Acercher

Plausible Negative Scenarios by Fund Type

Richard, as usual, thanks for some very interesting hard data. (I suppose it might be even more useful if you follow the first commenter's suggestions, but I can't be the only one who didn't understand even a little bit of it).

My issue is more basic, but goes to the issue of conflating fat tails with (highly) unpredictable events. Fat tails are the unpredictable residue left over from statistical analysis of the past. But unpredictable events can have different degrees of probability based just on common sense (i.e., knowledge not derived solely from statistics).

For instance, under the 2 standard deviation worst case column of your country chart, consider the following pairings:

United Kingdom (17)
Malaysia (17)

Switzerland (8)
Israel (10)

Sweden (30)
Russia (21)

I'm reasonably confident that the possibility of a very bad thing happening in Malaysia, Israel, and/or Russia is significantly higher than in the United Kingdom, Switzerland, and/or Sweden. I'm also reasonably confident the very bad thing would have a very bad effect on that country's stock market.

I find it very counter-intuitive (euphemism for unbelievable) that in essentially 96% of future scenarios, each of the two countries paired above has a basically equivalent downside risk. Comments?

Time to Change Country Mix in World Market-Cap

Your articles are consistently among the most interesting on Seeking Alpha. I appreciate the way you marry hard data with a point of view--too many other commentaries have one or the other but not both.

My personal portfolio for equities has been divided about 50/50 for the last couple of years, which I think is nowhere as risky as conventional wisdom would have it, particularly given the secular trend of a declining dollar.

However, I have consistently been troubled by the role of Japan in foreign allocations. Even in your schedule above, Japan has been hovering around 10% for years, yet has truly sucked eggs as an investment. How do you deal with this yourself?

Portfolio Planning and the Lost Decade

Geoff--Another good article. However, I could not find your rationale for no allocation to EEM, either here or in the earlier articles you cite. I can think of a couple of reasons why you may have excluded EEM, but am interested in your thinking. Thanks.

Choosing Your Portfolio Risk Tolerance

Geoff--Excellent article. It stimulated me to read many of your other articles, and I find myself in accord with your investing philosophy.

I was hoping you might find it worthwhile to comment or write about an issue that I see coming up in various investment commentaries by others: they seem to use the concepts of beta (correlation to an index like the S&P 500) and standard deviation (a measure of volatility) almost interchangeably. I think it's because almost everybody equates a low standard deviation with low beta, and ultimately with low risk.

But would you agree that certain asset classes or stocks could exhibit very low beta while at the same time having a very high standard deviation? For example, rare stamps might have almost no correlation with the S&P 500, and thus could have a beta of 0. However, I also assume it's possible that a collection of rare stamps might have a high standard deviation in terms of what it could be sold for in any given year.

If my understanding of these statistical terms is correct (which is by no means a given), wouldn't that have an effect on optimizing a portfolio? Typically, if the standard deviation of a portfolio was too high for comfort, you might choose to add more bonds or utilities which have a low beta and low standard deviation. But could you also reduce the standard deviation of the portfolio by adding one or two new asset classes, eg., commodities and currencies, which themselves have low beta but very high standard deviations, and thereby increase rather than reduce your expected return?

Perhaps I'll have to buy Quantext to find out, but could you give a little commentary on this issue for those people who prefer words to numbers? I promise to buy Quantext either way.