Equities have historically rewarded long-term investors with high, above-inflation returns, but the ride is rarely predictable. Defined return investments using a portfolio of autocallables¹ aim to deliver more predictable outcomes while targeting long-term returns similar to equities. Read our Portfolio Insight on the Role of Defined Return Autocallables in a Portfolio.

The greater predictability of defined-return autocallable strategies makes them a leading candidate to serve as an equity anchor in a strategic asset allocation. The evidence in this blog supports a meaningful strategic allocation rather than a marginal portfolio position over medium to long-term time horizons. The precise weight depends on the investor’s risk target, assumptions and holding period, but historical portfolio analysis consistently assigns a substantial part of the equity sleeve to these strategies.

Five traits that make Defined Return Autocallables strategies different

By using equity-linked derivatives (in this case, autocallables), defined return strategies can deliver investors with differentiated investment outcomes that are additive to other assets in a multi-asset portfolio. Here are five traits that make Defined Return Autocallables strategies different:

1. Narrower outcomes. A diversified basket concentrates returns around the target, making it more likely to reach.
2. High yield. Coupons are paid in many scenarios, so potential yields compare well with traditional fixed income.
3. Positive returns more often than classic pricing models would suggest. Autocallable coupons are partly funded by exposure to downside put optionality. However, capital losses have historically occurred less frequently than implied by derivative models.
4. Harnessing the equity risk premium. Autocallables gain exposure to the equity risk premium through their equity-linked payoff structure.
5. Harnessing the volatility risk premium. Implied volatility has generally exceeded realised volatility, so investors have often paid for protection.

Looking for an ‘optimal’ weight

Given those traits, we next examine how much an investor might allocate to a defined return strategy. To do that, we construct a Markowitz efficient frontier for portfolios combining a US defensive step-down autocallable strategy², a global equity index (the MSCI AC World net TR Index) and a global bond index (the Bloomberg Global-Aggregate Total Return). The frontier identifies the highest expected return and corresponding asset weights at each risk level.

Comparing the efficient frontiers with and without the defined return autocallable strategy shows that adding it produces a higher annualised return for all volatility targets historically. For example, at a target volatility of 12%, adding a defined return autocallable strategy increased the annualised return by 0.4% over the last 23 years.

Figure 1: Markowitz efficient frontier with and without the defined return autocallable strategy

Source: WisdomTree, Bloomberg Finance L.P., GS Marquee, as of 24 August 2026. Historical performance is not an indication of future performance, and any investments may go down in value.

Looking at the holdings of those optimal portfolios, a 12% volatility target portfolio comprises 75% equities and 25% bonds when only bonds and equities are available. For the same volatility target, the defined return autocallable strategy weight rises to 64% when looking at a 3-asset portfolio while bonds drop below 4%

It’s worth noting that for low volatility portfolios (up to 12%), the defined return autocallable strategy seems to replace equities (behave as an equity replacement) while for higher volatility, bonds are removed from the portfolio, and the strategy replaces those bonds.

Figure 2: Optimal efficient frontier weights after adding the defined return autocallable strategy

Source: WisdomTree, Bloomberg Finance L.P., GS Marquee, as of 24 August 2026. Historical performance is not an indication of future performance, and any investments may go down in value.

Note that the above analysis uses a backtest to provide a longer time series for the defined return autocallable strategy. That said, repeating the analysis using the existing WisdomTree Defined Return strategy’s 13-year track record and returns for UK equities and bonds produces a similar pattern, with an optimal allocation of 65% to the fund at a target volatility of 10%.

Are those results robust?

The above results use 23 years of data in a single path but how robust are those results? To test this further, we repeat the portfolio optimisation using rolling estimation windows of one, three, five and ten years. Two findings stand out:

• The average allocation to defined return autocallable strategies exceeds 20% at every investment horizon. As the window length increases, the mean weight for the defined return autocallable strategy increases from 27.5% to 58.5%, with longer periods capturing a wider range of market conditions.
• The distribution of optimal allocations narrows as the horizon increases, suggesting more consistent weights when the model uses a longer return history. For the 10-year horizon, the 10th percentile still includes more than 25% of the defined return strategy.

The difference between short and long estimation windows reflects the market conditions they capture. Autocallables’ limited upside can favour equities during sustained rallies, while bonds may offer better protection during sharp declines, which means that, for short horizons and depending on market conditions, a defined return strategy may not be optimal. Longer windows capture a broader mix of conditions which explains the higher average allocation to Defined Return autocallable in those analyses.

Figure 3: Distribution of autocallable allocation across different rolling estimation windows

Source: WisdomTree, Bloomberg Finance L.P., GS Marquee, as of 24 August 2026. Historical performance is not an indication of future performance, and any investments may go down in value.

Conclusion

The optimal allocation to a defined-return strategy over the short term depends heavily on market performance during that period. Allocation may be small in a strong bull market, for example.

However, as the time horizon increases, allocations to the strategy become more consistent because markets don’t move in one direction for very long, and over time, the strategy's diversification and tighter distributions make it more relevant. For long-term equity investing, history suggests that these strategies can serve as an anchor within a strategic asset allocation across a range of volatility targets.

¹ Autocallable use derivative contracts whose payoffs are linked to an underlying asset, often a major equity index. If the asset is at or above a preset level on a scheduled observation date, the autocallable terminates early and typically returns the principal plus the fixed coupon. Otherwise, it rolls on to the next observation date. If it reaches maturity without being called, the investor may lose principal if the underlying asset has fallen below a protective barrier, often around -30%. Defined return autocallable investments are usually built with a laddered portfolio of autocallables.

² For this exercise, we backtest a defined return autocallable strategy based on US step-down autocallables from January 2003 to August 2026. The portfolio invests in up to 52 autocallable contracts on the S&P 500, initiated at weekly intervals and replaced when they are called or mature, making it a diversified portfolio of autocallables where maturity and pin risk are reduced. Each contract has a maximum six-year term, annual observation dates, and call barriers that step down from 100% to 95%, 90%, 85%, 80% and 69% of the initial index level. A capital barrier of 64% of the initial index level applies at maturity.