Coursebooks

Financial econometrics

FIN-407

Lecturer(s) :

Monfort Alain Maurice Etienne

Language:

English

Summary

The objective of this course is to present the main tools of financial econometrics and to show their relevance for prediction ,causality ,shock propagation , signal extraction , risk measure and asset pricing .

Content

 

1-STOCHASTIC PROCESSES: Moments, Stationarity, Autocorrelation and Partial autocorrelation functions, Estimation of autocorrelation and partial autocorrelation functions


2-ARMA, ARIMA MODELS: Lag operator, Autoregressive processes, Moving average processes, ARMA processes, ARIMA processes


3-PREDICTION WITH ARIMA MODELS: General principles of prediction, Prediction in ARIMA models, Prediction function and pivotal values, Prediction intervals


4-INFERENCE IN ARMA MODELS: Estimation, Tests and confidence regions, Validation, Model selection


5-EXOGENEITY AND CAUSALITY: Definition based on probability distributions, Causality measures, Causality tests , Examples


6-VECTOR AUTOREGRSSIVE (VAR) MODELS AND RESPONSE FUNCTIONS; Multivariate processes, Definition of a VAR, Estimation and tests in a VAR, Causality, Shock propagation, Impulse response function, Variacne decomposition, Structural shocks , Examples


7-STYLISED FACTS IN FINANCIAL TIME SERIES: Fat tails, Volatility clustering, Asymmetric response to shocks, Correlation of powers, Persistence, Co-volatility


8-UNIVARIATE ARCH-GARCH MODELS: Motivations, Different kinds of white noises, Definitions of ARCH and GARCH models, Stationarity, Coherence with stylized facts


9-GENERALIZATIONS OF UNIVARIATE GARCH MODELS: Regression models with GARCH errors, ARMA-GARCH models, GARCH-M models, Asymmetric response models,


10-INFERENCE IN GARCH TYPE MODELS: Inference under conditional normality, Inference under conditional Student assumption, Semi-parametric approach, Examples

11-MULTIVARIATE GARCH MODELS: Constant Conditional Correlation (CCC) models ,Dynamic Conditional Correlation (DCC) models ,Asymmetric Volatilty , Examples

12-KALMAN FILTER AND EXTENSIONS: Definition of a linear factor model, Kalman filter, Kalman smoother, Estimation and tests, Extended Kalman Filter of order 1, Extended Kalman Filter of order 2, Quadratic Kalman Filter


13-APPLICATIONS OF THE KALMAN FILTER: Value at Risk modeling, Multivariate Factor GARCH models, Stochastic volatility models.


14-HIDDEN MARKOV CHAINS: Markov chains, Switching regime models, Kitagawa-Hamilton algorithm, EM algorithm, Coding , Parameterization of the transition matrix , Application to stochastic volatility models.


15-DISCRETE TIME AFFINE PROCESSES
Laplace Transform, Affine processes, Examples, Multi-Horizon Laplace Transform,  Application to asset pricing .

 


Keywords

Econometrics, Finance 

Learning Prerequisites

Required courses

 Econometrics

 

Recommended courses

Introduction to finance

Important concepts to start the course

Basic linear algebra.

Basic probalilistic and statistical concepts.

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Lectures and exercise sessions

Expected student activities

Assessment methods

100% Final exam

Supervision

Office hours Yes
Assistants Yes
Forum No

Resources

Bibliography

Hamilton, J.D.(1994):"Time Series Analysis" , Princeton Univertsity Press

Gourieroux C. and Monfort A.(1996):"Time Series and Dynamic Models" ,Cambridge University Press

Frank C. and Zakoian J.M.(2010) :"Garch Model"s ,Wiley

Gourieroux C. and Monfort A,(1996): "Statistics and Econometric Models" ,(2 vol.),Cambridge University Press

Bertholon H.,Monfort A. and Pegoraro F. (2008): "Econometric Asset Pricing Modelling",Journal of Financial Econometrics ,4,407-458

Gourieroux C.

 

Ressources en bibliothèque

Prerequisite for

In the programs

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German