Noisy chaotic dynamics in commodity markets

The nonlinear testing and modeling of economic and financial time series has increased substantially in recent years, enabling us to better understand market and price behavior, risk and the formation of expectations. Such tests have also been applied to commodity market behavior, providing evidence of heteroskedasticity, chaos, long memory, cyclicity, etc. The present evaluation of futures price behavior confirms that the resulting price movements can be random, suggesting noisy chaotic behavior. Prices could thus follow a mean process that is dynamic chaotic, coupled with a variance that follows a GARCH process. Our conclusion is that models of this type could be constructed to assist in forecasting prices in the short run but not over long run time periods.First version received: June 2001/Final version received: March 2003     

基于GARCH族模型对中国股市波动的分析与预测

运用GARCH类模型对沪深300指数序列的波动性、收益率进行了实证研究,并且对序列做了拟合与预测,获得了不错的效果。除此,还证实了中国股市存在着显著的非对称效应。     

Simpler Probabilistic Population Forecasts: Making Scenarios Work

The traditional high-low-medium scenario approach to quantifying uncertainty in population forecasts has been criticized as lacking probabilistic meaning and consistency. This paper shows, under certain assumptions, how appropriately calibrated scenarios can be used to approximate the uncertainty intervals on future population size and age structure obtained with fully stochastic forecasts. As many forecasting organizations already produce scenarios and because dealing with them is familiar territory, the methods presented here offer an attractive intermediate position between probabilistically inconsistent scenario analysis and fully stochastic forecasts.     

基于改进灰色模型电力负荷预测

随着电力市场的推进,负荷预测已成为保证电网稳定运行的基础,电力负荷预测在电力系统规划中的重要性和迫切性越来越受到高度重视。然而,基于电力系统的复杂性,保证预测的准确性是电力企业负荷预测工作的关键。传统的GM(1,1)模型在实际应用中存在很多缺点和局限性,本文从初始条件处理和初值的选取方面进行了改进:对原始输入数据的处理,运用了指数加权法,对初值的处理,利用预测值和实际值的欧氏距离最小化的方法来确定的连续变化微分方程时间响应函数中的参数c值来代替x(1)(1)作为初值。通过实例分析得出本文中的改进取得了较好的效果。     

基于工序的油藏经营工资制度简析

文章分析了现代油藏经营管理、现行工资制度的特点,探索基于工序的油藏经营工资制度,即基于工序的定额工资制度,以期逐步完善现有的油藏经营工资制度,更有效的激励员工,实现油藏效益与个人收益的紧密联系及最大化。     

Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009

In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact that they form a class of universal approximators and may be expected to work well during exceptional periods such as major economic crises. Neural network models are often difficult to estimate, and we follow the idea of White (2006) of transforming the specification and nonlinear estimation problem into a linear model selection and estimation problem. To this end, we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge Estimator, which is better known to statisticians. The performances of these three model selectors are compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series from the G7 countries and the four Scandinavian ones, and focus on forecasting during the economic crisis 2007–2009. The forecast accuracy is measured using the root mean square forecast error. Hypothesis testing is also used to compare the performances of the different techniques.     

Combining forecasts: An application to elections

We summarize the literature on the effectiveness of combining forecasts by assessing the conditions under which combining is most valuable. Using data on the six US presidential elections from 1992 to 2012, we report the reductions in error obtained by averaging forecasts within and across four election forecasting methods: poll projections, expert judgment, quantitative models, and the Iowa Electronic Markets. Across the six elections, the resulting combined forecasts were more accurate than any individual component method, on average. The gains in accuracy from combining increased with the numbers of forecasts used, especially when these forecasts were based on different methods and different data, and in situations involving high levels of uncertainty. Such combining yielded error reductions of between 16% and 59%, compared to the average errors of the individual forecasts. This improvement is substantially greater than the 12% reduction in error that had been reported previously for combining forecasts.     

生态水库研究及建设东风西沙生态水库探讨

本文通过对国内外生态水库研究现状的调查,阐述了生态水库的概念、内涵及标志,并就东风西沙生态型水库建设及生态调度进行了探讨,是对促进维持水库的基本功能并使其得以可持续发挥的有益尝试,对构建水资源合理利用与生态系统保护之间的和谐关系有着重要意义。     

出砂强敏感稠油油藏低效水驱转热采政策界限研究——以林东馆三段稠油油藏为例

林樊家油田林东馆三段地质条件复杂,地层敏感性强,供液差,产能低,油稠,出砂严重,多年来采用了各种工艺措施,均未取得好的水驱开采效果。文章运用数值模拟手段,分析了低水驱的主要原因和论证了低效水驱转蒸汽热采可行性。在此基础上,研究了该块低效水驱转蒸汽热采的开发经济技术政策界限。开发实践表明,低效水驱稠油油藏通过转热采可大幅提高采收率,同时研究成果对同类油藏的开发具有重要指导意义。     

Using Genetic Algorithms to Estimate and Validate Bioeconomic Models: The Case of the Ibero-atlantic Sardine Fishery

Synopsis The Neo-classical approach to fisheries management is based on designing and applying bioeconomic models. Traditionally, the basic bioeconomic models have used pre-established non-linear functional forms (logistic, Cobb–Douglas) in order to try to reflect the dynamics of the renewable resources under study. This assumption might cause misspecification problems and, in consequence, a loss of predictive ability. In this work we intend to verify if there is a bias motivated by employing the said non-linear parametric perspective. For this purpose, we employ a novel non-linear and non-parametric prediction method, called Genetic Algorithms, and we compare its results with those obtained from the traditional methods.