ASSET PRICING

Objective:

This course is an introduction to the modern theory of asset pricing and portfolio theory. It develops foundations for more specialized courses on securities valuation (e.g., derivatives pricing, continuous time finance, empirical estimation of asset pricing models, market microstructure etc...). Topics covered include (i) CAPM, mean-variance analysis, CCAPM, Arrow-Debreu pricing, factor pricing, arbitrage, (ii) asymmetric information and asset pricing, and (iii) derivative pricing in discrete time models.

Organization

1. The course is organized in 8 sessions of four hours.
2. Evaluation: Final Exam (open-book): 100% of the final grade. Final exam is planned on February,
19, 2013.
3. Presence is compulsory.

Texbooks
A good texbook for this course is: "Asset pricing" by George Pennachi, Pearson, 2008

Other useful references are given in the course outline below. Readings for each week are only recommended and not compulsory.

Slides of the lectures will be provided in advance.

Course Outline:
(is approximative and may be modified depending on time constraints)

FINANCIAL ECONOMETRICS

This course will familiarize the students with the technical tools of financial data analysis, with emphasis on asset pricing and time series analysis. The course will be accompanied by twelve hours of lab sessions for computer programming and applications.

BOOKS:
-Calvet, Laurent E., and Adlai J. Fisher (2008). Multifractal Volatility: Theory, Forecasting and Pricing. Elsevier – Academic Press. [CF]

-Campbell, John, Andrew Lo, and Craig MacKinlay (1996). The Econometrics of Financial Markets. Princeton University Press. [CLM]

-Gouriéroux, Christian, and Alain Monfort (1996). Simulation-Based Econometric Methods. Oxford University Press. [GM]

-Maronna, Ricardo A., R. Douglas Martin, and Victor J. Yohai (2006). Robust Statistics: Theory and Methods. Wiley, London. [MMY]


Course outline

1. Maximum Likelihood Estimation and Generalized Method of Moments

*CLM: Technical Appendix on Estimation Techniques
Hamilton, James (1994). Time Series Analysis. Princeton University Press, ch. 5 and 14.
Hansen, Lars (1982). “Large sample properties of generalized method of moments estimators.”
Econometrica 50, 1029-1054.

Newey, Whitney, and Daniel McFadden (1994). “Large sample estimation and hypothesis testing.”
In Handbook of Econometrics vol 4, Robert Engle and Daniel McFadden editors, Elsevier – North
Holland.

Newey, Whitney, and Kenneth West (1987). “A simple, positive semi-definite, heteroscedasticity and
autocorrelation consistent covariance matrix.” Econometrica 55, 703-708.


2. Regime-Switching Models

*Hamilton, James (1994), ch. 22.

*Hamilton, James (2008). “Regime-switching models.” In The New Palgrave Dictionary of Economics.
Second Edition. Eds. Steven N. Durlauf and Lawrence E.Blume. Palgrave Macmillan.

Hamilton, James (1989). “A new approach to the economic analysis of nonstationary time series and
the business cycle.” Econometrica 57, 357-84.


3. Dynamics of Financial Returns

a. ARCH and GARCH

*CLM, ch 12.2: Models of Changing Volatility

Andersen, Torben, and Tim Bollerslev (1998). ”Answering the skeptics: yes, standard volatility
models do provide accurate forecasts.” International Economic Review 39, 885-905.

Bollerslev, Tim (1986). “Generalized Autoregressive conditional heteroskedasticity.” Journal of
Econometrics 31, 307-327.

Bollerslev, Tim, Robert F. Engle, and Daniel Nelson (1994). “ARCH Models.” In Handbook of
Econometrics vol 4, Robert Engle and Daniel McFadden editors, Elsevier – North Holland.

Engle, Robert F. (1982). “Autoregressive conditional heteroskedasticity with the estimates of the
United Kingdom inflation.” Econometrica 50, 987-1008.

Hansen, Peter, and Asger Lunde (2005). “A forecast comparison of volatility models: Does
anything beat a GARCH(1,1)?” Journal of Applied Econometrics 20, 873-89.

Pagan, Adrian, and William Schwert (1990). “Alternative models for conditional stock volatility.”
Journal of Econometrics 45, 267-90.

