1、1-1,金融计量经济学导论,讲授：陈 磊 电话：84712508E-mail: ,1-2,学习要求与建议,作为理性人，应追求课堂收益最大化 课堂讲授+课下自学（最好课前预习） 阅读参考书 及时做习题 熟悉相关软件的使用,1-3,引 言,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“是一门具有高度实证性的科学”，“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，即以模型为基础的统计推断。 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技术 缺少金融计量经济学方面的适当教科书,1-4,Introductory Eco
2、nometrics for Finance,Chris Brooks,1-5,作者简介,Chris was formerly Professor of Finance at the ISMA Centre, University of Reading, where he also obtained his PhD and BA in Economics and Econometrics. His areas of research interest include econometric modelling and forecasting, risk measurement, asset ma
3、nagement, and property finance.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. Chris is Associate Editor of several journals,
4、 including the International Journal of Forecasting.,1-6,本书的特点,内容广泛：包含了与金融领域相关的各种经济计量方法 难度适中：不要求具备很多的数学知识 注重应用：提供相关软件的使用和金融方面的应用实例 最新版本：英国剑桥大学出版社2002年出版 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,1-7,其它参考教材,各种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 各种时间序列分析方面的
5、教科书； G.E.Box 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； T.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。 为金融市场的研究者提供从事金融时间序列的经验分析所必需的技术 J.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。 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
6、实证分析方法和理论前沿。,1-8,Chapter 1,Introduction,1-9,1.1 Introduction: The Nature and Purpose of Econometrics,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。 Definition of financial econometrics:The application of st
7、atistical and mathematical techniques to problems in finance.,1-10,金融计量经济学的用途,检验金融理论 确定资产价格或收益 检验关于变量之间关系的假设 考察经济景气的变化对金融市场的影响 预测金融变量的未来走势,1-11,Examples of the kind of problems that may be solved by an Econometrician,1. Testing whether financial markets are weak-form informationally efficient.(根据资产价
8、格的历史数据检验资产收益的可预测性) 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 re
9、lationships between prices and exchange rates,1-12,Examples of the kind of problems that may be solved by an Econometrician,6. Testing the hypothesis that earnings or dividend announcements have no effect on stock prices. 7. Testing whether spot or futures markets react more rapidly to news. 8.Forec
10、asting the correlation between the returns to the stock indices of two countries.,1-13,宏观经济计量分析的数据问题： 小样本；测量误差与数据修正 金融数据的观测频率高，数据量大 金融数据的质量高 这些意味着可以采用更强有力的分析技术，研究结果也更可靠。 金融数据包含很多噪音（noisy），更难以从随机的和无关的变动中分辨出趋势和规律 通常不满足正态分布 高频数据经常包含反映市场运行方式的、但人们并不感兴趣的其它模式(pattern) ，需要在建模时加以考虑,1.2 The Special Characteri
11、stics of Financial Data,1-14,1.3 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 be quantitative (e.g. exchange rates, stock prices), or qualitative (e.g. day of the week). Examples of time series dataSeries Freq
12、uencyGNP or unemployment monthly, or quarterlygovernment budget deficit annuallymoney supply weeklyvalue of a stock market index as transactions occur,1-15,Types of Data,Problems that Could be Tackled Using a Time Series Regression- How the value of a countrys stock index has varied with that countr
13、ys macroeconomic fundamentals.- How the value of a companys stock price has varied when it announced the value of its dividend payment.- The effect on a countrys currency of an increase in its interest rate Cross-sectional data(截面数据) are data on one or more variables collected at a single point in t
14、ime, e.g.- Cross-section of stock returns on the New York Stock Exchange- A sample of bond credit ratings for UK banks,1-16,Types of Data and Notation,Problems that Could be Tackled Using a Cross-Sectional Regression- The relationship between company size and the return to investing in its shares- T
15、he 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
16、 each observation by the letter t and the total number of observations by T for time series data, and to to denote each observation by the letter i and the total number of observations by N for cross-sectional data.,1-17,It is preferable not to work directly with asset prices, so we usually convert
17、the raw prices into a series of returns. * There are two ways to do this:Simple returns or log returnswhere, Rt denotes the return at time tpt denotes the asset price at time tln denotes the natural logarithm We also ignore any dividend payments, or alternatively assume that the price series have be
18、en already adjusted to account for them.,1.4 Returns in Financial Modelling,1-18,There are a number of reasons for this: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 we
