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Malmendier & Tate CEO Overconfidence (view source)
Revision as of 18:20, 7 October 2016
, 18:20, 7 October 2016no edit summary
Variables necessary to replicate Malmendier & Tate Over confidence measures:
Ideal Variables:* Value of Options, option grantdate year * Option grant date* Year in which option was exercised, mean * Mean stock price in year of exercise, median * Median stock price in year of exercise, high * High stock price in year of exercise,
*Malmendier & Tate use the 5th year after the option grant date (maybe we use 5th year after person becomes CEO because we haven't found the grant date variable) because across various packages it is the first year in which at least part of the option packages in the sample are exercisable.
*67% In the money appears to mean that the market price has appreciated 67% from the five years sincestrike price as opposed to 67% of a CEO's options being in the money at a given time.
We construct Measure 1 (for both 67% and 100% in the money during the fifth year) as
CEOs who “habitually” exercise options late.
== Our Malmendier type measure ==
We will come up with a measure to rank all the CEOs based on their option exercise behavior. This measure should first replicate some of the features of the overconfidence measure suggested by Malmendier and Tate. It should also exhibit sufficient variation in our sample of CEOs. After we have successfully ranked CEOs, we simply identify the top x percentile as overconfident.
The following annually recorded variable will be part of our measure:
Estimated value of in-the-money unexercised exercisable options($) VUE
Estimated value of in-the-money unexercised unexercisable options($) VUU
Value realized on option exercise($) VE
For each period <math> t </math>, let <math> OC_t^i = \frac{VE}{VE + VUE}</math> to be the preliminary measure of overconfidence of CEO <math> i </math> in period <math>t </math>. I was also wondering if there would be any justification for including the variable VUU in the denominator.
Note that for each CEO we'd have multiple observations for different time periods. Thus, let the <math>OC^i </math> to be the mean of all the observations for CEO <math> i </math>
[[Category:Internal]]
