FINANCIAL TIME-SERIES ECONOMETRICS.ppt

《FINANCIAL TIME-SERIES ECONOMETRICS.ppt》由会员分享，可在线阅读，更多相关《FINANCIAL TIME-SERIES ECONOMETRICS.ppt（24页珍藏版）》请在得力文库 - 分享文档赚钱的网站上搜索。

1、FINANCIAL TIME-SERIES ECONOMETRICSINTRODUCTIONContents 1. Models,Data and Process The nature of the econometric approach The Process of an econometric analysis 2. Applications of Financial Econometrics Dynamic effects of various shocks Empirical finance Refining data 3. Key Features of Financial Tim

2、e Series The regression model Time series models Dynamic model 4. Contents of Time Series Modeling Stationary stochastic time series model Nonstationary stochastic process Multiple time series modeling Time series models of heteroskedasticity State space model 5. Text and Software Text Software 6. S

3、ome Basic Tools Difference equations and their solutions Solution methodology Stability conditions Impulse response function The basics of time series analysis software 7. Summary and Conclusions Appendix: TSP Program to Accompany Chapter 1 Box: Empirical Research on Exchange Rate Bibliography1. MOD

4、ELS, DATA AND PROCESS The Nature of The Econometric Approach structural analysis evaluation forecasting The Process of An Empirical Analysis model specification structural equations and reduced forms parameters conditions sampling and refining data Identification and estimation statistical test econ

5、omic interpretationTheoryFactsModelDataStatistical TheoryEconometric TheoryRefined DataEconometric TechniquesEstimation of Econometric Model with the Refined Data Using Econometric TechniquesEvaluationForecastingStructural AnalysisEconometric Approach Structural Analysis Econometric Model Linear mod

6、el Greene (2000) Nonlinear model* Davidson Mackinnon (1993) Static model Time series model Enders （1995） Dynamic model Christian Gourieroux (1997) Structure Change （Maddala and Kim,1998) Chow test Time-varying parametersEvaluation The Simulation Approach Identification Limited-information estimation

7、 Full-information estimation Monte Carlo studies Other Approaches The Instruments-targets approach The Social-welfare-function approachForecasting Forecasting Methods Sample information Economic theory Introduction to Forecasting Techniques Time series model (ARIMA,GARCH,KALMAN-filter) Statistical m

8、odel (Monte Carlo techniques,MSFE) Data and Refining Type Quantitative versus qualitative data Time-series versus cross-section data (Panel Data) Non-experimental versus experimental data Micro versus macro data Nature Degrees of freedom Multicollinearity Serial correlation Structural change Errors

9、in measurement Non-stationary Source IMF international financial statistics (CD-ROM) 2. APPLICATIONS OF FINANCIAL ECONOMETRICS Dynamic Effects of Various Shocks Transmission mechanism of financial crisis Credit channel of policy Empirical Finance Forecasting(price of capital assets, risk premium,etc

10、.) Predictability of asset returns Market microstructure Term structure Financial integration Refining Data Missing data Base changes (GDP,M1,etc.) Nonstationary (EX,IR,etc.)3. KEY FEASURES OF FINANCIAL TIME SERIES The Regression Model The Method of ordinary least squares Assumption (disturbance ter

11、m;observations, independent variables) The Gauss-Markov theorem (BLUE,consistency) Other methods of estimation Maximum likelihood Moments Bayesian approach The Probability distribution for OLS estimator Parameters and disturbance term t,F,P tests and significance (confidence intervals) Applications

12、(structural break,prediction,model selection) Extensions Diagnosis and treatment)(tttuxy Time Series Models Differences between LRM and TSM Exogenous variables,sequence,theory Components Trends Seasonality Cycle Irregularity (convergence) Conditional heteroskedasticity (volatility) Non-linearity (st

13、ate dependency) Determinants Function structure: Lag order: Dynamic Model Transfer process (impulse response function),.,(21tpttttuxxxfxfp),.,(21tptttttuyyyxfy4. CONTENTS OF TIME SERIES MODELING Stationary Stochastic Time Series Model ARMA ARIMA Nonstationary Stochastic Process Unit root test Cointe

14、gration and error correction model Multiple Time Series Modeling VAR Granger test Structural VAR Time Series Models of Heteroskedasticity ARCH GARCH State Space Model KALMAN filter Regime switching modelOther Useful Financial Econometric Models Methods of Instrumental Variables GMM Discrete and Limi

15、ted Dependent Variable Models Probit,logit and tobit models Computationally Intensive Methods Monte Carlo methods The bootstrap Permutation test Nonparametric and semiparametric estimation Panel Data Analysis Survival Data Analysis Event-Study Analysis5. TEXT AND SOFTWARE Text Enders,Walter. (1995)

