Estimate Merton Distance-to-Default
Merton (1974) Distance to Default (DD) model is useful in forecasting defaults. This post documents a few ways to empirically estimate Merton DD (and default probability) as in Bharath and Shumway (2008 RFS).
Merton (1974) Distance to Default (DD) model is useful in forecasting defaults. This post documents a few ways to empirically estimate Merton DD (and default probability) as in Bharath and Shumway (2008 RFS).
Uninitialized variable in C can be anything (most of the time). I find, in some cases, we can know the value of an uninitialized variable and thus maybe exploit it.
Question
Given a centrifuge with \(n\) holes, can we balance it with \(k\) (\(1\le k \le n\)) identical test tubes?
In a traditional principal-agent model, firm output is a function of the agent's effort and the principal observes only the output not agent's effort. The principal carefully designs the agent's compensation package, especially the sensitivity of the agent's pay to firm output, to maximize the firm value. Now, what if we add another factor to the relationship between firm output and agent's effort? How would the optimal pay sensitivity change?
As in Eisfeldt and Papanikolaou (2013), we obtain firm-year accounting data from the Compustat and compute the stock of organization capital for firms using the perpetual inventory method that recursively calculates the stock of OC by accumulating the deflated value of SG&A expenses.