More Theory on Real Estate Investments

 There have been numerous volumes of work done on commerical real estate investing theory. Here we are going to touch on the basics to illustrate how commerical real estate investing theory can work for us, the small investor. The essence of commerical real estate investing theory is allocating funds to investments that maximize returns while limiting the volatility (risk). It is up to the investor to determine the level of volatility they are willing to take for a given level of return. The higher the return, the higher the volatility (risk).

Volatility in an investment is measured from the standard deviation of historic returns. Technically the standard deviation is the square root of variance - a measure of dispersion of data around the mean (please reference a good statistics book). The higher the standard deviation, the more a value moves above and below the average value - higher risk. For example, Stock "A' with historic share values of $100, $75, $10, and $15 has an average of $50 with a standard deviation of $44.5. Stock "B" with historic share values of $60, $40, $45, and $55 also has an average of $50, however; the standard deviation is only $9.12. Although the average share values average the same, we can see that Stock "A" is over five times as volatile as Stock "B". Stock "A" is more risky. The same measure of volatility can be done for markets. The stock market has a volatility of about 15% with return expectations around 10%. Bonds have a volatility of 8% with a return expectation around 6%. Real estate fits in the middle with a volatility of 10% and an expected return of 9%. All of the market volatilities and returns depend on the period that they are measured. The best bet is to verify the volatilities and returns with major financial websites and see where the consensus is. The expected returns and volatilities can change depending on the period under consideration.

Plotting the risk vs. reward on a chart for the stock, bond, and real estate markets (See Figure 1 below), we can see how each market compares to each other. Risk is plotted on the horizontal axis, while the reward labeled "expected returns" is plotted on the vertical axis. Each market is represented by a point on the graph. Stocks', being the highest risk and reward, is far to the upper right of the chart. Real estate is in the middle, with bonds at the bottom left of the chart. Plotting the potential investments gives us a quick way to select the better performing investments considering risk.

Investment Theories

Unlike their colleagues in the stock and bond markets,
institutional real estate investors have been slow to use Modern Portfolio Theory (MPT)
 in their decisionmaking processes. Surveys by Wiley, (1976), Webb (1984), Louargand (1992),
and Worzala and Bajelsmit (1997) have shown that diversification has slowly entered into the lexicon
and decision-making processes of institutional real estate investors, but those that used the
quantitative methods espoused by MPT were in the minority. See examples of commercial real estate listings. To be sure, not all stock and bond
managers use MPT to construct or analyze their portfolios, but the real estate practitioners’
unwillingness to use these quantitative tools was due to their discomfort with MPTs reliance on
data they saw as unrepresentative and MPTs abstraction from the traditional real estate
decision-making process, which has been concernedwith the details and specifics of “doing the deal.”