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1、2009.11 Huazhong University of Science and Technology,1,Econometrics for Finance 金融计量经济学,讲授：薛明皋 电话：E-mail:,2009.11 Huazhong University of Science and Technology,2,课程目标,课程目标:了解和掌握广泛应用于金融领域的现代经济计量的技术和方法.金融学的快速发展使它已成为一门相对独立的学科。金融学“是一门具有高度实践性的科学”，“金融理论与实证分析之间关系的密切程度是其他社会学科无法相比的”.金融经济学家进行推断的基本方法是金融计量经济学，
2、即以模型为基础的统计推断。,2009.11 Huazhong University of Science and Technology,3,教材,Introductory Econometrics for Finance Chris BrooksCambridge University Press 2008,2009.11 Huazhong University of Science and Technology,4,作者简介,Chris Brooks was formerly Professor of Finance at the ISMA Centre,University of Read
3、ing,where he also obtained his PhD and BA in Economics and Econometrics.His areas of research interest include econometric modeling and forecasting,risk measurement,asset management,and property finance.He has published over sixty articles in leading academic and practitioner journals,including the
4、Journal of Business,the Journal of Banking and Finance,Journal of Empirical Finance,Oxford Bulletin and Economic Journal.Chris is Associate Editor of several journals,including the International Journal of Forecasting.,2009.11 Huazhong University of Science and Technology,5,本书的特点,内容广泛：包含了与金融领域相关的各种经
5、济计量方法难度适中：不要求具备很多的数学知识预备知识数学：微积分和线性代数基础，统计学基础金融：公司金融、金融市场、投资等方面的基础知识注重应用：提供相关软件的使用和金融方面的应用实例,2009.11 Huazhong University of Science and Technology,6,其它参考教材,经济计量学方面的教科书；罗伯特 S.平狄克 等计量经济模型与经济预测，机械工业出版社J.M.伍德里奇,计量经济学导论现代观点，人民大学出版社时间序列分析方面的教科书；等时间序列分析预测与控制，中国统计出版社有关金融市场学、公司金融等方面的教科书；，1999,The Econometric
6、 Modelling of Financial Time Series，金融时间序列的经济计量学模型，经济科学出版社，2002年。et al.,1997,The Econometrics of Financial Market；金融市场计量经济学，上海财经大学出版社，2003年。专门介绍和论述股票市场、衍生证券、固定收入证券等方面的实证分析方法和理论前沿。,2009.11 Huazhong University of Science and Technology,1,Chapter 1,Introduction,2009.11 Huazhong University of Science an
7、d Technology,8,Learning Outcomes,In this chapter,you will learn how to Distinguish between different types of data Describe the steps involved in building an econometric model Calculate asset price returns Construct a workfile,import data and accomplish simple tasks in EViews,2009.11 Huazhong Univer
8、sity of Science and Technology,9,1.1 What is Econometrics?,Literal meaning is“measurement in economics”.对经济现象和经济关系的数量/计量分析以经济理论和经济数据为依据,应用数学和统计学的方法，通过建立数学模型来研究经济现象及其变化规律的一门经济学科。（有多种定义）Definition of financial econometrics:The application of statistical and mathematical techniques to study problems in
9、 finance.,2009.11 Huazhong University of Science and Technology,10,the value of financial econometrics,Testing theories in financeDetermining asset prices or returnsTesting hypotheses concerning the relationships between variables Examining the effect on financial markets of changes in economic cond
10、itionsForecasting future values of financial variables and for financial decision-making.,2009.11 Huazhong University of Science and Technology,11,Examples of some problems that may be solved by an Econometrician,1.Testing whether financial markets are weak-form informationally efficient.2.Testing w
11、hether the CAPM or APT represent superior models for the determination of returns on risky assets.3.Measuring and forecasting the volatility of bond returns.4.Explaining the determinants of bond credit ratings used by the ratings agencies.5.Modelling long-term relationships between prices and exchan
12、ge rates,2009.11 Huazhong University of Science and Technology,12,Examples of some problems that may be solved by an Econometrician,6 Determining the optimal hedge ratio for a spot position in oil7 Testing technical trading rules to determine which makes the most money8 Testing the hypothesis that e
13、arnings or dividend announcements have no effect on stock prices.9 Testing whether spot or futures markets react more rapidly to news.10 Forecasting the correlation between the returns to the stock indices of two countries.,2009.11 Huazhong University of Science and Technology,13,Financial data ofte
14、n differ from macroeconomic data.1 In economics,there are some problems:(a)small samples problem(b)measurement error(c)data revisions2 In finance,higher frequency data Furthermore,the analysis of financial data also brings with it a number of new problems.For example,(a)financial data have”noisy”;(b
