Mean Reversion and the Comovement of Equilibrium Spot and Futures Prices: Implications from Alternative Data‐Generating Processes

The comovements of spot and futures prices are characterized by six binary variables, including the term structure curvature of futures prices. These variables are used to uniquely identify 48 possible comovement patterns. Among them, 24 cases are associated with mean reversion, which is defined as a state when spreads between futures and spot prices are shrinking. These pattern frequencies are then calculated on a daily basis with the futures prices of 10 commodities, including precious metal, agricultural, and financial commodities. The results are further compared to simulation output from three data‐generating processes: a bivariate pure random walk, a mixed random walk with first‐order autoregression (AR(1)), and an error‐correction representation. The mean‐reverting frequencies for all 10 commodities are about 50%. Around half of the time, spot and futures prices are moving toward each other, and the rest of the time they move in the same direction. The symmetry of these results implies that the existence of substantial shocks originated from futures markets; thus, this is consistent with the risk premium view of futures trading. Also, although all simulation models produce similar mean‐reversion frequencies, the patterns of comovements of spot and futures prices are different, and the price dynamics depend heavily on whether the market is dominant contango or backwardation. Furthermore, the error‐correction model outperforms the random‐walk model for agricultural commodities, and the mixed random walk with AR(1) is hardly distinguishable from the pure random walk. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:769–796, 2001     

A Microeconomic Approach to Diffusion Models For Stock Prices

This paper studies a class of diffusion models for stock prices derived by a microeconomic approach. We consider discrete-time processes resulting from a market equilibrium and then apply an invariance principle to obtain a continuous-time model. the resulting process is an Ornstein-Uhlenbeck process in a random environment, and we analyze its qualitative behavior. In particular, we provide simple criteria for the stability or instability of the corresponding stock price model, and we give explicit formulae for the invariant distributions in the recurrent case.     

中外锌期货价格关联性研究

中国是世界上最主要的锌进口国和消费国,锌消费具有较高的对外依存度.采用协整检验、误差修正模型、格兰杰因果关系检验、方差分解和脉冲响应函数等计量经济方法对2007年4月16日～2015年10月12日的中外锌期货价格数据进行了实证分析,以研究中外锌期货价格的关联性,并提出相关对策建议.     

A Bayesian Approach to Modeling Purchase Frequency

Direct marketers are often faced with the task of ranking, or scoring individual customers in terms of their expected value to the firm. A critical element of their scoring systems is expected frequency of customer interaction. In this paper the authors develop a hierarchical Bayes model of purchase frequency that combines a Poisson likelihood with a gamma mixing distribution, where the mixing distribution is a function of covariates. The proposed model is evaluated with two direct marketing datasets, and is shown to provide improved estimates of purchase frequency, particularly for customers with short purchase histories or who have infrequent interaction with the firm.     

我国股指期货价格波动风险研究

我国股指期货市场从2010年成立至今,发展非常迅速,通过选择VaR方法对我国股指期货日内波动风险进行实证分析和预测,对不能用VaR方法解决的重大事件产生的影响作了压力测试,并结合我国市场实际状况提出建设性意见。     

货币流动性因素对国际大宗商品期货价格的影响

以货币流通量为代表的货币流动性与国际大宗商品期货价格之间存在长期的协整关系和因果关系,货币流动性虽然对大宗商品期货价格波动存在一定影响(并不特别显著),两者在变动走势中始终保持趋势基本一致的变化,但是货币流动性并不是引起国际大宗商品期货价格变动的最主要因素.货币流动性对资产价格具有影响,主要是由于货币资产配置的因素——国际大宗商品期货价格作为资产价格之一也是货币资产配置的选择之一.国际大宗商品期货价格波动更多依赖于商品的供需关系,货币流动性大小仅是通过货币因素制约或活跃商品交易量而影响价格波动.     

PTA期现价格动态关系实证研究

以郑州期货交易所PTA期货和进口、国产PTA现货为研究对象,利用格兰杰因果检验、协整检验、误差修正模型等方法,分析了我国PTA期货市场与现货市场长期均衡关系和短期动态关联关系。结果表明:国内的现货PTA价格和期货PTA价格是互相引导的;PTA期货价格对现货价格的影响强于现货价格对期货价格的影响;短期来看PTA期货价格与现货价格之间存在协整关系;长期来看PTA期货价格与现货价格保持着长期的均衡关系。以上研究表明,我国PTA期货市场已基本具备市场价格发现功能和一定的价格自我约束机制。     

