and the difference of news for the DI360; (ii) monetary policy and external shocks are statiscally significant as expected with exception of the external shocks for the Brazilian stock index; and (iii) there are volatility spillovers and changes of this volatility after the crisis for stock index and DI360.     

绿色指数发布的股价效应研究——基于投资者情绪的视角

近年来，承载着引导资金投向等多项使命，各类绿色指数相继发布，然而绿色指数是否真的对市场产生了影响有待验证。文章以2017-2019年绿色领先类公司股票数据为样本，采用事件研究法分析绿色指数发布后样本公司收益率的变化,借以探究绿色指数发布的股价效应。实证结果表明：在短期内，绿色指数发布对样本公司股价影响显著，指数发布后，公司的异常收益率在整体上显著为正。而长期来看，该股价效应不具备持续性，平均异常收益率会在长期回落。进一步，文章基于投资者情绪的视角，对该股价效应背后的影响机制做出了梳理。研究结果表明，绿色指数发布后，投资者情绪明显高涨，并且这种情绪对事件日后的异常收益有显著的正向影响。文章的研究为评价绿色指数发布的影响提供了良好的参考，同时对于内在机制的挖掘在一定程度上弥补了既有研究的不足。     

中美证券市场信息扩散速度比较研究

本文利用信息传播速度模型讨论证券市场信息的有效性。发现在上海证券交易市场上信息传播速度对上证指数条件波动率的影响具有随时间变化逐渐扩大的趋势,而在纽约证券交易市场上信息传播速度对道琼斯指数条件波动率的影响相对稳定。表明上海证券市场消化新信息的效率明显低于纽约证券市场。实证结果较好地刻画了中美证券市场信息流动的基本特征。     

隐含波动率的信息含量及其在我国的应用

国内现有关于波动率的研究多集中于时间序列模型,忽略了另一类预测波动率的方法即隐含波动率法。文章在回顾、评述了国内关于波动率的研究后,对国外关于隐含波动率的研究进行了梳理,为在我国大陆地区发展股指期权市场、通过提高期权市场的效率,以运用隐含波动率法更好地预测波动率提供了理论基础和政策建议。     

中国股市：迈上高位平台后的新征程——2006年回顾与2007年展望

2006年，中国股市出现了具有历史意义的重要转折，上证综指最终报收于2675点，全年上涨幅度高达130．43％。在此背景下，证券投资基金和证券公司的发展呈现新的转机，上市公司改革深化取得新的进展。2007年，中国股市还将维持牛市走势，但上升幅度将明显低于2006年，同时，股市风险将明显高于2006年。要支持股市长期走好，需要积极推进多层次市场体系的建立、进一步强化市场监管、推进监管机制的转换和股票市场的制度体系完善。     

TIME‐CHANGED MARKOV PROCESSES IN UNIFIED CREDIT‐EQUITY MODELING

This paper develops a novel class of hybrid credit‐equity models with state‐dependent jumps, local‐stochastic volatility, and default intensity based on time changes of Markov processes with killing. We model the defaultable stock price process as a time‐changed Markov diffusion process with state‐dependent local volatility and killing rate (default intensity). When the time change is a Lévy subordinator, the stock price process exhibits jumps with state‐dependent Lévy measure. When the time change is a time integral of an activity rate process, the stock price process has local‐stochastic volatility and default intensity. When the time change process is a Lévy subordinator in turn time changed with a time integral of an activity rate process, the stock price process has state‐dependent jumps, local‐stochastic volatility, and default intensity. We develop two analytical approaches to the pricing of credit and equity derivatives in this class of models. The two approaches are based on the Laplace transform inversion and the spectral expansion approach, respectively. If the resolvent (the Laplace transform of the transition semigroup) of the Markov process and the Laplace transform of the time change are both available in closed form, the expectation operator of the time‐changed process is expressed in closed form as a single integral in the complex plane. If the payoff is square integrable, the complex integral is further reduced to a spectral expansion. To illustrate our general framework, we time change the jump‐to‐default extended constant elasticity of variance model of Carr and Linetsky (2006) and obtain a rich class of analytically tractable models with jumps, local‐stochastic volatility, and default intensity. These models can be used to jointly price equity and credit derivatives.     

Pricing corporate bonds in Brazil: 2000 to 2004

This paper analyzes the factors that influence the issuing price of debentures in Brazil in the period from year 2000 to 2004, applying a factor model, in which exogenous variables explain return and price behavior. The variables in this study include: rating, choice of index, maturity, country risk, basic interest rate, long-term and short-term rate spread, the stock market index, and the foreign exchange rate. Results indicate that the index variable, probability of default and bond's maturity influence pricing and points out associations of long-term bonds with better rating issues.     

Markov switching GARCH models of currency turmoil in Southeast Asia

This paper analyzes exchange rate turmoil with a Markov switching GARCH model. We distinguish between two different regimes in both the conditional mean and the conditional variance: “ordinary” regime, characterized by low exchange rate changes and low volatility, and “turbulent” regime, characterized by high exchange rate devaluation and high volatility. We also allow the transition probabilities to vary over time as functions of economic and financial indicators. We find that real effective exchange rates, money supply relative to reserves, stock index returns, and bank stock index returns and volatility contain valuable information for identifying turbulent and ordinary periods.