It has been drilled in my head for the past year that the finance theories and their underlying premise are wrong. I nevertheless agree with the previous statement given the questionable assumptions with which the theories are based on; but where would we be if Markovitzs and Sharpe were never born or sadly if they majored in arts..?
Modern portfolio theory (MPT) rests on the idea that you can maximize an individuals expected return given a targeted risk profile (standard deviations of return). In constructing an allocation mix, the financial analyst must determine the historic return on each potential asset that may enter into the portfolio. The return of the entire portfolio with only 2 assets will be simply the weighted average of the expected returns of the two asset classes.
The standard deviation of this entire portfolio would be..
If we vary the correlation variable in the equation and plot it on a expected return – standard deviation plane, we will see something like this.
From standard theory, the idea is that if an asset class is negatively correlated to the existing asset in a portfolio, combining them will yield a reduced overall risk preserving the return.
Ok, I have just regurgitated what I’ve learned in my financial theory class for the past three weeks.
The idea of mixing uncorrelated assets together intuitively makes sense. If one asset is going down, then a negatively correlated asset class will up, cancelling out the risk. This view to asset allocation seems alright only when you assume the correlation between the asset class hold in the future. This usually isn’t the case due to globalization of the entire financial markets (ie 2008). Moreover, the expected value of the long run asset return is assumed to converge to a value(historic expected return). The reliance on this is arbitrary; a recent unexpected evidence of this is in a 30 year stretch, bonds have beaten stocks.
Can we adopt any of the ideas from MPT to systems development? One idea that I came across earlier and posted quite a bit on is system diversification. Instead of selecting the optimal assets to combine together, we can instead select combinations of “systems” to form different optimal portfolios. There are a lot of capabilities to this idea as from a systems point of view, we can create strategies for different time frames, anomalies (momentum, trend following, value, or mean reversion), or ideas limited to your imagination only. Given each systems statistics, achieved from robust backtest procedures, we can optimally combine them together to form portfolio of strategies engineered to a set of parameters.
The ideas above are just me day dreaming after class, they are just my by-products of when (if ever : D) my creative juices are at work…
Source: Investments 7th Edition, Bodie