19、ekly return and we have calculated daily log returns:r1 = ln p1/p0 = ln p1 - ln p0r2 = ln p2/p1 = ln p2 - ln p1r3 = ln p3/p2 = ln p3 - ln p2r4 = ln p4/p3 = ln p4 - ln p3r5 = ln p5/p4 = ln p5 - ln p4ln p5 - ln p0 = ln p5/p0,Log Returns,1-19,There is a disadvantage of using the log-returns. The simple
20、 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.（对数运算是一种非线性变换） 随着数据取样频率的增加，极限情况下，简单复合收益和连续复合收益是相等的。,A Disadvantage of using Log Returns,1-20,1.5 Steps involved in the formulation of e
21、conometric models,1a Economic or Financial Theory (Previous Studies) 1b Formulation of an Estimable Theoretical Model 2. Collection of Data3. Model Estimation 4. Is the Model Statistically Adequate? No Yes Reformulate Model 5. Interpret Model 6. Use for Analysis,1-21,金融/经济计量学的研究方法,模型设定：对经济现象或过程的一种数学
22、模拟。把经济变量之间的关系用适当的数学关系式表达出来。 要有科学的理论依据 选择适当的数学形式：单一方程/联立方程； 方程中的变量应具有可观测性建立模型既是一门科学，又是一种艺术。 参数估计：如何通过样本观测数据正确的估计总体模型的参数，是计量经济学的核心内容。 参数估计的方法：普通/广义最小二乘法，极大似然估计法，二阶段/三阶段最小二乘法,1-22,金融/经济计量学的研究方法,模型检验 经济意义的检验 统计推断检验：检验参数估计的可靠性，模型的拟合优度等 计量经济学检验：模型是否符合计量经济方法的基本假定，如多重共线性，模型扰动项是否存在自相关和异方差性等。 预测检验 模型应用 经济结构分析
23、 经济预测 政策评价,1-23,1. Does the paper involve the development of a theoretical model or is it merely a technique looking for an application, or an exercise in data mining?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
24、?3. Have the techniques been validly applied? Have diagnostic tests been conducted for possible violations of any assumptions made in the estimation of the model?,1.6 Some Points to Consider when reading a published paper,1-24,4. Have the results been interpreted sensibly? Is the strength of the res
25、ults 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?,Some Points to Consider when reading empirical finance papers,1-25,1.7 内容概要,第二章：经济计量学软件包 Eviews
26、 和 RATS 的使用方法。第三章：古典线性回归模型。 最小二乘估计；假设检验。第四章：线性回归模型的有关问题 线性回归模型的拟合优度和诊断检验； 不满足模型假设条件的后果及其补救方法； 一般到特殊的建模方法。,1-26,内容概要,第五章：单变量时间序列模型 一些标准的随机过程模型的性质； 模型的选择、估计和检验 预测及其评价 第六章：多变量时间序列模型 联立方程模型的估计方法 向量自回归（VAR）模型 VAR的解释：约束条件检验，因果性检验，脉冲响应，方差分解 第七章：建模长期关系 单位根过程和时间序列的非平稳性检验 协整及其检验，误差修正模型,1-27,内容概要,第八章：建模波动性和相关性
27、 金融时间序列的非线性问题 ARCH模型 ARCH模型的扩展 第九章：转换模型 Markov转换模型 门限自回归模型 第十章：模拟方法 Monte Carlo模拟 Bootstrapping方法,1-28,Chapter 2,Econometric packages for modelling financial data,1-29,常用的经济计量软件,EViews (Econometric Views) RATS (Regression Analysis of Time Series) SAS (Statistical Analysis System) SPSS (Statistical P
28、ackage for Social Science) TSP (Time Series Processor) GAUSS LIMDEP MATLAB SHAZAM,1-30,EViews,目前最流行的计量经济学软件。 主要功能 数据处理 绘图 统计分析 建模分析 预测 模拟 菜单驱动，操作简便、易学 广泛应用于经济、金融、保险、管理、商务等领域。,1-31,RATS (Regression Analysis of Time Series) software package is a leading econometrics/time-series analysis software packa
29、ge used worldwide by economists and others for analyzing time series and cross sectional data, developing and estimating econometric models, forecasting, and much more. RATS is a fast, efficient, and comprehensive time series analysis and econometrics software package. RATS makes simple tasks easy t
30、o accomplish, while its command-driven interface and extensive programmability also make it a very flexible and powerful tool for more complex applications.,RATS Econometrics Software,1-32,SPSS,SPSS has become a leader in predictive analytics technologies through a combination of commitment to innov
31、ation and dedication to customers. Throughout our history, we have produced predictive analytics software that enables our customers corporations, academic institutions, healthcare providers, and government agencies to better focus their operations. Predictive analytics connect data to effective act
32、ion by drawing reliable conclusions about current conditions and future events.,1-33,The GAUSS Mathematical and Statistical System,The GAUSS Mathematical and Statistical System is a fast matrix programming language widely used by scientists, engineers, statisticians, biometricians, econometricians,
33、and financial analysts. Designed for computationally intensive tasks, the GAUSS system is ideally suited for the researcher who does not have the time required to develop programs in C or FORTRAN but finds that most statistical or mathematical “packages“ are not flexible or powerful enough to perfor
34、m complicated analysis or to work on large problems. Whatever mathematical tool or language you are now using, youll find that GAUSS can greatly increase your productivity!,1-34,LIMDEP is an integrated program that is unsurpassed in the breadth and variety of its estimation tools for estimation and
35、analysis of linear and nonlinear models with cross section, time series and panel data. LIMDEP Version 8.0 is a major expansion of our premier software for estimation of regression models and nonlinear models for limited dependent variables, survival data(生存数据), qualitative choices, count data, stoc
