我国燃油期货价格指数波动特征研究

通过选取上海期货交易所燃油期货价格指数5分钟高频收益数据,本文构造了经调整的已实现波动率估计序列,运用4类非线性GARCH模型建模分析,描述了中国燃油期货价格指数的波动特征,运用6种损失函数以及Diebold-Mariano 检验法,实证检验了4类GARCH模型对燃油期货价格指数波动的样本外预测能力。就中国燃油期货市场而言,基于高频数据的FIAPARCH模型,能够较好地描述中国燃油期货价格的波动特征,并且具有最为出色的波动率预测能力,而IGARCH模型在某些损失函数标准下也体现出了较好波动率预测能力。     

基于跳跃、好坏波动率的混频已实现EGARCH模型的波动率预测与风险度量

为探究资产价格的跳跃行为和收益波动的非对称效应对波动率预测的影响,以高频数据建模为视角,基于跳跃、好坏波动率将Realized EGARCH-MIDAS模型进行拓展,以提升模型的波动率预测能力与风险度量效果。运用拓展后的模型,以沪深300指数价格高频数据为样本进行实证分析,探究中国股票市场的波动性规律,并采用似然函数、信息准则和基于损失函数的DM与MCS等检验方法,综合比较了改进前后的模型对波动率及风险值的预测效果。实证结果显示：(1)沪深300指数收益的长期波动主要来源于连续波动而非跳跃波动,且受正连续波动影响更大,而负跳跃对波动具有明显的负向冲击;(2)文章提出的拓展模型均能更好地捕捉波动率的长记忆性,在样本内估计和样本外预测上也都有更好的表现,其中同时考虑跳跃与非对称影响的Realized EGARCH-MIDAS-RSJ拓展模型拥有最优的估计及预测效果。     

我国农产品期货市场波动率实例分析

本文以郑州商品交易所白糖期货15分钟高频价格数据为例,运用多种损失函数,以已实现波动率为模型评价衡量标准,实证检验了不同异方差模型对白糖期货价格波动的刻画能力。实证结果显示,就我国2006年1月6日推出的白糖期货而言,GJR模型具有最为出色的波动刻画精度,而在某些损失函数标准下,IGARCH模型也体现出了较好的波动刻画精度。     

基于高频数据的ARCH类模型波动预测比较分析

Realized Volatility是在高频数据的研究基础上发展起来的度量波动率的新方法。本文以上证综合指数的高频数据为研究对象,采用滚动式样本外一步预测的方法对5种ARCH类模型进行了模型预测能力的比较研究。主要结论有:(1)Realized Volatility作为解释变量加入GARCH模型后能够提高波动预测精度。(2)GARCH-RV的波动预测值为Realized Volatility的无偏估计量。(3)沪市存在波动非对称性与很长的持续性。     

基于赋权已实现波动率的股票市场VaR度量

近二十年来,学术界对高频金融数据波动率模型的研究已经成为一个热门.特别是最近十几年,Andersen等学者提出了用高频分时数据来估计波动率的方法,这种方法可以得到比较准确的波动率估计值,称为“已实现”波动率,其中ARFIMA-RV是一类非常重要的波动率预测模型.本文在高频金融数据的基础上建立了赋权已实现波动率模型,发现其具有长记忆性,并通过建立对数赋权已实现波动率的分整自回归移动平均模型(lnWRV-ARFIMA)对赋权已实现波动率进行了拟合和预测.最后介绍了赋权已实现波动率在风险价值度量中的重要应用,并基于赋权已实现波动率,给出了风险价值的计算方法.     

基于GARCH类模型对美国股市波动性的对比分析

为研究美国股市股指的波动性特征,本文选取美国股市的Nasdaq指数和Russel2000指数的日收盘价数据,借助统计软件,利用GARCH类模型进行实证分析。实证结果表明：Russel2000指数的风险较Nasdaq指数更稳定,更适合投资,且相较GARCH(1,1)模型,满足学生t分布的APARCH(1,1)模型拟合的条件异方差可以更好地反映种股指日对数收益率的波动率情况,因此可选用此模型对两种指数波动率的未来值进行预测,为投资者提供未来投资参考。     

基于灰色组合模型的河南GDP预测

为解决GM(1,1)预测中存在的历史数据的跳变问题,依据灰色灾变预测原理,利用线性回归适用短期预测的特点,提出了一种新的预测方法:用GM(1,1)模型预测将来可能的数据跳变日期点,对其他非跳变点使用分段线性回归函数进行预测。通过对河南省生产总值的预测,结论显示出此种方法较好地克服GM(1,1)模型和线性回归模型的缺陷,在现实中达到较好的成效。     

