1-1
金融计量经济学导论
讲授：陈 磊
电话,84712508
E-mail,chenlei@dufe.edu.cn
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
Econometrics
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
management,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,
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 statistical 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 relationships between prices and
exchange rates
1-12Examples 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.Forecasting 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 Characteristics
of Financial Data
1-14
1.3 Types of Data
? There are 3 types of data,
1,Time series data
2,Cross-sectional data
3,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 data
Series Frequency
GNP or unemployment monthly,or quarterly
government budget deficit annually
money supply weekly
value 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 country’s stock index has varied with that
country’s macroeconomic fundamentals.
- How the value of a company’s stock price has varied when it
announced the value of its dividend payment.
- The effect on a country’s 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 time,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
- The relationship between a country’s 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 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 the raw prices into a series of returns,* There
are two ways to do this:
Simple returns or log returns
where,Rt denotes the return at time t
pt denotes the asset price at time t
ln denotes the natural logarithm
? We 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
%1 0 0
1
1 ???
?
?
t
tt
t p
ppR
%100ln
1
???
?
?
???
??
?t
t
t p
pR
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 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 p2
r4 = ln p4/p3 = ln p4 - ln p3
r5 = ln p5/p4 = ln p5 - ln p4
?????
ln p5 - ln p0 = ln p5/p0
Log Returns
1-19
? There 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:
? 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
R w Rpt ip it
i
N
?
?
?
1
1-201.5 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
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
– 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?
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 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?
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 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
– 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
金融计量经济学导论
讲授：陈 磊
电话,84712508
E-mail,chenlei@dufe.edu.cn
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
Econometrics
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
management,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,
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 statistical 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 relationships between prices and
exchange rates
1-12Examples 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.Forecasting 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 Characteristics
of Financial Data
1-14
1.3 Types of Data
? There are 3 types of data,
1,Time series data
2,Cross-sectional data
3,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 data
Series Frequency
GNP or unemployment monthly,or quarterly
government budget deficit annually
money supply weekly
value 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 country’s stock index has varied with that
country’s macroeconomic fundamentals.
- How the value of a company’s stock price has varied when it
announced the value of its dividend payment.
- The effect on a country’s 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 time,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
- The relationship between a country’s 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 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 the raw prices into a series of returns,* There
are two ways to do this:
Simple returns or log returns
where,Rt denotes the return at time t
pt denotes the asset price at time t
ln denotes the natural logarithm
? We 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
%1 0 0
1
1 ???
?
?
t
tt
t p
ppR
%100ln
1
???
?
?
???
??
?t
t
t p
pR
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 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 p2
r4 = ln p4/p3 = ln p4 - ln p3
r5 = ln p5/p4 = ln p5 - ln p4
?????
ln p5 - ln p0 = ln p5/p0
Log Returns
1-19
? There 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:
? 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
R w Rpt ip it
i
N
?
?
?
1
1-201.5 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
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
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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
– 经济预测
– 政策评价
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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?
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
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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
paper been overstated?
Some Points to Consider when reading
empirical finance papers
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1.7 内容概要
? 第二章：经济计量学软件包
– Eviews 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。
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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
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内容概要
? 第八章：建模波动性和相关性
– 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
