The simplest formula for VaR
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When the time period is very short such as one day
   VaR  =  p * z * std 

   VaR  : is our value at risk
    P   : is our position, such as value of our portfolio 
   z    : depend on confidence level
  std   : is the period standard deviation 

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Financial statement analysis
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Objective: 
   1) Understand the importance of financial statement analysis 
   2) understand the definitions of various ratios, such as
       Debt/equity ratio, ROE, ROA, DuPont Identity
   3) Compare the performance of the firm with itself and with peers
   4) Given your recommendations 

   Note: If you could "automate" your process, it will be more 
         meaningful. For example, you spend one day to finaish one company. 
         How long you would finish the next one or 10th one?

  Here are potential helps. 
        1) get financial statement easily, see type
           c28

        2) You can use some simple macro, such as record your operation
           c26

Tool: Excel 

Procedure: 
   1) Download a company's several years' financial statements 
   2) Conduct analysis such as ratio analysis
   3) Compare its performance with itself and with peers
   4) Write your comments and recommendation 

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Black and Litterman model (1992)
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Objective: 
----------
   1) Understand the shortcomings of our optimization model 
   2) understand the contributions of Black and Litterman (1992)
   3) using Excel to illustrate a few examples 
   4) Extension? 

Sources
-------
     blacklitterman.org   
         http://blacklitterman.org

     Black and Little example
         http://canisius.edu/~yany/excel/blacklitterman.xlsx

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Brandt, Santa-Clara and Valkanov model (2009)
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Objectives: 
----------
  1) Understand the traditional Markowitz mean-variance optimization

     http://www.effisols.com/basics/MVO.htm 

     https://en.wikipedia.org/wiki/Modern_portfolio_theory

  2) shortcomings and limitations of the current optimization model 

  3) understand the contributions of Brandt et al. (2009)
       Brandt, Santa-Clara, Valkanov approach (2009) 
       http://www.nber.org/papers/w10996   

  4) using R to implement their approach 

  5) Extension 

Data sources
-------
  1) CRSP
  2) Compustat
  3) Prof. French's Data Library 

  Parametric Portfolio Policies: Exploiting Characteristics in the 
     Cross Section of Equity Returns
       Abstract

  We propose a novel approach to optimizing portfolios with large numbers of assets. 
  We model directly the portfolio weight in each asset as a function of the asset's 
  characteristics. The coefficients of this function are found by optimizing the 
  investor's average utility of the portfolio's return over the sample period. 
  Our approach is computationally simple, easily modified and extended, produces 
  sensible portfolio weights, and offers robust performance in and out of sample.

  In contrast, the traditional approach of first modeling the joint distribution 
  of returns and then solving for the corresponding optimal portfolio weights is 
  not only difficult to implement for a large number of assets but also yields 
  notoriously noisy and unstable results. Our approach also provides a new test 
  of the portfolio choice implications of equilibrium asset pricing models. 
  We present an empirical implementation for the universe of all stocks in the 
  CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies.
    
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