指数平滑模型探讨

指数平滑模型在经济预测中应用较为广泛,时间序列的变动趋势不同,应用的平滑模型有所区别。本文介绍了各种指数平滑模型,并以某港为例分别用三次指数平滑及二阶差分—指数平滑模型对其吞吐量进行了预测,并做出了各种模型的适用性分析。     

上证综合指数的统计分析与预测

对上证综合指数进行了时间序列分解的实证研究，并在此基础上建立ＡＲＩＭＡ模型对其进行拟合预测，取得了一定的效果。     

ARMA模型在预测船价指数中的应用

船价是造船行业中最重要的指标之一,目前市场预测船价指数方法均没有考虑船价的自身长期趋势,为此在预测船价指数中引入ARMA模型,充分考虑了时间序列自身的发展趋势,以得出更准确的船价预期.     

复航河流沿岸港区的吞吐量预测方法的探讨

利用多种方法对复航河流沿岸港区吞吐量发展水平作出预测。近期预测主要采用时间序列法、灰色模型法和修正指数曲线法,对各方法预测结果加权平均得出吞吐量预测值。远期预测时,利用灰色模型曲线和修正指数曲线构造复合曲线获得吞吐量预测值。最后在定性分析的基础上对吞吐量预测值作出修正。     

基于三次指数平滑法的苏州港吞吐量预测

港口吞吐量预测是港口规划过程中的关键环节,直接关系到港口规划的科学合理性。文中根据苏州港集装箱吞吐量、货物吞吐量的历史数据,建立了时间序列的三次指数平滑模型预测模型,对苏州港集装箱吞吐量、货物吞吐量加以预测和分析,并提出了苏州港进一步发展的策略。     

组合预测模型在宁波港集装箱吞吐量预测中的应用

港口吞吐量预测是港口规划过程中的关键环节,直接关系到港口规划的科学合理性。本文根据宁波港集装箱吞吐量的历史数据,建立了时间序列的三次指数平滑模型、灰色系统预测模型等单项预测模型。鉴于单项预测模型的局限性,提出了组合预测模型,采用线性规划的方法确定其最优组合的权重,并对宁波港集装箱吞吐量加以预测和分析。     

波罗的海干散货运价指数波动性研究

<正>引言波罗的海国际干散货运价指数是干散货运费率的晴雨表,其走势反映了国际干散货的市场状况,一直受到从业者和学者的普遍关注。国际干散货运价指数的波动性一直都是国际干散货市场研究的焦点。一方面,波动性与干散货市场的不确定性和风险密切相关,这对于企业进行风险管理、投资和决策都具有很重要的意义。另一方     

舰船辐射噪声的混沌特性检验

为提取舰船目标辐射噪声混沌特征,实现对舰船目标的自动识别,首先需要对舰船辐射噪声的混沌特性进行检验。采用一种改进的Lyapunov指数谱估计方法,计算其最大Lyapunov指数是否大于零,以及所有的Lyapunov指数之和是否小于零来判定噪声时间序列是否具有混沌特性。采用三类舰船目标辐射噪声作仿真计算,仿真结果表明三类舰船辐射噪声都具有一定的混沌特性,该结论为下一步基于混沌预测的目标检测以及提取舰船辐射噪声非线性混沌特征等工作奠定了理论基础。     

南京港集装箱吞吐量预测研究

港口集装箱吞吐量的合理预测对提高港口竞争力与经济效益具有决定意义。为了提高港口集装箱吞吐量预测精度,分别采用时间序列法中的三次指数平滑法、灰色GM(1,1)法和因果分析法中的多元回归分析法对集装箱吞吐量进行预测。在此基础上运用多元回归法进行吞吐量预测模型的组合分析,根据预测结果与实际吞吐量进行优化组合研究并建立预测综合模型。综合模型融合了前三种方法的优点,克服了单一预测方法的不确定性,改善预测效果,更加适合于南京港集装箱吞吐量的实际预测。     

