But Professor Markowitz doesn't think so. According to his theory, it may be possible to achieve the effect of 1 + 1 > 2 by combining some seemingly bad ones. What's the secret?
In asset allocation, the correlation between investment targets is a critical factor and the most fundamental reason why asset allocation works. We must all have heard of something called the Merrill Lynch Investment clock. Although this framework appears in almost every asset allocation book, and many people vomit when they hear the name, it can really summarize the essence of the selection of investment targets in asset allocation.
According to Merrill Lynch's investment clock, the economy is divided into four primary cycles, the "overheating period," "stagnation period," "recession period," and "recovery period," and investors have two ways to avoid the impact of the economic cycle to the greatest extent.
Merrill Lynch Investment clock
The first is that investors predict the economic cycle and then select the investment targets that perform better in the corresponding process according to different bikes, that is, strategic asset allocation.
Second, most investors are difficult to predict the economic cycle, so simply choose one or two investment targets from each cycle when investing so as to cover all processes.
Of course, we can not wholly apply the Merrill Lynch Investment clock directly because the market is constantly changing. Merrill Lynch Investment clock is a static performance. In fact, if we can dynamically look at the correlation between these investment targets, we will have a more direct understanding. Then I use the S & P 500 as the underlying asset to calculate the 10-year correlation between each other investment and the S & P 500.
10-year correlation between investment targets and S & P 500
Different asset targets have other correlations with the S & P 500, and the correlation of all asset targets shows a certain periodicity, while according to different categories of assets, the marks in the same variety show a form of convergence.
In the stock category, the correlation between small-cap stocks in the United States and S & P has been high, with an average of 83%. Developed country stocks and emerging market stocks, while both stores show the potential benefits of risk diversification between local and non-local markets, with an average correlation of only 50% with S & P before 2000.
Bonds obviously show their inverse correlation with stocks or the attributes of risk-free assets. Short-term monetary and inflation protection is basically around minus 5%. The remaining 10-and 30-year treasury bonds average about 5%. It should be pointed out that the bonds here are all government-endorsed, so they are called relatively risk-free assets, which is another matter if you invest in high-yield corporate bonds.
Due to the significant differences in their attributes, the correlation with S & P is also very different. As a precious metal, gold has counter-cyclical attributes relative to stocks.The remaining commodities are also counter-cyclical, but they fluctuate considerably.
We often use the analogy that eggs can't be put in the same basket. So what the masters do is find these different baskets. Through the above data and charts, we can basically draw a conclusion: the asset allocation portfolio recommended by the masters is dispersed in other asset targets and has a specific negative correlation and counter-cyclical. Allocation is meaningful only when it is allocated in different baskets.
