金融计量经济学

Econometrics For Finance-Chapter 1Econometrics for FinanceEconometrics for Finance 金融计量经济学金融计量经济学讲授：薛明皋讲授：薛明皋 电话：电话：13554398877E-mail: 1Econometrics For Finance-Chapter 1课程目标课程目标n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.n金融学的快速发展使它已成为一门相对独立的学科。n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”.n金融经济学家进行推断的基本方法是金融计量经济学，即以模型为基础的统计推断。2Econometrics For Finance-Chapter 1教材教材nIntroductory Econometrics for Financen Chris BrooksnCambridge University Press 20082009.11 Huazhong University of Science and Technology3Econometrics For Finance-Chapter 1作者简介作者简介nChris Brooks was formerly Professor of Finance at the ISMA Centre, University of Reading, where he also obtained his PhD and BA in Economics and Econometrics. nHis areas of research interest include econometric modeling and forecasting, risk measurement, asset management, and property finance.n He has published over sixty articles in leading academic and practitioner journals, including the Journal of Business, the Journal of Banking and Finance, Journal of Empirical Finance, Oxford Bulletin and Economic Journal. nChris is Associate Editor of several journals, including the International Journal of Forecasting. 4Econometrics For Finance-Chapter 1本书的特点n内容广泛：包含了与金融领域相关的各种经济计量方法n难度适中：不要求具备很多的数学知识n预备知识n数学：微积分和线性代数基础，统计学基础n金融：公司金融、金融市场、投资等方面的基础知识n注重应用：提供相关软件的使用和金融方面的应用实例5Econometrics For Finance-Chapter 1其它参考教材其它参考教材n经济计量学方面的教科书；n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nJ.M.伍德里奇,计量经济学导论现代观点，人民大学出版社n时间序列分析方面的教科书；nG.E.Box 等时间序列分析预测与控制，中国统计出版社n有关金融市场学、公司金融等方面的教科书；nT.C.Mills，1999, The Econometric 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。nJ.Y.Campbell 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。n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。6Econometrics For Finance-Chapter 1Chapter 1Introduction7Econometrics For Finance-Chapter 1Learning OutcomesnIn this chapter, you will learn how ton Distinguish between different types of datan Describe the steps involved in building an econometric modeln Calculate asset price returnsn Construct a workfile, import data and accomplish simple tasks in EViews2009.11 Huazhong University of Science and Technology8Econometrics For Finance-Chapter 11.1 What is Econometrics?nLiteral 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）nDefinition of financial econometrics:The application of statistical and mathematical techniques to study problems in finance.9Econometrics For Finance-Chapter 1the value of financial econometricsnTesting theories in financenDetermining asset prices or returnsnTesting hypotheses concerning the relationships between variables nExamining the effect on financial markets of changes in economic conditionsnForecasting future values of financial variables and for financial decision-making. 10Econometrics For Finance-Chapter 1Examples of some problems that may be solved by an Econometrician1. Testing whether financial markets are weak-form informationally efficient.2. Testing whether 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 exchange rates 11Econometrics For Finance-Chapter 1Examples 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 earnings 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.12Econometrics For Finance-Chapter 1Financial data often 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) almost always not normally distribution. 