16、Applied Econometric Time Series. John Wiley & Sons,Inc. TSP (Ver.4.4) Reference Manual (1997) Greene,William H. (2000) Econometrics Analysis.4th ed. Prentice-Hall International,Inc. Software (http:/emlab.berkeley.edu) TSP,SHAZAM,RATS GAUSS,S-PLUS SPSS,SAS,STATA Mathematica,Excel6. SOME BASIC TOOLS D

17、ifference Equations and Their Solutions The special form of nth-order linear difference equation The special form of the forcing process The solution form of difference equations Solution Methodology Iteration (e.g. first-order) With initial condition:forward from the specific period Without initial

18、 Condition: backward to infinity tniitituyaay100iititu Ctfytt,)(0y)(i)(101011010tiitittiitayaaay Structural decomposition methods e.g. General solution: Homogeneous solution Characteristic equation and characteristic root Particular solution (challenge solution) (1)Method of undetermined coefficient

19、sthtAyd 0thtthtAytyd;0)cos(021trydtht)(2/)cos(;)(2/1212/12aaar4)(221aadsptdpthttyyyycyudptdt 00iitispttstyuttttuyayaay22110)(stdttuuu (2)Lag operators for , then for , then Stability Conditions Inside unit circle Necessary condition: Sufficient condition: Unit root process Unit root exit, if Impulse

20、 Response Function The effect of stochastic shock:)(ittiyyL1a)1/()1 (3322aLyyLaLaaLtt1a01)()()1/(itityaLaLaLy11niia11niia11niia),(1Ctgptnt The Basics of Time Series Analysis Software Starting and quitting Interactive mode batch mode Fundamental program structure and some important commands Construct

21、ing and manipulating data Data set-up(frequency,numbers) Data input(external file;format;subsets) Data transformation(dynamic equation;order change) Refining data(seasonality,etc.) Descriptive statistics(mean,variance,correlation,etc.) Data output(print,plot,output,type,etc.) Linear regression analy

22、sis Analysis command(OLS) The interpretation of the test statistics The economical implication of empirical results7. SUMMARY AND CONCLUSIONSEconometrics utilizes economic theory,facts(data) and statistical techniques,to measure and to test certain relationships among economic variables,thereby givi

23、ng these results to economic reasoning.Empirical finance provides analytical tools needed to examines the behavior of financial markets.Topics covered include estimating the dynamic impact multiplier of financial shocks,forecasting the value of capital assets,measuring the volatility of asset return

24、s, testing the financial integration, and more.Time-series econometrics is concerned with the estimation of difference equations containing stochastic components. These solution can be divided into two parts: a homogeneous portion and particular portion .The former is especially important in that it

25、 yields the characteristic roots which determine the system stability,the latter will be solved by the use of lag operators.This chapter introduces some basic concepts of the soft used to time series analysis and describes commands for setting up observations, reading data,making transformation,and

26、illustrating OLS estimation method. Appendix : TSP Programs to Accompany IntroductionOPTIONS CRT;? Monetary Approach to Exchange RateFREQ M;SMPL 80 :1,90:12;LOAD(FILE=C:DATAEXCISE1.XLS);PRINT SJA MJA IJA YJA MGE IGE YGE;? Data statistic descriptionMSD(CORR,COVA)MJA MGE IJA IGE;? Data transformations

27、 SJAGE=SJA/SGE;LOGSJAGE=LOG(SJAGE);LOGM=LOG(MJA)-LOG(MGE);DI=IJA-IGE;LOGY=LOG(YJA)-LOG(YGE);PLOT LOGM * LOGY +;PLOT DI %; ? Empirical analysis (technique:OLS)OLSQ LOGSJAGE C LOGM DI LOGY;ESLSJAGE=FIT;ESRES=RES;PLOT LOGSJAGE + ESLSJAGE*;PLOT ESRES %;END;Box: Empirical research on Exchange Rate Assump

28、tion: (a) perfect substitutes in consumer demand functions (b) perfect substitutes between domestic and foreign bonds (c) domestic and foreign elasticities are equal Model: (1) (2) (3) (4) (5) tttttiypmttttppstttttuiiyymms)()()(tttttssEii)()(1ttttttEyymms1)()()()(tttttiypmBibliographyCampell,J.Y., L

29、o,A.W. and MacKinlay,A.C. (1997) The Econometrics of Financial Markets. Princeton University Press.Frankel,J. A. and A.K.Rose (1995) “Empirical research on nominal exchange rates.” In G.M.Grossman and K.Rogoff,eds., Handbook of international economics, vol.3. Amsterdam:North Holland.Hodrick, R. (1978) “An empirical analysis of the monetary approach to the determination of the exchange rate.” In J.Frenkel and H.G.Johnson,eds., The Economics of Exchange Rates, Addison-Wesley.