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Getting real about risk

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The investment community spends a lot of time discussing the risk of different investments, but we don’t often spend time discussing how that risk is actually defined. Here, we take a closer look at the most common measure of risk, standard deviation, and discuss how downside tail loss may more accurately represent one of the risks that investors truly care about.

Bell-shaped in a perfect world

When a standard deviation model is used to measure risk, it assumes the returns of an investment or security are normally distributed and plotted symmetrically around a mean value — the familiar symmetric "bell curve" as seen in Figure 1.

Figure 1 shows a normal distribution of returns.

Fat tails in the real world

Real-world investing does not always exhibit this normal bell-curve pattern of returns, which results in an asymmetric curve with a negative skew. Additionally, most investments tend to have "fat tails" in which outlier events occur more frequently than would be expected by the normal distribution, as seen in Figure 2.

Normal distribution in Figure 2

Estimating returns in a sharp market pullback

Expected tail loss (ETL) is an extension of the popular Value at Risk (VaR) metric — a specific projected return value that marks a probability boundary (i.e. VAR at 5% indicates that 5% of the projected returns will exceed that value, as seen in Figure 3). The ETL illustrates how significant a drawdown could be once VaR is breached, essentially providing an estimate of how bad returns may be during a sharp market pullback. This is sometimes also known as tail risk and shows the average return of the worst 5% of outcomes.

As tail risk does not require the assumption of normally distributed returns, it can help mitigate the difficulties that standard deviation has in analyzing non-normal portfolio returns with fat tails or negative skew.

Figure 3 shows VAR at 5% indicates that 5% of the projected returns will exceed that value

Relying on tail risk to evaluate portfolios

Nuveen uses a non-linear, Monte Carlo simulation projecting expected returns across 10,000 portfolio simulations to estimate how a portfolio may perform in various market environments. From this data, we calculate the expected average return along with potential downside risk. This process utilizes Nuveen’s proprietary forward-looking return projections as well as correlations and volatility data history going back prior to the 2008 financial crisis.

Nuveen model portfolios use this risk management approach.  To learn more, visit our tax-exempt income model, or call us at (866) 819-2711.

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Glossary

Bloomberg Barclays Aggregate Bond Index: tracks the performance of U.S. investment grade bonds. It is not possible to invest directly in an index.

Monte Carlo Simulation: a mathematical technique that generates random variables for modelling risk or uncertainty of a certain system.

MSCI ACWI (All Country World Index): a free float-adjusted market capitalization index that is designed to measure equity market performance in the global developed and emerging markets. It is not possible to invest directly in an index.

Negative Skew: (also known as left-skewed) distribution is a type of distribution in which more values are concentrated on the right side (tail) of the distribution graph while the left tail of the distribution graph is longer.

VAR:Value at Risk–a specific projected return value that marks a probability boundary–i.e. VAR at 5% indicates that 5% of the projected returns will exceed that value.

A word on risk

Investing involves risk; principal loss is possible. If evaluating investment companies, please carefully consider a fund’s investment objectives, risks, charges and expenses before investing. For this and other information that should be read carefully, please obtain a fund prospectus or summary prospectus from your your financial professional or Nuveen at 866.802.6398 or visit nuveen.com.

Featuring portfolio management by Nuveen Asset Management, LLC, an affiliate of Nuveen, LLC.

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