1.2 Is financial econometrics different from economic econometrics?13Econometrics For Finance-Chapter 1 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 be 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 Technology14Econometrics For Finance-Chapter 1Types 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 increase in countrys interest rateCross-sectional data(横横截面数据截面数据) 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 banks2009.11 Huazhong University of Science and Technology15Econometrics For Finance-Chapter 1Types 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）（主权债务）Panel Data （平行数据，面板数据）（平行数据，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 and the total number of observations by N for cross-sectional data.2009.11 Huazhong University of Science and Technology16Econometrics For Finance-Chapter 1nIt is preferable not to work directly with asset prices, so we usually convert the raw prices into a series of returns. n* There are two ways to do this: Simple returns or continuously compounded returns where, Rt denotes the return at time t pt denotes the asset price at time t ln denotes the natural logarithmnWe 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%10011ttttpppR%100ln1tttppR2009.11 Huazhong University of Science and Technology17Econometrics For Finance-Chapter 1nThere 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（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合频率无关紧要，不同资产间的收益很容易加以比较2. 2. 多期连续复合收益就是单期复合收益的连续简单加总。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 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/p0Log Returns2009.11 Huazhong University of Science and Technology18Econometrics For Finance-Chapter 1A Disadvantage of using Log ReturnsnThere is a disadvantage of using the log-returns. The simple return on a portfolio of assets is a weighted average of the simple returns on the individual assets: nBut this does not work for the continuously compounded returns.nIn the limit. Rw RptipitiN1)0(trRtt2009.11 Huazhong University of Science and Technology19Econometrics For Finance-Chapter 11.5 Steps involved in the formulation 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 Science and Technology20Econometrics For Finance-Chapter 1补充例子补充例子n以著名的凯恩斯消费理论为例说明上述步骤以著名的凯恩斯消费理论为例说明上述步骤n（1）步骤步骤:理论或假说的陈述：理论或假说的陈述：凯恩斯说：基本的心理定律凯恩斯说：基本的心理定律是，平均而言，人们倾向于消费随是，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（简言之，凯恩斯设想，边际消费倾向（MPC），即收入每变化一），即收入每变化一个单位的消费变化率，大于零而小于个单位的消费变化率，大于零而小于1。（2）步骤步骤: 消费数学模型的设定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：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 Technology21Econometrics For Finance-Chapter 110 221XY数。分别代表截距和斜率系和参数的收入，而被称为模型消费支出，其中21XY2009.11 Huazhong University of Science and Technology22Econometrics For Finance-Chapter 1（）步骤（）步骤：计量经济学模型计量经济学模型n考虑经济变量之间的非准确关系，计量经济学家会把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：确定性的消费函数修改如下：其中其中u被称为干扰或误差项，是一个随机变量，它有良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，干扰项好定义的概率性质，干扰项u可用来代表所有未经指明可用来代表所有未经指明的对消费有所影响的哪些因素。的对消费有所影响的哪些因素。XY212009.11 Huazhong University of Science and Technology23Econometrics For Finance-Chapter 1n可把消费函数的计量经济模型描绘成像图可把消费函数的计量经济模型描绘成像图1.2那样那样2009.11 Huazhong University of Science and Technology24Econometrics For Finance-Chapter 1（4 4）步骤：步骤：获得数据获得数据年年YX19802447.13776.319812476.93843.119822503.73760.319832619.43906.619842746.14148.519852865.84279.819862969.14404.519873052.24539.919883162.44718.619893223.34838.019903260.44877.519913240.84821.0Y（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 Technology25Econometrics For Finance-Chapter 1（5 5）步骤：步骤：计量经济模型的估计计量经济模型的估计n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得估计值。2009.11 Huazhong University of Science and Technology26Econometrics For Finance-Chapter 1（6 6）步骤步骤：假设检验假设检验n如前所说，凯恩斯曾预期如前所说，凯恩斯曾预期MPC是正的，但小于是正的，但小于1.在我在我们的例子中，我们求得们的例子中，我们求得MPC约为约为0.72.但在把这一发现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估计值是否充分地低于1，以使我们不再怀疑这个估计，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，太特殊了，换言之，0.72是不是在统计意义是不是在统计意义（statistically）上小于）上小于1？