[下载]硕士学位论文 农村居民食物消费结构变动及其对粮食需求影响的实证分析

Variety and Volatility in Financial Markets
Authors: Lillo, Fabrizio; Mantegna, Rosario N.

We study the price dynamics of stocks traded in a financial market by considering the statistical properties both of a single time series and of an ensemble of stocks traded simultaneously. We use the n stocks traded in the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days subsequent to these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments are fluctuating in time and are stochastic processes themselves. We characterize the statistical properties of ensemble return distribution central moments by investigating their probability density functions and temporal correlation properties. In general, time-averaged and portfolio-averaged price returns have different statistical properties. We infer from these differences information about the relative strength of correlation between stocks and between different trading days. Lastly, we compare our empirical results with those predicted by the single-index model and we conclude that this simple model is unable to explain the statistical properties of the second moment of the ensemble return distribution.

Comment: 10 pages, 11 figures

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Online Mathematics Materials

In my spare time I've been developing some online educational materials for mathematics. Some of these may eventually become part of the Felynx Cougati library of multimedia mathematics materials, an ambitious project which I am peripherally involved in. Others were developed for courses I was lecturing, or as personal projects.

• Classification of Cellular Automata Some lecture notes I've prepared for an informal seminar on cellular automata I delivered at the University of Houston in spring of 2002. [Gzipped PostScript Version]...... [Adobe PDF Version]
  

• Lecture notes in Partial Differential Equations (250 pages; working draft) I originally wrote these for Math 3363, a course I taught at the University of Houston in 2001-2002. I am now using them to teach Math 305 at Trent University [Gzipped PostScript Version]...... [Adobe PDF Version]
  

• Visual Abstract Algebra(240 pages; working draft) An introduction to groups, rings, and fields, which I'm using to teaching Math 330 here at Trent.
  

• Analysis, Measure & Probability: A visual Introduction (163 pages; working draft) My attempt to develop a new pedagogical approach to real analysis, with emphasis on geometric intuition and probabilistic interpretations. [[Postscript]........[PDF]]
  

• Voting, Arbitration, and Fair Division: the mathematics of social choice (133 pages)
  Contents: Survey of voting procedures and their shortcomings. Sen's Impossibility Theorem, Arrow's Impossibility Theorem, and the Gibbard-Satterthwaite Impossibility Theorem. Binary voting systems; May's theorem. Weighted and Vector-weighted systems. Bentham's utilitarianism; von Neumann-Morgenstern definition of cardinal utility. Bargaining Games and the Nash Arbitration Scheme. Fair division theory. [Gzipped Postscript]................ [Adobe PDF]
  

• Models of Philosophy (121 pages) A short monograph on how mathematical methods could be profitably employed to address certain problems in philosophy of mind, philosophy of language, philosophy of science, and political philosophy.
  

• Lecture notes in Linear Algebra I wrote these for Math 223, a course I taught at the University of Toronto in spring of 2000.
  

• Ergodic Theory, Stochastic Processes, and Information Theory (30 pages) Slides from a two hour seminar I delivered in 1999 at the University of Toronto, intended to be an introduction for nonspecialists. It is (I hope) accessible to any mathematically literate person. [Gzipped PostScript Version]...... [Adobe PDF Version]

[此贴子已经被作者于2006-4-24 3:42:23编辑过]

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1. [求助]garch模型的选择标准 ;
   
2. [求助]1型tobit模型中关于正态性和异方差的检验 ;
   
3. [求助] Hausman Test in Eviews5 ;
   
4. 有谁懂面板数据联立方程 ;
5. 【求助】似不相关估计 ;
6. [讨论]Data Envelopment Analysis
7. Granger因果检验
8. [讨论]TOBIT模型的学习！
9. 如何使用hasuman检验内生性问题？
10. [求助]主成份回归与因子回归
11. [求助]结构突变的问题
12. 主成分分析与因子分析的区别联系。

    [

[此贴子已经被作者于2006-4-24 21:52:50编辑过]

《实用数据统计分析及SPSS 12.0应用》 出版社：人民邮电出版社 作者：求是科技/章文波/陈红艳

[此贴子已经被作者于2006-4-25 7:34:52编辑过]

