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  • 1. School of Banking and Finance www.banking.unsw.edu.au
  • 2. FINS3640 - Investment Management Modeling
    Week 4 - 11 Aug 2010
    Introduction to using Stata
    for Financial Modeling
  • 3. Revision
    Stata commands
    Regression and t-test interpretation
    R2
    P-value
    Hypothesis testing
    Null hypothesis H0
    Conditional testing
    Binary
    Visual plot analysis
    Price observation, holding period return, dividend and stock split adjustments
    WRDS
  • 4. Multivariate Models
  • 5.
  • 6. Capital Asset Pricing Model
    Market Premium
  • 7.
  • 8. Fama-French Three-Factor Model
    Size Premium
    Value Premium
  • 9.
  • 10. Four-Factor Model
    Momentum
    Momentum-Driven
    Portfolio Rebalancing
  • 11.
  • 12. Five-Factor Model
    Asset Growth
  • 13.
  • 14.
  • 15. Generic Multivariate Model
    This is what you need to build
  • 16. How? Some hints:
    Read contemporary research (see suggested reading list)
    Retrieve & process data (in-class demonstration)
    Establish hypotheses (should be from a quantitative course)
    Test the hypotheses
    Correlation
    R2 & adjusted R2
    P-value
    t-value
    Other econometrics indicators (chi2, autocorrelation…)
    Build and optimise the model(s)
  • 17.
  • 18. Modeling
  • 19. Data Management
    Wharton WRDS
    French Data
    Stock selection
    Monthly
    5-30 years
  • 20. Weighting
  • 21. Risk-free Rate
    CAPM assumption: single risk-free rate
    Is this practically true?
  • 22.
  • 23. Statistical Testing
    Multivariate regression
    t-test
    Visual analysis
  • 24. Multicollinearity
    Variables are almost linearly dependent
    Large standard errors lead to insignificant t-values
    Little explanatory power
    Test Collinearity
    Correlation matrix
    Rotation of variables: R2 does not change much when one variable is dropped
    Remedy
    Drop collinear variable(s)
  • 25. Outliers & Influential Points
    Extreme values
    Market crashes e.g. October 1987, PG 2010
    Market capitalisation of top firms from highly concentrated indices e.g. BHP from ASX
    Skews the model
    'Black swans'
    Identify: unusual observations on visual display
    Remedies
    Time series method: log normal
    Exclusion of influential points
  • 26.
  • 27. Andersen T G, Bollerslev T, Diebold F X, Wu G, 2006, 'Realized Beta: Persistence and Predictability', Econometric Analysis of Financial and Economic Time Series, Advances in Econometrics, Volume 20, 1-39, Elsevier, 2006
  • 28. Binary Variables
    Grouping
    by
  • 29. Heteroskedasticity
    White 1980
    Run regression
    reg y x
    The Het test right after running regression
    hettest
    Save the residual
    predict res, r
    Plot the residuals
    plot res x
    Bibliograph
    http://www.polsci.wvu.edu/duval/ps602/Notes/STATA/heteroskedasticity.htm
    http://web.missouri.edu/~kolenikovs/stata/Duke/class3.html
    http://www.stata.com/support/faqs/stat/panel.html
  • 30. Autocorrelation
    Autocorrelation
    ac
    Partial autocorrelation
    pac
    Q-statistics
    Correlogram
    corrgram
  • 31.
  • 32.
  • 33. ARIMA
    Autoregressive integrated moving average
    arima
    predict
  • 34. Reading
  • 35. Reading (1)
    Required Reading
    Reeves J. J. 2008
    Recommended Reading
    Multivariate Models
    Louise Swift, Sally Piff, Quantitative Methods for Business, Management and Finance, 2nd edition
    John Y. Campbell, Yeung Lewis Chan, Luis M. Viceira, 2001, 'A multivariate model of strategic asset allocation'
    Alvin C. Rencher, 2002, Methods of multivariate analysis
  • 36. Reading (2)
    Fama French
    Fama, Eugene F.; French, Kenneth R. (1993). "Common Risk Factors in the Returns on Stocks and Bonds". Journal of Financial Economics 33 (1): 3–56
    Fama, Eugene F.; French, Kenneth R. (1992). "The Cross-Section of Expected Stock Returns". Journal of Finance 47 (2): 427–465
  • 37. Reading (3)
    Momentum
    Barberis, N., A. Shleifer, and R. Vishny. “A Model of Investor Sentiment.” Journal of Financial Economics, 49, 1998.
    Crombez, J. "Momentum, Rational Agents and Efficient Markets." The Journal of Psychology and Financial Markets, 2, 2001.
    Daniel, K., D. Hirschleifer, and A. Subrahmanyam. “A Theory of Overconfidence, Self-Attribution, and Security Market Under and Over-reactions.” Journal of Finance, 53, 1998.
    Jegadeesh, N., and S. Titman. “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency.” Journal of Finance, 48, 1993.
    Jegadeesh, N., and S. Titman. “Profitability of Momentum Strategies: An Evaluation of Alternative Explanations.” NBER Working paper #7159, 1999.
  • 38. Reading (4)
    Asset Growth
    Cooper, Gulen & Schill, 2009, 'The asset growth effect in stock returns'
    Business Cycle
    DeStefano, Michael, 'Stock Returns and the Business Cycle'. Financial Review, Vol. 39, No. 4, November 2004
    Corporate Governance
    Shane A. Johnson, Ted Moorman, and Sorin Sorescu, 2005, 'Governance, Stock Returns, and Market Efficiency'
  • 39. Reference
    Reeves J. J. 2008
    Andersen et al 2006
    Heng et al 2010
    http://www.polsci.wvu.edu/duval/ps791c/Notes/Stata/arimaident.html