Don’t say the R(isk) word!

Diversification: Trying to reduce risk in a portfolio by investing in a variety of investments with different performance patterns.

The great insight behind the diversification theory is that an investment portfolio’s return is the weighted average of all of its underlying securities. At the same time, the overall portfolio’s risk is typically lower than the weighted average risk of each of the portfolio’s underlying securities. This would suggest that an investor can manage risk without sacrificing return potential.

I wanted to test this concept with an experiment in numbers. My question: “What is the actual performance benefit, in terms of cumulative return experience, that an investor might achieve if you were able to reduce risk without sacrificing return?” In other words, “What is the performance benefit of diversification?” (Bearing in mind that diversification and strategic asset allocation do not assure against profit or protect against loss in declining markets).

Digging into risk

To find out, I ran an experiment – a sort of horse race between hypothetical return streams. First, I used the random number generator tool (think of it as a sophisticated coin toss) in Excel to create two hypothetical return streams that would both have an expected annual return of 10% (I picked 10% because it’s a nice round number, but you could do the same with a different hypothetical return target).

Second, to really be able to test the benefit of diversification, I set the two streams to have different risk levels. One of the hypothetical return streams has a 10% standard deviation – let’s call that one the “Low Risk Stream,” and the other hypothetical return stream has a 20% standard deviation – let’s call that one the “High Risk Stream.” I compared the 50-year return streams 10,000 times to make the outcomes statistically significant.1

(Standard deviation is a statistical measure of the degree to which an individual value in a probability distribution tends to vary from the mean of the distribution. The greater that degree of dispersion, the greater the risk.)

In picture form, the two return streams look like the graph below. The distribution of returns in the High Risk Stream is wider, and more volatile, than that of the Low Risk Stream:

Low Risk vs High Risk Hypothetical Return Streams

This hypothetical example is for illustration only and is not intended to reflect the return of any actual investment.

With the Low Risk Stream, the probability of outcomes higher or lower than 10% is reduced. But, what does this mean in terms of performance over time?

Take it up a notch

Upon analyzing the data, it becomes clear that there is a positive relationship between a lower dispersion of returns and higher performance: the Low Risk Stream usually outperforms the High Risk Stream over time. In fact, after just 5 years, the Low Risk Stream outperforms the High Risk Stream 56% of the time; after 20 years, the Low Risk Stream outperforms 61% of the time:

Low risk outperforms high risk over time

IMPORTANT: The projections or other information generated by this analysis shown on this and subsequent charts regarding the likelihood of various investment outcomes are hypothetical in nature, do not reflect actual investment results and are not guarantees of future results. Results may vary with each use and over time.

Talk to your clients

As you may have experienced in talking with your clients, the word “risk” triggers all sorts of emotions among investors. The risk of losing money. The risk of not meeting their long-term financial goals. And it’s true, nearly everyone agrees that risk should be managed in investment portfolios. Hopefully this analysis and some of our other posts about the benefits of diversification can be useful in your conversations with clients as you encourage them to stick to a long-term plan.

Johann Schneider is program director of capital market insights for Russell Investments. View Johann’s bio »

1A Monte Carlo simulation is a sophisticated mathematical approach used within the financial industry to model possible outcomes of investment scenarios by substituting a range of values – a probability distribution – for any factor that has inherent uncertainty. It then calculates results over and over, each time using a different set of random values from the probability functions. The projections or other information generated by the Monte Carlo simulation regarding are hypothetical in nature, do not reflect actual investment results, and are not guarantees of future results.

Strategic asset allocation and diversification do not assure profit or protect against loss in declining markets.

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