You see how risk has become this objet de l'attention for me. It has been permeating all my discussions of investing, whether in capital markets or real estate. What are the risks? How do you model them? How do you price them? What potential blind spots are there?
For a while I've had an idea to model real estate risk, from an investor's perspective. I started working on the model - identifying factors, working to create initial values for them based on the limited data available from the few deals my partners and I had done, etc. It is still far from being complete, but it is coming along.
While thinking about this problem - modeling real estate investment risks - I started thinking about information markets and basic value investing. Essentially, you have to discount your price or present value (PV, for all the DCF wonks) by some (hopefully) standard amount for each factor where you have incomplete information. The amount of the discount should be roughly proportional to the completeness of the information you have about that factor.
In an information market, prices should (will?) be discounted by some amount based on the completeness of the information about the product. Real estate is no different from the stock market in this regard. We see this in the pricing of financial stocks, especially the bulge bracket IBs (Goldman, Morgan Stanley, etc.). The argument goes that since their operations and holdings are so opaque, the market applies a discount to their share prices for the uncertainty about how they make money, assets they carry on (and off) their books, etc. It makes total sense. If I can't tell what's going on with a house structurally (say, I purchased at an auction of some sort and was not allowed to have an inspection done, or there was no time for the inspection), then there should be some discount applied to the price due to that information shortfall.
Anyway, that's just a taste of an ongoing project of mine. I am working on learning how to model risk in various markets. If anyone has any suggestions, whether they are articles, books, or authors to read, classes to take, or any other ways to learn how to model, please let me know. I know that over time, my modeling will improve, but I am not above accelerating the process.
Until next time, because I think I have more to say on this and I just needed to get this one out the door...
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