如果是，就可用来支持凯？如果是，就可用来支持凯恩斯理论。恩斯理论。2009.11 Huazhong University of Science and Technology27Econometrics For Finance-Chapter 1（7 7）步骤步骤：预报或预测预报或预测846.40)60(7196. 08 .231YMPCM11n为了说明起见，假定实际为了说明起见，假定实际GDP在在1994年的预期未来值年的预期未来值是是60万美元，问万美元，问1994年的预期消费支出是多少？如果年的预期消费支出是多少？如果我们认为在我们认为在1994年消费函数仍然有效，这个答案就是：年消费函数仍然有效，这个答案就是：n所估计的模型还有另一用途。假若政策改变，投资有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，投资支出每改变我们，投资支出每改变1元，收入的改变由收入乘数元，收入的改变由收入乘数（M）给出。）给出。2009.11 Huazhong University of Science and Technology28Econometrics For Finance-Chapter 1（8 8）步骤：步骤：利用模型进行控制或制利用模型进行控制或制定政策定政策n假若我们已估计出凯恩斯消费函数，而且政府认为假若我们已估计出凯恩斯消费函数，而且政府认为4万万亿美元的（消费）支出水平即可维持当前约亿美元的（消费）支出水平即可维持当前约6.5%的失的失业率（业率（1994年年4月美国劳工统计局做出的估计），问月美国劳工统计局做出的估计），问什么收入水平将保证消费支出的这一目标值？什么收入水平将保证消费支出的这一目标值？n4000=-231.8+0.7194Xn X=5882（近似值）（近似值）n就是说，给定约为就是说，给定约为0.72的一个的一个MPC，58820（亿）美（亿）美元的收入水平。元的收入水平。n上述计算提示我们，一个已估计出来的模型可服务于上述计算提示我们，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（合，政府可操纵控制度量（control Variable）X以产以产生目标变量（生目标变量（target variable）Y的指望水平。的指望水平。2009.11 Huazhong University of Science and Technology29Econometrics For Finance-Chapter 1小结上述小结上述步骤步骤n剖析了经典计量经济学的建模方法剖析了经典计量经济学的建模方法n经济理论n理论的数学模型n理论的计量经济模型n数据n计量经济模型的估计n假设检验n预报或预测n利用模型进行控制或制定政策2009.11 Huazhong University of Science and Technology30Econometrics For Finance-Chapter 11. 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 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 paper2009.11 Huazhong University of Science and Technology31Econometrics For Finance-Chapter 14. 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 paper been overstated? Points to Consider when reading empirical finance papers2009.11 Huazhong University of Science and Technology32Econometrics For Finance-Chapter 11.7 Econometric packages for modelling financial datanwhat packages are available?nEVIEWS (menu-driven); RATS (command-driven)nGAUSS; LIMDEP; MATLAB; nSAS: SHAZAM; SPSS ; TSPn* RATS n*EVIEWS2009.11 Huazhong University of Science and Technology33Econometrics For Finance-Chapter 1Accomplishing simple tasks using EViewsn1. Creating a workfile and importing datan2. Verifying the datan3. Transformations(new variable “A, B, G”, old variable “Z”)nA=Z/2 B=Z*2 C=Z2 D=LOG(Z) E=EXP(Z) nF=Z-1 G=LOG(Z/Z-1)n4. Computing summary statisticsn5. Plots n6. Printing resultsn7. saving data results and workfile2009.11 Huazhong University of Science and Technology34Econometrics For Finance-Chapter 11.8 Outline of the remainder of this booknChapter 2：the classical linear regression modelnChapter 3：further development and analysis of the classical linear regression modelnChapter 4. Classical linear regression model assumptions and diagnostic tests.2009.11 Huazhong University of Science and Technology35Econometrics For Finance-Chapter 1OutlinenChapter 5:univariate time series modelling and forecastingnChapter 6: Multivariate modelsnChapter 7: Modelling long-run relationships in financenChapter 8:Modelling volatility and correlation2009.11 Huazhong University of Science and Technology36Econometrics For Finance-Chapter 1OutlinenChapter 9:Switching modelsnChapter 10:Panel datanChapter 11:Limited dependent variable modelsnChapter 12:Simulation methods2009.11 Huazhong University of Science and Technology37Econometrics For Finance-Chapter 1OutlinenChapter 13:Conducting empirical research or doing a project or dissertation in financenChapter 14: Recent and future developments in the modelling of financial time seriesnAppendix 1:A review of some fundamental mathematical and statistical conceptsnAppendix 2 Tables of statistical distributionsnAppendix 3 Sources of data used in this book2009.11 Huazhong University of Science and Technology38