波罗的海干散货运价指数的ARFIMA模型研究

近年来国内外学者对波罗的海干散货运价指数(BDI)的预测建模做了许多分析和研究工作,笔者在认真研读相关文献的基础上,通过实证分析发现BDI指数收益率序列存在长记忆性,因此本文尝试引入ARFIMA模型来改进传统的ARMA预测模型。     

基于货运强度变化规律的货运量预测方法

目前我国部分地区货运量统计数据存在收集不全、统计口径不一致及社会经济环境变化大等问题,导致常规的时间序列预测法和回归预测法难以在这些地区应用。鉴于此,分析了国内外货运强度变化的规律,指出人均GDP和第三产业所占比例是影响货运强度的主要因子,提出了通过模糊聚类方法对地区货运发展阶段进行定位,找出其发展阶段所对应的货运强度值,进而提出依据人均GDP和第三产业所占比例进行货运量预测的方法。最后对邢台市的货运量预测进行了实证研究。     

进口原油运输船型经济性分析

石油是世界海上运量最大的货种之一,约占海上总运输量的三分之一。加入WTO后,中国石油海上运输量,特别是进口原油运输量将大幅度地增加。针对这一现实情况,本文对世界原油运输船队的技术经济作了概括性分析,对原油进口航线作了介绍。建立了单船运输经济性测算模型。基于实船经济指标测算结果,以必要运费率为主,通过比较选出了优良船型。并定量测算出不同类型船舶在同一航线上营运的必要运费率及其差异。研究结果指出,随着进口原油量的大幅度增加,中国应大力发展VLCC和Suezmax船队,重点建设大型深水油轮码头。     

上海内河货运量的组合预测

内河航运是综合交通运输系统中不可缺少的运输方式,存在着很大的潜在优势.定量地把握未来内河运输的发展趋势,具有重大的现实意义.通过利用时间序列模型、logistic曲线与自回归模型等,对2010-2015年的上海内河货运量进行预测.在此基础上,对不同模型赋予不同的权重,建立了组合预测模型.研究表明:未来上海内河货运量将持续稳定地增长.为提高预测的精度,有必要综合地使用多个预测方法.     

Some properties of international maritime statistics

This paper tests two fundamental hypotheses concerning international maritime statistics. The first one deals with the question of stationary of the maritime market statistics. The second hypothesis tested is the assumption that the international maritime statistical time series are not distributed according to a normal of Guassian probability law, but rather belong to the same family of distributions with distinctly different critical parameters. Through well documented statistical methods, the paper concludes that the international freight rates observed on a day to day basis are generated by a random walk process. The paper finds that the shipping industry's conventioal wisdom is essentially correct. 'Last done' is as good a forecast of tomorrow's freight rate as any other generated by more sophisticated forecasting methods. Furthermore, freight rates and secondhand tonnage prices fluctuate closely together. The freight rates are generated by stochastic processes fully described by the Paretian family of distributions. The critical parameters of these distribution, the characteristic exponents, are such that the risk conscious ship operator can indeed reduce his exposure to risk by securing a correct set of freight rate contracts.     

Some properties of international maritime statistics

This paper tests two fundamental hypotheses concerning international maritime statistics. The first one deals with the question of stationary of the maritime market statistics. The second hypothesis tested is the assumption that the international maritime statistical time series are not distributed according to a normal of Guassian probability law, but rather belong to the same family of distributions with distinctly different critical parameters. Through well documented statistical methods, the paper concludes that the international freight rates observed on a day to day basis are generated by a random walk process. The paper finds that the shipping industry's conventioal wisdom is essentially correct. ‘Last done’ is as good a forecast of tomorrow's freight rate as any other generated by more sophisticated forecasting methods. Furthermore, freight rates and secondhand tonnage prices fluctuate closely together. The freight rates are generated by stochastic processes fully described by the Paretian family of distributions. The critical parameters of these distribution, the characteristic exponents, are such that the risk conscious ship operator can indeed reduce his exposure to risk by securing a correct set of freight rate contracts.     