36、hastic frontiers（边界） and samples subject to nonrandom selection. Over 100 different models are supported, including an unparalleled list of formulations for panel data. No other software is as up to date, fast, accurate, and easy to use.,LIMDEP,1-35,MATLAB,MATLAB is an intuitive language and a techn
37、ical computing environment. It provides core mathematics and advanced graphical tools for data analysis, visualization, and algorithm and application development. With more than 600 mathematical, statistical, and engineering functions, engineers and scientists rely on the MATLAB environment for thei
38、r technical computing needs. Introduced in 1984, MATLAB is a technical computing and application development environment used today by more than 500,000 engineers and scientists and by more than 2,000 financial companies worldwide. Financial professionals rely on MATLAB to accelerate their research,
39、 shorten analysis and development time, and reduce project costs.,1-36,SHAZAM,SHAZAM is a computer package for econometric and statistical computing. SHAZAM offers a comprehensive set of econometric methods for model estimation and testing. The current version is Version 9. SHAZAM has thousands of u
40、sers in more than 85 countries. It is used in undergraduate and graduate teaching as well as for research published in academic journals. SHAZAM is also used by government and industry. SHAZAM is a command language system. The user prepares a SHAZAM program in a command file. SHAZAM processes the co
41、mmand file and produces an output file of results.,1-37,一些相关的参考书,张晓峒主编，计量经济学软件EViews使用指南，南开大学出版社2003年7月出版； 易丹辉主编，数据分析与EViews应用 ，中国统计出版社2002年10月出版； 朱世武著，基于SAS系统的金融计算，清华大学出版社2004年5月； 金浩编著，经济统计分析与SAS应用，经济科学出版社，2002年9月出版； 王吉利 等，SAS软件与应用统计，中国统计出版社，2000年9月出版。,3-38,Chapter 3,A brief overview of the classic
42、al linear regression model,3-39,1 Regression,Regression is probably the single most important tool at the econometricians disposal.What is regression analysis? It is concerned with describing and evaluating the relationship between a given variable (usually called the dependent variable) and one or
43、more other variables (usually known as the independent variable(s). 回归是试图用自变量的变动来解释因变量的变化。,3-40,Some Notation,Denote the dependent variable by y and the independent variable(s) by x1, x2, . , xk where there are k independent variables. Some alternative names for the y and x variables:y xdependent va
44、riable independent variablesregressand regressorseffect variable causal variables explained variable explanatory variable Note that there can be many x variables but we will limit ourselves to the case where there is only one x variable to start with. In our set-up, there is only one y variable.,3-4
45、1,2 Regression is different from Correlation,If we say y and x are correlated, it means that we are treating y and x in a completely symmetrical way. In regression, we treat the dependent variable (y) and the independent variable(s) (xs) very differently. The y variable is assumed to be random or “s
46、tochastic” in some way, i.e. to have a probability distribution. The x variables are, however, assumed to have fixed (“non-stochastic”) values in repeated samples. Regression as a tool is more flexible and powerful than correlation,3-42,3 Simple Regression,For simplicity, say k=1. This is the situat
47、ion where y depends on only one x variable. Examples of the kind of relationship that may be of interest include: How asset returns vary with their level of market risk Measuring the long-term relationship between stock prices and dividends. Constructing an optimal hedge ratio（套期比）,3-43,Simple Regre
48、ssion: An Example,Suppose that we have the following data on the excess returns on a fund managers portfolio (“fund XXX”) together with the excess returns on a market index: We therefore want to find whether there appears to be a relationship between x and y given the data that we have. The first st
49、age would be to form a scatter plot of the two variables.,3-44,Graph (Scatter Diagram),3-45,Finding a Line of Best Fit,We can use the general equation for a straight line, y=a+bx to get the line that best “fits” the data. However, this equation (y=a+bx) is completely deterministic. Is this realistic
50、? No. So what we do is to add a random disturbance term, u into the equation. yt = + xt + ut where t = 1,2,3,4,5,3-46,Why do we include a Disturbance term?,The disturbance term can capture a number of features:- We always leave out some determinants of yt- There may be errors in the measurement of yt that cannot be modelled.- Random outside influences on yt which we cannot model,