我国社会消费品零售总额的预测分析——基于最小二乘法的改进GM(1,1)模型

我国社会消费品零售总额受到诸多因素的影响,导致数据波动性较大,单纯地采用灰色预测模型无法更加准确地进行预测,因此本文提出了基于最小二乘法的改进GM(1,1)模型,首先介绍了普通GM(1,1)模型的建立方法与步骤;接着通过采用最小二乘法的原理弱化波动较大的数据,加强其规律性从而建立新的GM(1,1)模型;最后结合2007²011年我国社会消费品零售总额数据建立新的预测模型,并用2012年数据对模型进行验证合格,可以用来预测未来几年我国社会消费品零售总额,便于我国对未来社会消费品宏观调控。结果表明该预测方法是合理可行的,为其他相关预测提供了理论依据。     

基于SVR-GARCH的货币波动率预测研究——以加密货币和传统货币为例

货币价格波动率的建模和预测一直以来都是国家和企业层面重要的研究内容。文章使用加密货币和传统货币的分频汇率数据构建SVR-GARCH模型,为波动率的预测引入非线性交互,提高了模型的预测精度和泛化能力。此外,进一步构建了DCC-SVR-GARCH模型探讨加密货币与传统货币之间的关联性。实证结果表明：首先,在预测方面,机器学习算法的引入显著增强了模型预测性能,SVR-GARCH模型在低频和高频数据上均有稳健的预测表现。其次,加密货币波动率的特征较传统货币更为明显,两者间具有某种同步性,并进一步验证了其存在。最后,两者波动率的关联性表现为：在高不确定性时期呈现正相关关系,且具有明显的事件驱动性;在低不确定性时期往往是负相关关系。     

基于灰色模型与BP神经网络的青岛旅游需求预测模型

本文主要研究青岛市旅游需求预测的有关问题。本文首先对搜集的数据进行无量纲化处理,利用主成分分析得到影响旅游需求的主成分,以旅游人口建立GM(1,1)模型,进而将模型推广到GM(1,N)模型,并进行残差检验确保其可靠性;其次,对影响旅游需求的因素进行GM(1,1)灰度预测,并利用预测数据建立BP神经网络模型对GM(1,1)模型进行优化改进,最后,分析得到运用BP神经网络模型进行预测的结果更为准确。     

The predictability of carbon futures volatility: New evidence from the spillovers of fossil energy futures returns

In this paper, we find new evidence for the carbon futures volatility prediction by using the spillovers of fossil energy futures returns as a powerful predictor. The in-sample results show that the spillovers have a significantly positive effect on carbon futures volatility. From the out-of-sample analysis with various loss functions, we find that fossil energy return spillovers significantly outperform the benchmark and show better forecasting performance than the competing models using dimension reduction, variable selection, and combination approaches. The predictive ability of the spillovers also holds in long-term forecasting and does not derive from other carbon-related variables. It can bring substantial economic gains in the portfolio exercise within carbon futures. Finally, we provide economic explanations on the predictive ability of the fossil energy return spillover by the channels of the carbon emission uncertainty and the investor sentiment on the warming climate.     

Managed futures,positive feedback trading,and futures price volatility

A major issue in recent years is the role that large, managed futures funds and pools play in futures markets. Many market participants argue that managed futures trading increases price volatility due to the size of managed futures trading and reliance on positive feedback trading systems. The purpose of this study is to provide new evidence on the impact of managed futures trading on futures price volatility. A unique data set on managed futures trading is analyzed for the period 1 December 1988 through 31 March 1989. The data set includes the daily trading volume of large commodity pools for 36 different futures markets. Regression results are unequivocal with respect to the impact of commodity pool trading on futures price volatility. For the 72 estimated regressions (two for each market), the coefficient on commodity pool trading volume is significantly different from zero in only four cases. These results constitute strong evidence that, at least for this sample period, commodity pool trading is not associated with increases in futures price volatility. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 759–776, 1999     

Foreign exchange futures volatility: Day-of-the-week,intraday, and maturity patterns in the presence of macroeconomic announcements

Using standard deviations and numbers of price changes calculated from tick data for currency futures, this study finds strong day-of-the-week effects for both the Deutsche mark and Japanese yen, mild effects for the British pound, and no effects for the Canadian dollar after controlling for scheduled macroeconomic announcements and days to contract expiration. The day-of-the-week effects are found to be caused either by Mondays’ low volatility, or by Thursdays’ or Fridays’ high volatility. This result suggests that the day-of-the-week effects in the currency futures are not driven by the announcements of macroeconomic indicators as proposed in previous studies, but rather by other factors, such as private information-based trading or by market microstructure. This study also finds that the announcements are processed equally across the days of the week for all four currency futures. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 665–693, 1999     