航道货运量预测方法及其应用

为了精确预测航道未来货运量需求,克服传统预测方法无法实现复杂非线性拟合的缺点,分析了航道货运量的影响因素,探讨了遗传规划方法在航道货运量预测问题上的应用.根据遗传规划巾复制、交换、变异等进化方式,建立了基于遗传规划的航道货运量预测模型.以江苏省连申线苏北段历年货运量及区域经济发展状况为样本,采用遗传规划方法自动找出货运量随时间变化的规律,并对未来货运量进行了预测.结果表明,本箅法的计算相对误差很小,预测结果合理可信,且优于常用的回归预测,为解决航道货运量等非线性系统预测提供了一条新的途径.     

Forecasting short-term freight rate cycles: do we have a more appropriate method than a normal distribution?

General economists, as well as Maritime economists, assume that the time series they forecast follow normal distribution, and data is independently and identically distributed around the mean. This paper contests this assumption with the aid of three sets of time series: (1) The Dry Cargo Freight Index, 1741–2005: in this series the data deviate from the mean by more than three standard deviations on no fewer than six occasions, and exhibited “fat tails”; (2) The time charter freight rates for a 10-year-old, 80?000 dwt vessel from 6 January 1989 to 26 December 2008: this series also exhibits skewness and kurtosis in a leptokurtic distribution; and (3) The Dry Cargo Time Charter Index from 1971 to 2004: this series diverged from the normal distribution four times. Next, we searched more recent data for short-term cycles using the V-statistic. One cycle was found to last 4 years (2005 to 2008), which is in accordance with theory. This cycle started on 29 July 2005 and ended when it reached the (lowest) level of $4000 on 1 December 2008. A new 4-year cycle started on 1 December 2008 and is forecast to last until the end of 2010. Short-term forecasting of the cycle using V-statistic is theoretically confirmed by the theory advanced by Hampton [1990, published in 1989, ‘Analysis and shipping cycles I and II’, Seatrade Journal, 19–23. Long and Short Shipping Cycles: The Rhythms and Psychology of Shipping Markets, Monograph, 2nd ed. (Cambridge: Cambridge Academy of Transport), March, p. 66].     

乌江银盘枢纽工程河段货运量神经网络预测研究

采用BP神经网络建立了乌江银盘枢纽工程河段货运量的预测模型,并对货运量进行了实际预测,分析认为神经网络预测结果较戴尔斐法和GM(1,1)法更为合理。     

An investigation of forecast horizon and observation fit’s influence on an econometric rate forecast model in the liner shipping industry

This paper evaluates the influence of forecast horizon and observation fit on the robustness and performance of a specific freight rate forecast model used in the liner shipping industry. In the first stage of the research, a forecast model used to predict container freight rate development is presented by exploring the relationship between individual company’s rates and aggregated market rates, and thus assists in dealing with uncertainty and market volatility for a given business situation. In the second stage, a design of experiment approach is applied to highlight the influence of the forecast horizon and observation fit and their interactions on the forecast model’s performance. The results underline the complicated nature of creating a suitable forecast model by balancing business needs, a desire to fit a good model and achieve high accuracy. There is strong empirical evidence from this study; that a robust model is preferable, that overfitting is a true danger, and that a balance must be achieved between forecast horizon and the number of observations used to fit the model. In addition, methodological guidance has also been provided on how to test, design, and choose the superior model for business needs.     

A new perspective on price dynamics of the dry bulk market

The main result of this article is that freight rates and second hand prices in the dry bulk market seem to be stationary. By unit-root tests, an established tool for testing for random walk in economic time series, the random walk hypothesis can be rejected in most cases for the freight rate samples. This result is in contrast to the findings of a number of papers during the 1990s. However, the results confirm classical shipping market models that indicate stationarity in freight rates, which is not the case if the freight rates follow a random walk. By transforming all observations from US$ to Japanese yen detrended freight rates and prices seem to become stationary and volatility is reduced.