West, Kenneth, and Dongchul Cho (1995). “The predictive ability of several models of exchange
rate volatility.” Journal of Econometrics 69, 367-91.


b. Stochastic Volatility

Andersen, Torben, and Luca Benzoni (2008). “Stochastic volatility.” In Encyclopedia of Complexity
and System Science, ed. B. Mizrach. Springer.

Andersen, Torben, and Bent Sorensen (1996). ”GMM estimation of a stochastic volatility model: a
Monte Carlo study.” Journal of Business and Economic Statistics 14, 328-52.
Barndorff-Nielsen, Ole, and Neil Shephard (2001). “Non-Gaussian Ornstein-Uhlenbeck-based models
and some of their uses in financial economics.” Journal of the Royal Statistical Society B 63: 167-241.

Comte, Fabienne, and Eric Renault (1998). Long memory in continuous time stochastic volatility
models. Mathematical Finance 8, 291-323.

Hull, John, and Alan White (1987). The pricing of options on assets with stochastic volatility. Journal
of Finance 42, 281-300.

Taylor, Stephen (1986). Modeling Financial Time Series. John Wiley and Sons.

Wiggins, J. B. (1987), Option values under stochastic volatility: theory and empirical estimates,
Journal of Financial Economics 19, 351-372.

c. Multifrequency Modeling

*CF, ch. 1-4.

*Calvet, Laurent E., and Adlai J. Fisher (2004). “How to forecast long-run volatility: regime-switching
and the estimation of multifractal processes.” Journal of Financial Econometrics 2, 49-83.

Bacry, Emmanuel, Alexey Khozhemyak, and Jean-François Muzy (2008).
“Continuous cascade models for asset returns.” Journal of Economic Dynamics and Control 32(1),
156-99.

Calvet, Laurent E. (2008). “Fractals.” In The New Palgrave Dictionary of Economics. Second Edition.
Eds. Steven N. Durlauf and Lawrence E. Blume. Palgrave Macmillan.

Calvet, Laurent E., and Adlai J. Fisher (2001). “Forecasting multifractal volatility.” Journal of
Econometrics 105, 27-58.

Calvet, Laurent E., Adlai J. Fisher, and Samuel B. Thompson (2006). “Volatility comovement: a
multifrequency approach.” Journal of Econometrics 131, 179-215.

Lux, Thomas (2008). “The Markov-switching multifractal model of asset returns: GMM estimation and
linear forecasting of volatility.” Journal of Business and Economic Statistics 26, 194-210.


d. Pricing Multifrequency Risk

*CF, ch. 9-10.

Calvet, Laurent E., and Adlai J. Fisher (2007). “Multifrequency news and stock returns.” Journal of
Financial Economics 86, 178-212.

4. Simulation-based Econometric Method

a. Simulated Method of Moments

*CLM, ch 2

Duffie, Darrell, and Kenneth J. Singleton (1993). "Simulated moments estimation of Markov models
of asset prices". Econometrica 61 (4), 929-52.

Lee, Bong-Soo, and Ingram, Beth (1991). "Simulation estimation of time series models". Journal
of Econometrics 47, 197-205.

b. Indirect Inference and Efficient Method of Moments

*GM, ch 4.

Andersen, Torben G., Hyung-Jin Chung, and Bent E. Sorensen (1999). "Efficient method of moments
estimation of a stochastic volatility model: a Monte Carlo study." Journal of Econometrics 91 (1),
61-87.

Gallant, A. Ronald, and George Tauchen (1996). "Which moments to match?". Econometric Theory
12, 657-681.

Gouriéroux, Christian, Alain Monfort, and Eric Renault (1993). "Indirect inference. "Journal of
Applied Econometrics 8, S85-S118.

Heggland, K. and Frigessi, A. (2004). "Estimating functions in indirect inference." Journal of the
Royal Statistical Society, Series B66, 447-62.

Sentana, Enrique, Giorgio Calzolari, and Grabriele Fiorentini (2008). "Indirect estimation of large
conditionally heteroskedastic factor models, with an application to the Dow 30 stocks." Journal
of Econometrics 146 (1), 10-25.

Smith, Anthony A. (1993). "Estimating nonlinear time series models using simulated vector
autoregressions." Journal of Applied Econometrics 8, S63-S84.


