R. A. Ferri - All About Asset Allocation (II)
June 1, 2007Thanks for visiting! If you like what you're reading, you may want to subscribe to my RSS feed.
This is the second part of my book review for Richard Ferri’s “All About Asset Allocation”. If you haven’t read the first part, I strongly suggest you do here.
Chapter 3 - Asset Allocation Explained
Ferri gives the most concise definition of the term that I have come across so far when he says: “Asset allocation is a mathematical approach to diversification. It involves estimating the expected risk and return on various investments, observing how those investments interrelate to one another under different market conditions, and then methodically constructing a portfolio that has a high probability of achieving your goals with the lowest level of expected portfolio risk.”
The main points made in this chapter involve the importance of rebalancing and the theory behind correlation and how it affects a portfolio’s return. I shall try to capture Ferri’s main ideas.
Your asset allocation strategy will be based on long-term expected returns and the associated risks of different asset classes. Regardless of how well these values model the long-term performance of your portfolio, it is bound to behave differently in the short run. In order to bring it back on target a portfolio thus needs to be rebalanced by selling the positions that performed well and now dominate the allocation and buying more of the positions that underperformed. While at first it seems counterintuitive to do this, it ties in with a strategy of buying low and selling high.
There are two main strategies for rebalancing: by percentage or by time. If you have a portfolio that is, for example, evenly divided between stocks and bonds (i.e. 50% stocks, 50% bonds) and you decide to re-balance as soon as any of the positions stand at 10% more (or less) than their target (e.g. stocks have performed well and now constitute 60% of the portfolio’s assets), you are rebalancing by percentage. While this yields slightly higher returns and lower risks than just rebalancing once a year (i.e. by time), it also involves more monitoring and higher trading costs which could potentially erode the additional return. In general, the author holds the opinion that rebalancing annually is sufficient for any individual investor.
The author then introduces the concept of correlation and how it affects asset allocation and portfolio returns. In short, to maximise stability and guarantee steady returns, investors should be looking to include asset classes that are in negative correlation with each other. Negative correlation describes a concept where the returns of two (or more) asset classes will always move in the exact opposite direction. For example, assuming asset class A is negatively correlated with asset class B, then B will go down in value whenever A increases and vice versa. In reality, it is very hard to find assets that are negatively correlated with each other, and investors can be lucky to include categories that either have no correlation with each other or which are only slightly positively correlated.
A further difficulty arises from the unsteadiness of the correlation factor which tends to fluctuate over time. This is illustrated by a chart showing the rolling 36-month correlation between intermediate-term treasury notes (a bond) and the S&P 500 (a major US equities index). Between 1952 and 2004 the correlation factor between these two asset classes has experienced highs of +0.67 (where +1 represents perfect positive correlation) and lows of -0.62 (where -1 represents perfect negative correlation). Despite these two extremes, however, the average correlation for the given period was +0.12, which suggests that bonds and equities are not correlated (it is commonly assumed that where a correlation factor lies between -0.30 and +0.30 no definite correlation can be proven).
To conclude this chapter, Ferri introduces the classic risk-and-return frontier. Starting off with two asset classes, this frontier depicts the annualised return and standard deviation which can be achieved by combining the two asset classes in a portfolio.
(Apologies for the bad image quality, but Excel wasn’t very co-operative this morning so I decided to scan the illustration from the book.)
The graph shows that a portfolio would have an expected return of ~6% (with a standard deviation of ~5.8) if it was fully dedicated to Investment #1 while at the same time a 12% return could be achieved by only buying into Investment #2. The problem with the latter is the high standard deviation of ~17.5 since we learned in Chapter 2 that (in the long run) a consistent return is preferable to a volatile return in terms of overall portfolio gains.
The dots on the graph represent a varying mixture of the two asset classes, where each “dot” represents a 10% change. Therefore it becomes clear that by buying 20% of Investment #2 and 80% of Investment #1 we achieve a higher overall return while maintaining a relatively low-risk portfolio. By introducing more asset classes, we aim to move as high up into the left corner as possible (also called “Northwest Quadrant“), which represents an allocation of high returns and low risk (i.e. low volatility).
More about multi-asset class allocation in Chapter 4.