《SPSS12统计建模与应用实务》 出版社：中国铁道出版社 作者：林杰斌/林川雄/刘明德/飞捷工作室 上架日期：2006-04-03 出版日期：2006年2月

[此贴子已经被作者于2006-4-25 7:35:23编辑过]

《社会统计分析——SPSS应用教程》 出版社：清华大学出版社 作者：卢湘鸿/周爽/朱志洪/朱星萍 上架日期：2006-03-29 出版日期：2006年3月

《统计学习基础—数据挖掘、推理与预测》 [ 华储网推荐 ] The Elements of Statistical Learning:Data Mining,Inference,and Prediction 出版社：电子工业出版社 作者：[美]Trevor Hastie/Robert Tibshirani/Jerome Friedman著/范明/柴玉梅/昝红英等译

《统计学习理论》 [ 华储网推荐 ] Statistical Learning Theory 出版社：电子工业出版社 作者：（美）Vladimir N.Vapnik 许建华/张学工 上架日期：2004-07-17 出版日期：2004年6月

Linear Regression Models for Panel Data Using SAS, STATA, LIMDEP, and SPSS

Hun Myoung Park

Winter 2005

Table of Contents

1. Introduction
   
   • 1.1 Data Arrangement
     
   • 1.2 Fixed Effect versus Random Effect Models
     
   • 1.3 Estimation and Software Issues
2. Least Squares Dummy Variable Regression
   
   • 2.1 Model 1 without a Dummy Variable
     
   • 2.2 Model 2 with a Dummy Varialbe
     
   • 2.3 Visualization of Model 1 and 2
     
   • 2.4 Alternatives to LSDV1
     
   • 2.5 Estimating Three LSDVs
3. Panel Data Models
   
   • 3.1 Functional Forms and Notation
     
   • 3.2 Fixed Effect Models
     
   • 3.3 Random Effect Models
     
   • 3.4 Hausman Test: Fixed Effects versus Random Effects
     
   • 3.5 Poolability Test
4. The Fixed Group Effect Model
   
   • 4.1 The Pooled OLS Regression Model
     
   • 4.2 LSDV1 without a Dummy
     
   • 4.3 LSDV2 without the Intercept
     
   • 4.4 LSDV3 with Restrictions
     
   • 4.5 Within Group Effect Model
     
   • 4.6 Between Group Effect Model: Group Mean Regression
     
   • 4.7 Testing Fixed Group Effects
     
   • 4.8 Summary
5. The Fixed Time Effect Model
   
   • 5.1 Least Squares Dummy Variable Models
     
   • 5.2 Within Time Effect Model
     
   • 5.3 Between Time Effect Model
     
   • 5.4 Testing Fixed Time Effects
6. The Fixed Group and Time Effect Model
   
   • 6.1 Least Squares Dummy Variable Models
     
   • 6.2 LSDV1 without Two Dummies
     
   • 6.3 LSDV1 + LSDV3
     
   • 6.4 LSDV3 with Two Restrictions
     
   • 6.5 Two-way Within Effect Model
     
   • 6.6 Using the TSCSREG and PANEL Procedures
     
   • 6.7 Testing Fixed Group and Time Effects
7. Random Effect Models
   
   • 7.1 The One-way Random Group Effect Model
     
   • 7.2 Estimations in SAS, STATA, and LIMDEP
     
   • 7.3 The One-way Random Time Effect Model
     
   • 7.4 The Two-way Random Effect Model in SAS
     
   • 7.5 Testing Random Effect Models
     
   • 7.6 Fixed Effects versus Random Effects
     
   • 7.7 Summary
8. Poolability Test
   
9. Conclusion
   
10. Appendix
    
11. References

This document summarizes linear regression models for panel data and illustrates how to estimate each model using SAS 9.1, STATA 9.0, LIMDEP 8.0, and SPSS 13.0. This document does not address nonlinear models (i.e., logit and probit models), but focuses on linear regression models.

[此贴子已经被作者于2006-4-25 22:52:25编辑过]