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I am attempting to determine the hypothetical market value of a stock for a company emerging from bankruptcy as of a date prior to actual the issuance of the stock. For example, let's say the formerly bankruptcy company issues new equity on February 1, 2013. I would like to value that equity as of January 1, 2013.

This article performs a similar study, and valued the equity like this:

We discount the firm's market value of equity to the PV date, using a discount rate based on the capital asset pricing model (CAPM) and levered equity beta . . . . This value is added to the value of the reorganized company's debt to calculate the market value.

Is this the best approach? And if not, what alternative approach would be better?

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The way I would approach it is to get the best theoretical value you can get (what you are trying to do) and then do a nonlinear supervised learning algorithm on historical data to identify what accounting (etc) features (and their nonlinear interactions) cause deviations from this theoretical value ('surprise forecasting'). –  user2763361 Dec 30 '13 at 7:13
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