illiquidity measure, Amihud (2002)
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Objective: estimate 12 stocks  illiquidity measures for each month in 2016. 
     Note: you choose the last 6 stock yourself. 
	Comments on your findings


     6 stock symbols are given below. 
        Company name            Ticker	Industry
        ----------------------  ------  ------------------
   1	Microsoft Corporation   MSFT    Application software
   2	Apple Inc.              AAPL    Personal Computer
   3	Citigroup Inc.             C    Money Center Banks
   4	Wal-Mart Stores, Inc.    WMT    Discount, Variety Stores
   5	Home Depot, Inc.          HD    Home improvement services
   ..   .................       ...     ......
  12	General Electric Corp     GE	Technology

 Amihud (2002) illiquidity measure uses the absolute daily return over 
   its corresponding trading dollar volume. A monthly stock illiquidity 
   measure is the mean of daily illiquidity measure.  
                   1                |Ri|
       illiq(t)=  --- * sum (--------------- )      (1)
                   n             pi * Vi

   where illiq(t) is a monthly illiquidity measure, n is the number of 
         trading days within the month, Ri is daily return on day i, 
         Vi is the trading volume on day i and Pi is the closing 
         price of the underlying stock on day i. 

   The Amihud illiquidity measure includes two components: 
        spread and the impact of trading. Illiquidity is the 
        opposite of liquidity, i.e., a higher value indicates a low 
        liquidity and a small value indicates a higher liquidity level. Why?

   Step 1: download daily price data from Yahoo Finance 
   Step 2: estimate daily returns and dollar trading volume
   Step 3: estimate the ratio
   Step 4: estimate monthly illiquidity measures

 References
    Amihud, Yakov, 2002, Illiquidity and Stock returns, Journal of Financial Markets 5, 31-56.

var/std conversion, confidence
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we have the following formulae to convert variances 
      and standard deviations based on daily or monthly returns. 

   var(annual) = 252 * var(daily)

   var(annual) = 12  * var(monthly)

   std(annual) = sqrt(252) * std(daily)

   var(annual) = sqrt(12 ) * std(monthly)

 
    var(10day) = 10 *var(daily)

    std(10day) = sqrt(10) std(daily

Confidence level vs. significant level
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  Confidence level = 1 - significance level
  If significant level =1%
     -> confidence level is 99% 
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