This post was authored by Adem Tumerkan, Dunham's Content Writer. If you have questions concerning today's topic, please call us at (858) 964 - 0500. Hold us to higher standards.
On Friday, May 2nd, both of our investmentstrategies — the globally diversified model (DunhamDC) and the U.S.-focused model (Dunham US) — triggered fresh SELL signals.
And while the index is still down ~4% for the year (with the NASDAQ down ~7%), the bounce has been aggressive.
Figure 2: MacroMicro.me
Those who leaned into that volatility were rewarded. And now? The system is telling us something different.
That’s why our DunhamDC strategies sold.
Not based on emotion. Not based on opinion.
But based on how the crowd is reacting, which may look a bit greedy here.
A Quick Recap: Selling Greed After Buying Fear
Back in our April 15th blog, we noted that DunhamDC issued its first SELL signal of the year on April 14th following a flurry of BUY signals in March and early April.
Some of the reasons for rising stock prices since then were:
Market optimism over potential tariff relief on tech goods, as well as China willing to entertain trade deals.
Rumors of auto tariff pauses, boosting automaker shares.
The Fed’s dovish tone - amplified by slowing job growth and softening inflation - has increased bets on cuts, fueling “risk-on” behavior.
AI-driven stocks and mega-cap tech continue to dominate capital flows, pushing valuations even higher.
Geopolitical risks – such as Middle East flare-ups, China trade murmurs - are being brushed off (for now).
Because of these variables (and many more), markets have started flashing greed again, with both the technical and fundamentals indicating potentially overbought conditions.
Valuation: The Elephant in the Trading Room
But beneath the headlines, valuations appear still historically stretched.
And so far, that thesis has held up. But we may not be at the end of the road just yet. . .
For context, WisdomTree’s Jeff Weniger noted that history suggests that rallies like the one we’re in can go further than many expect — and often set the stage for strong performance down the road.
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DunhamDC (“DunhamDC”) is a proprietary algorithm of Dunham & Associates Investment Counsel, Inc. (“Dunham”) that seeks to mitigate sequence risk, which poses a threat to an investor's returns due to the timing of withdrawals. The algorithm employs what Dunham considers to be a pragmatic strategy, generally making incremental increases to the equity allocation when global stock market prices decrease and decreasing it when global stock prices increase. This approach is objective, unemotional, and systematic. Rebalancing is initiated based on the investment criteria set forth in the investors application and is further influenced by the DunhamDC algorithm.
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DunhamDC operates within predefined parameters and rules, some or all of which may not be available to review. While this approach can reduce emotional biases and enhance consistency, it may limit adaptability to changing market conditions, economic considerations, or unforeseen events. Extreme conditions may require deviations from the program’s prescribed approach, and such adaptability may be challenging to incorporate. The DunhamDC algorithm is programmed based on specific criteria and rules, it may not capture certain qualitative or contextual factors that can impact investment decisions or movement in the markets. Beyond the initial assumptions used to develop the algorithm, it lacks other inputs or considerations that human judgement and discretion may be necessary to evaluate. DunhamDC may utilize historical data, statistical analysis, and predefined rules. It does not make any predictions and may add to certain investments before they perform poorly or may divest from other investments before they perform well. Dunham makes no predictions, representations, or warranties as to the future performance of any account.
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Asset allocation models are subject to general market risk and risks related to economic conditions.
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DunhamDC has a limited track record, with an inception date of July 31, 2024.
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Index Definitions
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