中美贸易战对农产品期货价格的影响

本文在中美贸易摩擦的背景下,从供给、需求等方面定性地分析了贸易战对农产品期货价格的影响因素与程度。在此基础上,本文还选取了2017-2018年豆粕现货价格和期货价格数据进行初步计量分析,研究贸易战对期货价格影响程度。中国农业应积极发展农业现代化,调整农业补贴结构;调整农产品供给结构,弥补短期缺口;加强期货市场监管,消除过度投机行为,稳定农产品期货价格,控制贸易战对农产品期货市场的影响。     

A No‐Arbitrage Fractional Cointegration Model for Futures and Spot Daily Ranges

The no‐arbitrage relation between futures and spot prices implies an analogous relation between futures and spot daily ranges. The long‐memory features of the range‐based volatility estimators are analyzed, and fractional cointegration is tested in a semi‐parametric framework. In particular, the no‐arbitrage condition is used to derive a long‐run relationship between volatility measures and to justify the use of a fractional vector error correction model (FVECM) to study their dynamic relationship. The out‐of‐sample forecasting superiority of FVECM, with respect to alternative models, is documented. The results highlight the importance of incorporating the long‐run equilibrium in volatilities to obtain better forecasts, given the information content in the volatility of futures prices. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark 33:77–102, 2013     

A Partially Observed Model for Micromovement of Asset Prices with Bayes Estimation via Filtering

A general micromovement model that describes transactional price behavior is proposed. The model ties the sample characteristics of micromovement and macromovement in a consistent manner. An important feature of the model is that it can be transformed to a filtering problem with counting process observations. Consequently, the complete information of price and trading time is captured and then utilized in Bayes estimation via filtering for the parameters. The filtering equations are derived. A theorem on the convergence of conditional expectation of the model is proved. A consistent recursive algorithm is constructed via the Markov chain approximation method to compute the approximate posterior and then the Bayes estimates. A simplified model and its recursive algorithm are presented in detail. Simulations show that the computed Bayes estimates converge to their true values. The algorithm is applied to one month of intraday transaction prices for Microsoft and the Bayes estimates are obtained.     

A Simplified Quadrature Approach for Computing Bermudan Option Prices

We examine a simple quadrature approach to compute the prices of Bermudan options when the value of the corresponding European claim can be computed in closed form, one period before maturity. Using a constant grid of stock prices at early exercise time points, the known value of the European option is used as a smoothing device to enable efficient numerical integ ration with quadrature approaches. Examples with the geometric Brownian motion context and the lognormal jump‐diffusion context are provided.     

A Partially Hidden Markov Model of Customer Dynamics for CLV Measurement

Customer lifetime value (CLV) measurement is challenging as it requires forecasting customers' future purchases. Existing stochastic CLV models for this purpose generally make the following assumptions: 1) purchase behavior of customers can be described by purchase frequency and the average monetary value of transactions, 2) customers keep the same purchase behavior pattern over time, 3) purchase frequency and monetary value are independent, and 4) customers are active during a limited period of time after which they permanently defect. We develop a new stochastic model that relaxes these four assumptions. First, in addition to the number of transactions and its monetary values, we also model purchase incidence decisions (i.e. whether or not to purchase). Second, our partially hidden Markov truncated–NBD-GG (PHM/TNBD-GG) model allows dynamic purchase patterns, dependence between purchase frequency and monetary value, and customers to become active after a few periods of temporary inactivity. Validation of our model on two datasets demonstrates that if assumptions 1 to 4 of existing stochastic models are violated our model produces more accurate forecasts of future customer behavior.     

Return and Volatility Dynamics in the Spot and Futures Markets in Australia: An Intervention Analysis in a Bivariate EGARCH‐X Framework

This article provides evidence of linkages between the equity market and the index futures market in Australia, where the futures market has experienced a major structural event due to the futures contract respecification. A bivariate Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model is developed that includes a cointegrating residual as an explanatory variable for both the conditional mean and the conditional variance. The conditional mean returns from both markets are influenced by the long‐run equilibrium relationship, and these markets are informationally linked through the second moments. The crossmarket spillovers exhibit asymmetric behavior in that the volatility responses to past standardized innovations are different for market advances and market retreats. An intervention analysis shows that some of the parameters describing the return‐generating process have shifted after the contract respecification by the futures exchange. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:833–850, 2001     

沪深300股指期货与现货的价格发现分析——基于频带分解的视角

运用集合经验模式分解方法(EEMD)对沪深300股指期货与现货价格进行频带分解,并在重构不同周期长度的波动分量的基础上,应用向量自回归、Granger因果检验分析指数期货与现货在对应短周期、中周期波动分量与长期趋势分量间的引导关系,结果表明:指数期货与现货间的价格发现关系具有随着波动成分周期长度不同而变化的结构化特征;在短周期波动分量上,指数期货对现货存在较为有限的价格发现能力;而在中周期波动分量与长期趋势分量上,现货在价格发现中居主要地位。