simple linear regression with financial applications

simple linear regression with financial applications -...

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M ODULE 5 S IMPLE L INEAR R EGRESSION W ITH F INANCIAL A PPLICATIONS
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2 C ONTENTS : M ODULE 5 1. Introduction 2. Model Specification 2.1 The Nature of Stochastic Functions 2.2 The Types of Mathematical Functions 2.3 The Choice of Variables 2.4 The Assumptions about the Error Terms 3. Estimation Procedures 3.1 Key properties of an estimator 3.2 The Ordinary Least Squares (OLS) Method 3.3 Estimating the Variance of the Error Terms 3.4 Maximum Likelihood Estimation 3.5 Estimation Problems 4. Model Evaluation 4.1 Correlation Analysis 4.2 The 't' Test of β 4.3 Measuring Different Types of Variation 4.4 The Coefficient of Determination 4.5 The Adjusted Coefficient of Determination 4.6 The Analysis of Variance Procedure 5. Forecasting with Regression Models 6. Finance Applications 6.1 Introduction 6.2 Estimating Betas 6.2.1 The Alternative Models 6.2.2 The Thin Trading Problem 6.3 A Financial Ratio Analysis Application 6.4 A Hedging Application Appendix – The secrets of hypothesis testing
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3 R EFERENCES Gujarati, Ch 1, 2, 3 and 5 Johnson and Di Nardo, Ch 1 Thomas, Ch 4, 5 and 6 Wooldridge Ch 1 and 2 Additional Useful References P.Barnes (1985), The Analysis and Use of Financial Ratios: A Review Article Journal of Business Finance and Accounting, Vol14(4) p 449 - 461. E.R.Berndt (1991), The Practice of Econometrics: Classic and Contemporary , Ch 2 T.J. Brailsford, R.W.Faff, Research Design Issues in the Estimation of Beta , Ch 4. and B.R.Oliver (1977) J.Doti and E.Adibi (1998) The Practice of Econometrics with EViews , Ch 4.3-4.4 M.Grinblatt and S.Titman (1998) Financial Markets and Corporate Strategy , Ch 5. M.Kritzman (1991) What Practitioners need to know about Regressions Financial Analysts Journal, May-June, p 12 - 15 B.McDonald and M.Morris (1985) The Functional Specification of Financial Ratios: An Empirical Examination , Accounting and Business Research, Summer, p 223 - 228. R.Ramananathan (1998) Introductory Econometrics (4e), Ch 3 T.Watsham and K.Parramore (1997) Quantitative Methods in Finance , Ch 6
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4 1. I NTRODUCTION We begin by examining the 4 stages of any econometric study. When discussing these four stages we will use what is called the Simple Linear Regression model. This is a model in which there is only one independent variable. For this module we will be using an artificial example which tries to predict leisure consumption given income. In simple statistics we could use the mean of leisure consumption to make predictions. A more sophisticated approach is to allow the mean to vary as a function of another variable. To do this we will have to determine an equation or model which in this case would tell us how the mean leisure consumption behaves as income changes. The first stage is to ' specify ' the model. After specifying or choosing a model we ' estimate ' the parameters and then we ' evaluate ' the results we have obtained. Once we are satisfied with the model we use it to produce ' forecasts '. At the specification stage we must state the type of function we will use and the variables we will include in the model. The most commonly used function is the simple linear function. In econometrics, however, we use what is called a stochastic linear function. We will
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This note was uploaded on 01/21/2012 for the course STAT 3008 taught by Professor C.y.yau during the Spring '11 term at CUHK.

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simple linear regression with financial applications -...

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