Is there an “optimal” portfolio?
As the investment theories developed to this point, there are quite a lot successful stories such as the Modern portfolio theory, capital asset pricing model (CAPM), diversification, Sharpe simplification etc. Investment institutions are even implementing them through various quantifications. There are certainly flip-flops, for example, LTCM in 1998.
This theory and its variance are very computation intensive. Even with Sharpe’s simplification that has improved run time compared to Markowitz’s original scheme, it still not a light set for most investors. That might be one of the reason the method is successful because less practioners. Also, dynamic nature of this method also increases computation load.
Consider there are only 50 stocks here for casual reading (the theory can handle real market), the question is to find an “optimal” portfolio through diversification? The optimality is based on maximum return and minimum variance. The later is also interpreted as risk. So given an expected return and individual stock performance, the theory can find out the covariance among them and use linear programming method to find a basket of portfolio. That is a lot of work before getting this basket. But once it is obtained, it is optimal because it finds a balance point between return, the expected one, and risk, the variance of return.
Assuming everyone investor uses this method, it is not surprised to see many of them would punch in similar expected return. Thus, these people would get the same basket of stocks (individual stock performance should be the same at the same time). So it is interesting to see this “optimal”, in a sense of math model, is actually not optimal in real life if everyone is using it.
It is not always desirable to have optimal portfolio, even it is controversial. Keynes preferred less diversification to more. Loeb once said, “Once confidence is obtained, diversification is not desirable”. “Diversification is an indication of don’t know what to do”. Obviously, this is sub-optimal portfolio management, but it is still typical. The biggest edge is that no one knows these sub-optimal ways.
This is an example that high intelligent and street smart are both important.
This theory and its variance are very computation intensive. Even with Sharpe’s simplification that has improved run time compared to Markowitz’s original scheme, it still not a light set for most investors. That might be one of the reason the method is successful because less practioners. Also, dynamic nature of this method also increases computation load.
Consider there are only 50 stocks here for casual reading (the theory can handle real market), the question is to find an “optimal” portfolio through diversification? The optimality is based on maximum return and minimum variance. The later is also interpreted as risk. So given an expected return and individual stock performance, the theory can find out the covariance among them and use linear programming method to find a basket of portfolio. That is a lot of work before getting this basket. But once it is obtained, it is optimal because it finds a balance point between return, the expected one, and risk, the variance of return.
Assuming everyone investor uses this method, it is not surprised to see many of them would punch in similar expected return. Thus, these people would get the same basket of stocks (individual stock performance should be the same at the same time). So it is interesting to see this “optimal”, in a sense of math model, is actually not optimal in real life if everyone is using it.
It is not always desirable to have optimal portfolio, even it is controversial. Keynes preferred less diversification to more. Loeb once said, “Once confidence is obtained, diversification is not desirable”. “Diversification is an indication of don’t know what to do”. Obviously, this is sub-optimal portfolio management, but it is still typical. The biggest edge is that no one knows these sub-optimal ways.
This is an example that high intelligent and street smart are both important.
posted by Intl.investment.services at
4:08 PM
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