Pricing Eurodollar Futures Options with the Heath—Jarrow—Morton Model

This article uses the algorithm developed by Ritchken and Sankarasubramanian (1995) to make comparisons among the Heath—Jarrow—Morton (HJM) models (Heath, Jarrow, & Morton, 1992) with different volatility structures in pricing the Eurodollar futures options. We show that the differences among the HJM models as well as the difference between the HJM models and Black's model can be insignificant when the volatility of the forward rate is relatively small. Moreover, our findings imply that the difference between the American‐style and European‐style options is insignificant for options with a life of less than 1 year. However, the difference can be significant for options with a 1‐year maturity, the difference depending on the exercise price. Finally, our tests indicate that the difference between the forward price and the futures price is insignificant if the volatility parameter is low enough and when the volatility of the spot rate is proportional to the spot rate. A higher volatility parameter can lead to a significant difference between the forward price and the futures price, although its impact on the price of the options will still be trivial. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21: 655–680, 2001     

我国期货市场的波动性与有效性--基于三大交易市场的实证分析

通过对中国三大期货市场的铜、黄豆和小麦三种主要期货品种收益率的分布与波动性的实证分析 ,论证了其时间序列存在ARCH效应 ;运用GARCH模型对这三种期货品种进行了拟合分析和统计检验 ,检验结果表明这三个期货品种的波动性均具有很高的持续性 ,但大连黄豆的波动持续性弱于上海铜和郑州小麦 ,其波动性受各种外部冲击的影响较大 ;通过GARCH( 1 ,1 )的市场有效性检验 ,论证了中国期货市场尚未达到弱式有效 ,市场风险较大。     

Price discovery and volatility spillovers in the DJIA index and futures markets

The Dow Jones Industrial Average (DJIA) is the most widely quoted stock index worldwide. This article examines the minute-by-minute price discovery process and volatility spillovers between the DJIA index and the index futures recently launched by the CBOT. The Hasbrouck (1995) cointegrating model suggests that most of the price discovery takes place at the futures market. However, by examining the volatility spillovers between the markets based on a bivariate EGARCH model, a significant bidirectional information flow is found. That is, innovations in one market can predict the future volatility in another market, but the futures market volatility-spillovers to the stock market more than vice versa. Both markets also exhibit asymmetric volatility effects, with bad news having a greater impact on volatility than good news. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 911–930, 1999     

An N‐factor Gaussian model of oil futures prices

This article studies the ability of an N‐factor Gaussian model to explain the stochastic behavior of oil futures prices when estimated with the use of all available price information, as opposed to traditional approaches of aggregating data for a set of maturities. A Kalman filter estimation procedure that allows for a time‐dependent number of daily observations is used to calibrate the model. When applied to all daily oil futures price transactions from 1992 to 2001, the model performs very well, requiring at least three factors to explain the term structure of futures prices, but four factors to fit the volatility term structure. The model also performs very well for daily copper futures transactions from 1992 to 2001 and for out‐of‐sample daily oil futures transactions from 2002 to 2004. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:243–268, 2006     

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     

Pricing VIX futures: Evidence from integrated physical and risk‐neutral probability measures

This study derives closed‐form solutions to the fair value of VIX (volatility index) futures under alternate stochastic variance models with simultaneous jumps both in the asset price and variance processes. Model parameters are estimated using an integrated analysis of integrated volatility and VIX time series from April 21, 2004 to April 18, 2006. The stochastic volatility model with price jumps outperforms for the short‐dated futures, whereas additionally including a state‐dependent volatility jump can further reduce out‐of‐sample pricing errors for other futures maturities. Finally, adding volatility jumps enhances hedging performance except for the short‐dated futures on a daily‐rebalanced basis. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:1175–1217, 2007     

The Costs of Arbitrage and Futures Market Trading Activity

Abstract Standardizing a futures contract’s specifications to enhance its transfer-ability is problematic for any commodity whose cash market adopts relational contracting procedures. Standardization implies the contract’s value cannot be completely determined by competitive arbitrage order flow, inhibiting the market’s price discovery function, and leaving the futures price susceptible to manipulation. These effects may result in the market’s failure. The model, based on the theory of storage, predicts that contracts with a higher spread-open position price volatility are more likely to contain a range of arbitrage indeterminacy, hence to experience difficulties in sustaining trading. The prediction is supported in an empirical examination of 104 US futures markets. The range of indeterminacy also increases the informational requirements of spread traders, reducing the effectiveness of spread arbitrage in maintaining the equilibrium intertemporal futures pricing relationship. Detailed evidence from 15 US contract markets demonstrates spread arbitrage is less effective in contract markets which subsequently fail.