**Definition of Asset Correlation**

Asset correlation is a measurement of the relationship between two or more assets and their dependency. This makes it an important part of asset allocation because the goal is to combine assets with a low correlation.

The correlation measurement is expressed as a number between +1 and -1. A zero correlation indicates there is no relationship between the assets. A +1 indicates an absolute positive correlation (they always move together in the same direction). A -1 indicates an absolute negative correlation (they always move together in opposite directions of each other).

**Examples of Asset Correlation**

### Positive Correlation

When two or more assets move up and down together. Stocks in the same industry would have a high positive correlation. They would probably be affected similarly by events.

### Zero Correlation

When two or more assets show no relationship to each other. Combining multiple assets with no correlation would be an ideal diversified portfolio because volatility (risk) of the whole portfolio would theoretically be minimized. In the real world most assets have some correlation; so a low asset correlation such as between gold and S&P stocks, would be a good example of near non-correlated assets.

### Negative Correlation

When two or more investments move inversely to each other they have negative correlation. Two assets that were perfectly negatively correlated would eliminate risk of the combined assets.

Perfect negative correlation is mostly only found in synthetic instruments such as futures contracts or inverse ETFs. These instruments can provide near perfect negative correlation and therefore can be useful tools to reduce portfolio volatility. Of course these instruments, particularly futures contracts, can be very risky if not employed properly.

**Problems with Asset Correlation**

In the real world very few asset classes have a perfect positive correlation (+1), zero correlation (0), or perfect negative correlation (-1). The vast majority of investments will have some correlation (between 0 and +1). The goal is to have low asset correlation. The fact that most investments are positively correlated is a problem and means finding the right mixture of assets more challenging.

Another problem* *is correlations are dynamic. You know the saying “Past performance does not equal future returns”. This is especially true with correlations because they change. The world is becoming increasingly interconnected, so many investments that formerly had low correlations are now more correlated.

In recent years when we experienced turmoil in global markets almost everything suffered. In other words, because of globalization, asset classes are tending to be more correlated than in the past. This problem is making proper asset allocation more difficult.

**Asset Correlation and Cash**

The shrinking number of asset categories with low correlations should give cash and cash equivalents an increased and higher priority to asset allocation models. Cash has a zero correlation with most other investment assets and provides a means to preserve capital in bear markets.

**Why is Asset Correlation Important? **

The financial concept of asset correlation is important because the goal of asset allocation is to combine assets with low correlation. The purpose of asset allocation is to lower portfolio volatility. By putting low correlation and/or negatively correlated investments in a portfolio, the overall volatility of the portfolio is lowered.

Combining asset categories that have a low correlation reduces the volatility of the portfolio as a whole and allows the portfolio manager to invest more aggressively. In other words, a portfolio manager willing to accept a given amount of volatility can invest in higher return/risk investments. This is because the volatility of the overall portfolio is lower due to combining non-correlated assets. This is called portfolio optimization.

Understanding asset correlation can reap huge rewards for your portfolio. Small differences in rate of return can make gigantic differences in portfolio value in the long run. If you can increase your returns by 1% annually a $100,000 portfolio will return you an **extra** $146,000 over a 30 year period.

**AssetCorrelation.com**

AssetCorrelation.com is a website to learn more about asset correlation. In fact you can sign in (free) and set up an investment portfolio. It will produce a matrix where you can see the correlations between each of your assets.

Related Reading: Value Strategies For Asset Allocation

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Excellent post Ken, good explanation of a complex and important investing principle.

Thank you Roger.

It should be noted that correlations (or diversification) alone is not good enough to construct a good portfolio. It has to consist of assets with high expected returns. For example, in the permanent portfolio, U.S. stocks have long-term average annual total returns of 7.8% (nominal returns with 2.8% inflation) while 20-year long-term U.S. Treasuries have about 4.6%. All are based on Rick Ferri. See the Bogleheads’ excellent wiki page on this subject. Historically, gold also exhibits a similar return like stocks. All of these can help one to derive a ball park average expected returns for your portfolio.

Thank you Keith.

It is generally agreed that there is a higher degree of correlation in the markets observed within the past 10 years than has been observed in the past, and the conclusion of many investment professionals is that investors should find obscure and illiquid investments just to get these supposedly uncorrelated assets to diversify your portfolio. Gold and commodities are always being touted as the best portfolio diversifiers. However, the above plots show how different asset classes (commodities, international stocks, domestic government bonds) can all of a sudden move in sync with the S&P500 index (higher correlation). For perfect diversification, we want negative correlation – its great when bonds rise when stocks fall. Zero correlation, in theory, should work too – though not as well as negative correlation. But what we see from the above charts is that this is not to be taken for granted, and there is no rule of thumb that is always true. We can also see that correlation can not be reduced to a single number, even for a single week. Week by week, the numbers can jump erratically, and if a daily chart could be observed, we would see the same type of erratic behavior. Because of the apparently unpredictable nature of the correlation plots, future correlation can not be predicted, as it constantly changes from negative to positive, making it very difficult to make sure that different investments are truly uncorrelated or negatively correlated, because past history does not say very much about how correlation we can expect in the future. Thus, we can not take the magnitude and the sign of correlation for granted. When a crash comes, and we know crashes come quite often nowadays, correlation between different asset classes can spike like it did in 2008, leading to big losses across the board, and this is exactly what happened to many illiquid investments held by a number of institutional investors for the purpose of diversification.

The second key point from looking at the correlation matrices is that an investor ultimately needs to look at correlations to the overall portfolio rather than correlations between individual asset classes. IGE exhibits higher correlation to EFA than to SPY. If you mix SPY and EFA in a portfolio, the incremental value of adding in IGE will be lower than if you have no EFA. We add EFA to SPY in a portfolio to gain the diversification value that adding international stocks provides, but adding EFA diminishes the incremental value of adding natural resources. The same is true of bonds. To determine how to build a strong asset allocation plan, an investor will, ideally, be able to look at the incremental value of adding an asset to a portfolio. Further, because the total portfolio impacts of adding an asset are a combined function of both volatility and correlation, the investor needs to see the portfolio impacts of both. Quantext Portfolio Planner accounts for the range of correlation effects between assets as well as generating realistic projected values for volatility for individual assets, but many common methods do not. Without accounting for these correlations and volatility effects, it is often not possible to properly measure the impact of adding an asset class to a portfolio or to calculate the total portfolio risk with confidence.

Thank you. Most portfolios that use more than a few ETFs are OVER diversified in my opinion.

The matrix is a good way to identify assets that have the potential of working well together in a portfolio. You can see in this matrix that the correlations between the assets range from moderately negatively correlated to moderately positively correlated, thus they should form a fairly good portfolio, but a four asset portfolio would benefit from additional diversification. Also, it would be best to use monthly returns rather than annual returns to construct the matrix. I used annual returns simply because it allowed me to show all of the data in a relatively small table that could be shown in its entirety with the matrix.

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