文档介绍：大连海事大学
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毕业论文
二○一二年六月
基于时间序列分析及Clementine软件的宝钢股价研究
专业班级:数学与应用数学2008级1班
姓名: XX
指导教师: XX
数学系
摘要
时间序列是按照时间顺序取得的一系列观测值,现实中的很多数据都是以时间序列的形式出现的:一个工厂每月生产的一系列货物数量,每周道路事故的一系列数据,每小时观察的药品生产产量。时间序列的例子在一些领域中是极丰富的,诸如经济,商业,工程等。时间序列分析典型的一个本质特征就是相邻观测值之间的依赖性。时间序列观测值之间的这种依赖特征具有重要的现实意义。时间序列分析所论及的就是对这种依赖性进行分析的技巧。要求对时间序列数据生成随机动态模型,并将这种模型用于重要的应用领域。
本文的主要内容是借助SPSS Clementine 软件研究宝山钢铁股票价格随时间的变化规律,并用时间序列分析的有关知识对其进行建模预测。本文分两部分:第一部分介绍时间序列分析的一些基本概念,如平稳过程、自相关函数、偏相关函数、白噪声等,然后对几种时间序列模型进行描述;另一部分借助SPSS Clementine 软件对宝山钢铁股价这一具体事例分别用专家建模、指数平滑建模和ARIMA建模并对股价进行短期预测,最后通过模型参数比较及预测值误差对比,找出最佳模型。在给案例建模的同时,将给出使用SPSS Clementine软件研究的具体过程。
关键词:时间序列;SPSS Clementine软件;宝钢股价;模型比较
Abstract
The time series is a sequence of observations taken sequentially in time. Many sets of data appear as time series in reality: a monthly sequence of the quantity of goods shipped from a factory, a weekly series of the number of traffic accidents, hourly observations made on the yield of a chemical process, and so on. Examples of time series abound in such fields as economics, business, engineering and so on. The nature of this dependenced among observations of a time series is of considerable practical interest. Time series analysis is concerned with techniques for the analysis of this dependence. This requires the development of stochastic and dynamic models for time series data and the use of such models in important areas of application.
The main task of this dissertation is to have a research on the law of the varying number of the stock price of the Baoshan iron and pany. In this study, we will make the use of the software SPSS Clementine and create the models of the stock price by using the time series analysis. To begin with, this dissertation briefly introduces some basic concepts such as stationery process, autocorrelation function partial correlation functions and white noise about the time series analysis. In addition, this dissertation begins to talk in detail about several f