Statistical inference and modelling of momentum in stock prices

The following results are obtained, (i) It is possible to obtain a time series of market data {y(t)} in which the fluctuations in fundamental value have been compensated for. An objective test of the efficient market hypothesis (EMH), which would predict random correlations about a constant value, is thereby possible, (ii) A time series procedure can be used to determine the extent to which the differences in the data and the moving averages are significant. This provides a model of the form y(t)-y(t-l)=0.5{y(t- l)-y(t-2)}+ε(t)+0.8ε(r-1) where ε(t) is the error at time t, and the coefficients 0.5 and 0.8 are determined from the data. One concludes that today's price is not a random perturbation from yesterday's; rather, yesterday's rate of change is a significant predictor of today's rate of change. This confirms the concept of momentum that is crucial to market participants. (iii) The model provides out-of-sample predictions that can be tested statistically. (iv) The model and coefficients obtained in this way can be used to make predictions on laboratory experiments to establish an objective and quantitative link between the experiments and the market data. These methods circumvent the central difficulty in testing market data, namely, that changes in fundamentals obscure intrinsic trends and autocorrelations. This procedure is implemented by considering the ratio of two similar funds (Germany and Future Germany) with the same manager and performing a set of statistical tests that have excluded fluctuations in fundamental factors. For the entire data of the first 1149 days beginning with the introduction of the latter fund, a standard runs test indicates that the data is 29 standard deviations away from that which would be expected under a hypothesis of random fluctuations about the fundamental value. This and other tests provide strong evidence against the efficient market hypothesis and in favour of autocorrelations in the data. An ARIMA time series finds strong evidence (9.6 and 21.6 standard deviations in the two coefficients) that the data is described by a model that involves the first difference, indicating that momentum is the significant factor. The first quarter's data is used to make out-of-sample predictions for the second quarter with results that are significant to 3 standard deviations. Finally, the ARIMA model and coefficients are used to make predictions on laboratory experiments of Porter and Smith in which the intrinsic value is clear. The model's forecasts are decidedly more accurate than that of the null hypothesis of random fluctuations about the fundamental value.     

Contract type and decision right of sales promotion in supply chain management with a capital constrained retailer

From the practices of Chinese consumer electronics market, we find there are two key issues in supply chain management: The first issue is the contract type of either wholesale price contracts or consignment contracts with revenue sharing, and the second issue is the decision right of sales promotion (such as advertising, on-site shopping assistance, rebates, and post-sales service) owned by either manufacturers or retailers. We model a supply chain with one manufacturer and one retailer who has limited capital and faces deterministic demand depending on retail price and sales promotion. The two issues interact with each other. We show that only the combination (called as chain business mode) of a consignment contract with the manufacturer’s right of sales promotion or a wholesale price contract with the retailer’s right of sales promotion is better for both members. Moreover, the latter chain business mode is realized only when the retailer has more power in the chain and has enough capital, otherwise the former one is realized. But which one is preferred by customers? We find that the former is preferred by customers who mainly enjoy low price, while the latter is preferred by those who enjoy high sales promotion level.     

Real-World Forward Rate Dynamics With Affine Realizations

We investigate the existence of affine realizations for Lévy driven interest rate term structure models under the real-world probability measure, which so far has only been studied under an assumed risk-neutral probability measure. For models driven by Wiener processes, all results obtained under the risk-neutral approach concerning the existence of affine realizations are transferred to the general case. A similar result holds true for models driven by compound Poisson processes with finite jump size distributions. However, in the presence of jumps with infinite activity we obtain severe restrictions on the structure of the market price of risk; typically, it must even be constant.     

Explicit Solutions of Quadratic FBSDEs Arising From Quadratic Term Structure Models

We provide explicit solutions of certain forward-backward stochastic differential equations (FBSDEs) with quadratic growth. These particular FBSDEs are associated with quadratic term structure models of interest rates and characterize the zero-coupon bond price. The results of this paper are naturally related to similar results on affine term structure models of Hyndman (Math. Financ. Econ. 2(2):107–128, 2009) due to the relationship between quadratic functionals of Gaussian processes and linear functionals of affine processes. Similar to the affine case a sufficient condition for the explicit solutions to hold is the solvability in a fixed interval of Riccati-type ordinary differential equations. However, in contrast to the affine case, these Riccati equations are easily associated with those occurring in linear-quadratic control problems. We also consider quadratic models for a risky asset price and characterize the futures price and forward price of the asset in terms of similar FBSDEs. An example is considered, using an approach based on stochastic flows that is related to the FBSDE approach, to further emphasize the parallels between the affine and quadratic models. An appendix discusses solvability and explicit solutions of the Riccati equations.     