5. Filtering

a. The Kalman Filter

Hamilton, James (1994). Time Series Analysis. Princeton University Press, ch. 13.

b. Particle Filters

Arulampalam, Sanjeev, Simon Maskell, Neil Gorgon, and Tim Clapp (2002). "A tutorial on particle
filters for online nonlinear/non-Gaussian Bayesian tracking.'' IEEE Transactions on Signal
Processign 50-2) 174-188.

Calvet, Laurent E., and Veronika Czellar (2011). "Efficient estimation of learning models." Working
Paper, HEC Paris.

Chopin, Nicolas (2004). "Central limit theorem for sequential Monte Carlo methods and its
applications to Bayesian inference." Annals of Statistics 32(6), 2385-2411.

Crisan, Dan, and Arnaud Doucet (2002). "A survey of convergence results on particle filtering
methods for practitioners." IEEE Transactions on Signal Processing 50(3) 736-746.


6. Robust Statistics

*MMY, ch. 4 and 5

Czellar, Veronika, G. Andrew Karolyi, and Elvezio Ronchetti (2007). "Indirect robust estimation of
the short-term interest rate process." Journal of Empirical Finance 14,564-63.

Czellar, Veronika, and Elvezio Ronchetti (2010). "Accurate and robust tests for indirect inference"
Biometricka 97(3), 621-630.
Dell'Aquila, Rosario, Elvezio Ronchetti, and Fabio Trojani (2003). "Robus GMM analysis of models
for the short rate process", Journal of Empirical Finance 10, 373-397.

Hampel, Frank R., Elvezio M. Ronchetti, Peter J. Rousseeuw, and Werner A. Stahel (1986), Robust
Statistics: The Approach Based on Influence Functions, Wiley-Interscience, New York.

Ortelli, Claudio, and Fabio Trojani (2005). "Robust efficient method of moments." Journal of
Econometrics 128, 69-97.

Zaman, Asad, Peter J. Rousseeuw, and Mehmed Orhan (2001). "Econometric applications of
high breakdown robust regression techniques." Economics Letters 71, 1-8.


1. Lectures 1 and 2: Equilibrium in Security Markets
-Arrow Debreu Securities
-Competitive equilibrium
-Complete/Incomplete market
-Pareto optimality and risk sharing
-Stockastic discount factor risk neutral probabilities pricing kernel
-Fundamental pricing equation (Consumption based CAPM; one period)

Reading: Pennachi, Chapter 4

2. Lectures 3 and 4: Mean Variance Analysis, CAPM
-Efficient Frontier
-Sharpe ratio
-CAPM
-Factor pricing (APT)
-Beta pricing
-Factor pricing and CAPM
-Test of CAPM and zero-beta CAPM

Reading: Pennachi, Chapters 2 and 3; Cochrane, Chapter 9, Fama and French (1992), (1993).

3. Lecture 4 and 5 : Multi-period extensions
-Consumption-based CAPM: Multi-period extension
-Risk-free rate and Equity Premium puzzle
-Hansen-Jagannathan Bounds
-Bellman dynamic programming principle
-Lucas'model

Reading: Pennachi, Chapters 5 and 6.

4. Lecture 5 and 6: Toward a resolution of the risk free rate and equity premium puzzles
-Epstein and Zin GEU
-Habit formations
-Keeping up with the Joneses
-Prospect theory
-Frictions and liquidity adjusted CAPMI


5. Lecture 6 and 7: Asset Pricing with asymmetric information
-Competitive equilibrium with private information: Grossman's model
-Rational expectations and revealing equilibrium
-Kyle's model of insider trading
-Adverse selection and liquidity

Reading: Pennachi, Chapter 16

6. Lecture 7 and 8: Introduction to no-arbitrage pricing of derivated
-No-arbitrage in liquid/complete markets and option pricing
-The impact of transaction costs

Course taught in English at HEC

References for reading

-Cochrane J. (2001), "Asset Pricing", Princeton University Press.
-Fama, E. and French, K. (1992), "The cross-section of expected stock returns", Journal of Finance,
47, 427-465.
-Fama, E., and French, K. (1993), "Common risk factors in the returns on stocks and bonds", Journal
of Financial Economics, 33(1), 3-56.

Course taught in English at HEC

Dernière mise à jour : jeudi 2 août 2012