15、)almost always not normally distribution.,1.2 Is financial econometrics different from economic econometrics?,2009.11 Huazhong University of Science and Technology,14,1.3 Types of Data,There are 3 types of data:1.Time series data2.Cross-sectional data3.Panel data,a combination of 1.&2.The data may b
16、e quantitative(e.g.exchange rates,stock prices),or qualitative.Examples of time series dataSeriesFrequencyGDP or unemploymentyear,quarterly or monthlygovernment budget deficitannuallymoney supplyweeklyvalue of a stock market indexas transactions occur,2009.11 Huazhong University of Science and Techn
17、ology,15,Types of Data,Problems that Could be Tackled Using a Time Series Data-How the value of a countrys stock index has varied with that countrys macroeconomic policy.-How a companys stock price has varied when it announced the value of its dividend payment.-The effect on stock price of an increa
18、se in countrys interest rateCross-sectional data(横截面数据)are data on one or more variables collected at a single point in time,e.g.-Cross-section of stock returns on the New York Stock Exchange-A sample of bond credit ratings for UK banks,2009.11 Huazhong University of Science and Technology,16,Types
19、of Data and Notation,Problems that Could be Tackled Using a Cross-Sectional Data-The relationship between company size and the return to investing in its shares-The relationship between a countrys GDP level and the probability that the government will default on its sovereign debt.（主权债务）Panel Data（平
20、行数据，面板数据）has the dimensions of both time series and cross-sections,e.g.the daily prices of a number of blue chip stocks over two years.It is common to denote each observation by the letter t and the total number of observations by T for time series data,and to denote each observation by the letter i
21、 and the total number of observations by N for cross-sectional data.,2009.11 Huazhong University of Science and Technology,17,It is preferable not to work directly with asset prices,so we usually convert the raw prices into a series of returns.*There are two ways to do this:Simple returns or continu
22、ously compounded returnswhere,Rt denotes the return at time t pt denotes the asset price at time t ln denotes the natural logarithmWe also ignore any dividend payments,or alternatively assume that the price series have been already adjusted to account for them.,1.4 Returns in Financial Modelling,200
23、9.11 Huazhong University of Science and Technology,18,There are a number of reasons for Log Returns:1.They have the nice property that they can be interpreted as continuously compounded returns（连续复合收益）。此时，收益的复合频率无关紧要，不同资产间的收益很容易加以比较2.多期连续复合收益就是单期复合收益的连续简单加总。e.g.if we want a weekly return and we have
24、 calculated daily log returns:r1=ln p1/p0=ln p1-ln p0 r2=ln p2/p1=ln p2-ln p1 r3=ln p3/p2=ln p3-ln p2r4=ln p4/p3=ln p4-ln p3r5=ln p5/p4=ln p5-ln p4 ln p5-ln p0=ln p5/p0,Log Returns,2009.11 Huazhong University of Science and Technology,19,A Disadvantage of using Log Returns,There is a disadvantage of
25、 using the log-returns.The simple return on a portfolio of assets is a weighted average of the simple returns on the individual assets:But this does not work for the continuously compounded returns.In the limit.,2009.11 Huazhong University of Science and Technology,20,1.5 Steps involved in the formu
26、lation of econometric models,1a Economic or Financial Theory(Previous Studies)1b Formulation of an Estimable Theoretical Model 2.Collection of Data 3.Model Estimation 4.Is the Model Statistically Adequate?No Yes Reformulate Model 5.Interpret Model 6.Use for Analysis,2009.11 Huazhong University of Sc
27、ience and Technology,21,补充例子,以著名的凯恩斯消费理论为例说明上述步骤（1）步骤:理论或假说的陈述：凯恩斯说：基本的心理定律是，平均而言，人们倾向于消费随着他们收入的增加而增加，但比不上收入增加的那么多。简言之，凯恩斯设想，边际消费倾向（MPC），即收入每变化一个单位的消费变化率，大于零而小于1。（2）步骤:消费数学模型的设定虽然凯恩斯假设了消费与收入之间有一正向的相关关系，但他并没有明确指出这两者之间的准确的函数关系。为简单起见，数理经济学家也许建议采用如下的凯恩斯消费函数形式：,2009.11 Huazhong University of Science and