一种改进的三帧差分运动目标实时检测算法

针对传统的三帧差分法提取的运动目标存在大量的噪声和空洞,提出了一种改进的三帧差分运动目标实时检测算法。该算法采用Surendra背景提取算法提取有效背景,对视频流中连续的三帧图像分别进行背景减除,得到的结果作为反馈对背景进行选择性更新,利用HSV颜色空间去除阴影后进行三帧差分,将差分结果进行“与”运行,通过将中间帧背景减除结果与“与”运算的结果进行“或”运算,这样可以得到运动目标的完整信息。实验结果表明,该算法能够快速、完整、准确地检测出运动目标,可有效应用于实时监控系统。     

工资上涨对我国物价和出口品成本的影响分析

近年来我国劳动者报酬增速低于国内增加值(GDP)增速,居民收入水平提高较慢.提高各部门工资水平、增加居民收入、使得居民收入与GDP同步增长成为保证我国经济快速稳定增长的必要措施.2010年我国大部分省市将最低工资标准提高20%以上,作者提出了新的区分加工出口的非竞争型投入产出价格模型,并推导出工资水平提高对我国物价以及出口品成本的影响公式.实际测算结果表明,工资上涨带来的通货膨胀及对出口品成本影响较小,我国应该及时出台相应的政策措施提高各部门工资水平.     

三种生成神经网络拓扑结构的方法在股票、商品价格预测中的应用及结果比较

对比了三种不同神经网络模型的生成方式:传统神经网络生成模型,遗传算法训练神经网络模型,以及在第二种方式训练参数的基础上,再使用传统神经网络优化生成模型.论文使用上述三种方法对代表性股票和商品价格进行拟合并预测,通过预测结果准确性和稳定性的比较发现:引入遗传算法后的神经网络在样本内的拟合误差有所降低,而第三种方法在样本外有最低的预测误差和最优稳定性.     

我国铝期货、铝现货与废铝价格动态关系的实证研究

利用Johansen协整检验、Granger因果检验以及向量误差修正(VEC)模型、脉冲响应分析和方差分解分析,从三个不同的角度对我国铝期货、铝现货和废铝市场价格间的动态关系进行了实证分析,研究结果表明:从引导关系看,铝期货价格与铝现货价格之间具有协整关系,并且铝期货价格对铝现货价格及废铝价格具有单向价格引导关系,铝现货价格对废铝价格具有单向价格引导关系;从冲击反应看,铝期货对铝现货的冲击比较强烈,而铝期货对废铝以及铝现货对废铝的冲击相对比较和缓;从价格发现程度看,铝期货市场具有最强的价格发现能力,铝现货价格发现能力次之,废铝的价格发现能力最弱,表明铝期货是价格发现过程的主要驱动力量.     

国际油价波动跳跃性特征的实证分析

根据国际油价波动中存在异常跳跃的情况,本文运用EGARCH-Jump模型对国际油价波动的跳跃性特征进行了实证分析。结果表明,加入跳跃因素的模型减缓了国际油价波动的持续性,同时杠杆效应消失,表明跳跃性因素是国际油价波动的影响因素之一,也证实了国际油价波动的跳跃性特征是国际石油市场产生杠杆效应的原因。但从长期来看,跳跃性因素对国际油价波动的扰动影响并不大,国际油价的波动仍主要受正常信息的影响。总体上,EGARCH-Jump模型比普通GARCH族模型能更好地捕捉国际油价波动的动态性特征。     

中美燃料油期货价格引导研究

本文利用ADF单整检验、EG协整检验、误差修正模型、引导关系检验等方法研究中美燃料油期货价格之间的互动关系,结果表明:我国燃料油期货在价格和价格收益方面均与国际燃料油市场存在明显的即时引导关系;国际燃料油期货市场上的价格变动对国内燃料油期货价格以及价格收益的变动具有单向的滞后引导作用;我国燃料油期货市场的价格和收益方面的信息对于国际市场几乎不产生影响,我国尚不具备制定价格的话语权。