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Investment: A change of view

As more institutional portfolios are managed with an objective of generating alpha, interest in the concept of asset correlation continues to grow. The concept emerged from an obscure place in Modern Portfolio Theory to provide analytical support for investment allocation decisions. By successfully combining pairs of low-correlating asset classes or investments, portfolio managers could theoretically temper the volatility of returns and enhance risk-adjusted performance.

In dynamic markets, many institutional investors realise that investment correlation analysis can be more complex in practice than in theory. To be useful, correlation relationships should be observable in the present and endure for a meaningful future interval. However, as market dynamics turn faster, some correlation relationships have been changing before they can be captured by conventional methods of analysis.

For example, 10 years ago, the correlation between the S&P 500 Index and the MSCI EAFE Index — an overseas equity index from the perspective of a US investor, which therefore excludes US equities — was 0.31, suggesting an opportunity to gain risk-adjusted return by diversifying among US and foreign equities. The correlation between these benchmarks started to increase steadily, reaching an all-time high of 0.87 in July 2007.

However, this data is based on five-year historic look-back periods of rolling monthly returns. Using the shorter and more time-sensitive, two-year look-back period produces a very different conclusion, in that the correlation between US and foreign stocks peaked at 0.93 in March 2005 and had declined to 0.62 by June 2007. A more dynamic time frame indicates that the diversification benefit of combining US and foreign equities has, in fact, staged a quiet comeback during the past two years.

This illustrates the problem in bridging the gap between correlation analysis theory and effective portfolio strategies. An evaluation of historic investment index correlations may help institutional investors bridge this gap.

Correlations are dynamic and complex
This analysis indicates that correlations have been as dynamic as financial markets, and the fluid nature of the data added to the complexity in identifying low-correlating pairs of assets with the potential to enhance risk-adjusted returns.

The correlation analysis was conducted using available historic monthly performance data of 21 investment indexes over the period January 1979 to June 2007, derived from US dollar returns. Looking at the methodology more closely, the correlation data was evaluated:

>> Over three ‘static’ historical look-back periods — two years, five years and 10 years — all viewed from the perspective of June 2007. For each look-back period, monthly returns were evaluated.
>> On a ‘rolling’ basis since December 1980 for each of the three look-back periods — to the extent historic data was available — which revealed dynamic changes in correlations with US equities over time.

The FactSet analytical engine was used to generate all correlation data interpreted in this analysis.

Correlations are calculated by standing at one point in time and looking back at historical relationships over a defined period. The longer the look-back period, the more the analysis produces long-term averages. Table 1 compares the correlation of the S&P 500 Index with three other indices over all three static look-back periods in this analysis. (In each case, the point of look-back reference is June 2007.) To see recent correlation trends, we use the static two-year look-back data. To evaluate long-term averages, we use the static five-year or 10-year periods.

The value of rolling period analysis
It can also be useful to see how correlations change over rolling periods: Charts 1 and 2 show dynamic rolling-period correlations with the S&P 500 Index for all three indexes included in Table 1, based on look-back periods of two years (Chart 1) and 10 years (Chart 2), respectively.

When the look-back period shifts from two to 10 years, correlations appear dramatically different because the two-year rolling period analysis shows greater sensitivity to recent trends. Correlations are dynamic, not static. Evaluating two-year look-back periods on a rolling basis reveals short-term, cyclical or chaotic shifts in investment relationships.

Dynamics of correlation relationships
As Chart 1 indicates, the correlation between the S&P 500 Index and MSCI EAFE Index (foreign stocks) has been fairly stable over time. A separate review of two-year rolling correlations indicates that several other indices also appear to have relatively stable correlations versus the S&P 500 Index. They include the Russell 1000 Growth, Russell 1000 Value, Russell Midcap, and CS/Tremont Dedicated Short Bias indices.

In addition, Chart 1 indicates that the Lehman US Aggregate’s correlation with US equities has been more cyclical than stable, because total returns on bonds are typically driven by interest rate cycles that do not always correspond to the behaviour of the stock market.

The correlation of the C/S Tremont Hedge Fund Index with US stocks (Chart 1) appears more difficult to evaluate. While the dynamics of bond-index correlations are explainable by cycles, those of this hedge fund index — which includes 10 different hedge fund styles — appear more chaotic. Consequently, when hedge funds are viewed in the aggregate, it is difficult to make reliable assumptions about how they will correlate with stocks in the future.

Table 2 categorises 20 indices based on the perceived stability of their correlations over time and the perceived cyclical or chaotic character of their correlations. In each case, all indices are compared to the S&P 500 Index. These categorisations were made based upon a visual examination of the data and are, therefore, somewhat subjective. Perhaps an in-depth statistical analysis of the data will develop more accurate and useful patterns of historic rolling-period correlations.

The categories found in Table 2 are defined as follows:

>> Stable: only one index — short-bias hedge funds (C/S Tremont Dedicated Short Bias) have consistently produced low correlations with US stocks. This suggests the potential to include short-bias hedge funds as risk-mitigating instruments in buy-and-hold equity-heavy portfolios.
>> Cyclical: the duration and timing of cycles varies greatly among the 10 indices. If the art of using correlation data to develop efficient portfolios may depend, in part, on the ability to identify sustainable future relationships based on analysis of dynamic historic data patterns, an asset class that demonstrates longer cycles (for example, commodities) may be more dependable than one with shorter cycles (for example, US Real Estate Investment Trusts).
>> Chaotic: in a few indices — for example, emerging markets, small-caps and gold — correlations were dynamic in ways that were not attributed primarily to cycles.

Summary
Based on the above information, it is important to consider:

>> Correlation data should not be taken at face value. Evaluation of rolling two-year periods can show trends in correlations that can be cyclical or chaotic. Diversified portfolios that seek to generate alpha by combining low-correlating investments should monitor changing correlations and, ideally, make periodic adjustments.
>> The analysis has identified 10 indices that have demonstrated cyclical patterns of changing correlations with US equities. All except one have had average long-term correlations below 0.60 (see Table 2). While history does not predict the future, it may be prudent to regularly monitor asset class cycles and relationships trending toward lower correlations.
>> Hedge funds may require special care in evaluating correlations, because labels can be misleading. Rolling two-year period analysis shows that equity-long and short hedge funds in particular have experienced rising correlations recently, peaking at 0.85 in April 2005 (two-year look-back as represented by C/S Tremont Long Short Equity Index).

Perhaps institutional investors that acquire these funds for diversification do not desire such high correlation with US stocks and would, therefore, be wise to ‘look under the bonnet’ of hedge funds.


Ric van Weelden is managing director of international consultant relations at Janus Capital International