28、Technology,22,2009.11 Huazhong University of Science and Technology,23,（）步骤：计量经济学模型,考虑经济变量之间的非准确关系，计量经济学家会把确定性的消费函数修改如下：其中u被称为干扰或误差项，是一个随机变量，它有良好定义的概率性质，干扰项u可用来代表所有未经指明的对消费有所影响的哪些因素。,2009.11 Huazhong University of Science and Technology,24,可把消费函数的计量经济模型描绘成像图1.2那样,2009.11 Huazhong University of Scien
29、ce and Technology,25,（4）步骤：获得数据,Y（个人消费支出）和X（国内总产值）数据，1980-1991，均以10亿1987年美元为单位,资料来源：Economic Report of the President总统经济报告，1993，Table B-2，p.350。,2009.11 Huazhong University of Science and Technology,26,（5）步骤：计量经济模型的估计,既然有了数据，下一步的工作就是估计消费函数中的参数，参数的估计将对消费函数赋予经验内容。利用回归分析的统计技术获得估计值。,2009.11 Huazhong Uni
30、versity of Science and Technology,27,（6）步骤：假设检验,如前所说，凯恩斯曾预期MPC是正的，但小于1.在我们的例子中，我们求得MPC约为0.72.但在把这一发现看作是对凯恩斯消费理论的认可之前，还要追问这一估计值是否充分地低于1，以使我们不再怀疑这个估计值仅是一次偶然的机会得来，或者怀疑我们用的数据太特殊了，换言之，0.72是不是在统计意义（statistically）上小于1？如果是，就可用来支持凯恩斯理论。,2009.11 Huazhong University of Science and Technology,28,（7）步骤：预报或预测,为了说
31、明起见，假定实际GDP在1994年的预期未来值是60万美元，问1994年的预期消费支出是多少？如果我们认为在1994年消费函数仍然有效，这个答案就是：所估计的模型还有另一用途。假若政策改变，投资有所下降，其对经济的影响将如何？宏观经济理论告诉我们，投资支出每改变1元，收入的改变由收入乘数（M）给出。,2009.11 Huazhong University of Science and Technology,29,（8）步骤：利用模型进行控制或制定政策,假若我们已估计出凯恩斯消费函数，而且政府认为4万亿美元的（消费）支出水平即可维持当前约6.5%的失业率（1994年4月美国劳工统计局做出的估计）
32、，问什么收入水平将保证消费支出的这一目标值？4000=-231.8+0.7194X X=5882（近似值）就是说，给定约为0.72的一个MPC，58820（亿）美元的收入水平。上述计算提示我们，一个已估计出来的模型可服务于控制或政策的目的。通过适当的财政与货币政策的配合，政府可操纵控制度量（control Variable）X以产生目标变量（target variable）Y的指望水平。,2009.11 Huazhong University of Science and Technology,30,小结上述步骤,剖析了经典计量经济学的建模方法经济理论理论的数学模型理论的计量经济模型数据计量经
33、济模型的估计假设检验预报或预测利用模型进行控制或制定政策,2009.11 Huazhong University of Science and Technology,31,1.Does the paper involve the development of a theoretical model or is it merely a technique looking for an application so that the motivation for the whole exercise is poor?2.Is the data of“good quality”?Is it from
34、 a reliable source?Is the size of the sample sufficiently large for the model estimation?3.Have the techniques been validly applied?Have tests been conducted for possible violations of any assumptions made in the estimation of the model?,1.6 Points to Consider when reading a published paper,2009.11
35、Huazhong University of Science and Technology,32,4.Have the results been interpreted sensibly?Is the strength of the results exaggerated?Do the results relate to the questions posed by the authors?5.Are the conclusions drawn appropriate given the results,or has the importance of the results of the p
36、aper been overstated?,Points to Consider when reading empirical finance papers,2009.11 Huazhong University of Science and Technology,33,1.7 Econometric packages for modelling financial data,what packages are available?EVIEWS(menu-driven);RATS(command-driven)GAUSS;LIMDEP;MATLAB;SAS:SHAZAM;SPSS;TSP*RA
37、TS*EVIEWS,2009.11 Huazhong University of Science and Technology,34,Accomplishing simple tasks using EViews,1.Creating a workfile and importing data2.Verifying the data3.Transformations(new variable“A,B,G”,old variable“Z”)A=Z/2 B=Z*2 C=Z2 D=LOG(Z)E=EXP(Z)F=Z-1 G=LOG(Z/Z-1)4.Computing summary statisti
38、cs5.Plots 6.Printing results7.saving data results and workfile,2009.11 Huazhong University of Science and Technology,35,1.8 Outline of the remainder of this book,Chapter 2：the classical linear regression modelChapter 3：further development and analysis of the classical linear regression modelChapter
39、4.Classical linear regression model assumptions and diagnostic tests.,2009.11 Huazhong University of Science and Technology,36,Outline,Chapter 5:univariate time series modelling and forecastingChapter 6:Multivariate modelsChapter 7:Modelling long-run relationships in financeChapter 8:Modelling volat
40、ility and correlation,2009.11 Huazhong University of Science and Technology,37,Outline,Chapter 9:Switching modelsChapter 10:Panel dataChapter 11:Limited dependent variable modelsChapter 12:Simulation methods,2009.11 Huazhong University of Science and Technology,38,Outline,Chapter 13:Conducting empir
41、ical research or doing a project or dissertation in financeChapter 14:Recent and future developments in the modelling of financial time seriesAppendix 1:A review of some fundamental mathematical and statistical conceptsAppendix 2 Tables of statistical distributionsAppendix 3 Sources of data used in this book,
