---
title: "Investboard: Weather the Storm Portfolio"
description: "Explore all 30 Storm holdings, compare technology exposure with SPY and inspect the 2021–2025 backtest. Full research PDF, free with no login."
canonical: "https://investboard.com/knowledge/weather-the-storm-portfolio"
language: "en"
published: "2026-10-08"
modified: "2026-10-09"
last_verified: "2026-10-08"
author: "David Bartas"
author_url: "https://investboard.com/about"
---

# Investboard: Weather the Storm Portfolio

Thirty holdings across six asset groups, with a 2021–2025 comparison and a clear view of technology, semiconductor and AI exposure.

## In short

Weather the Storm is a hypothetical 30-holding allocation with 54% equities and 46% in bonds, gold, commodity futures, managed futures and Treasury bills. Its first public edition compares actual fund histories over 2021–2025. The report measures technology, semiconductor and AI exposure, including overlapping holdings inside funds.

- Each position targets 3% or 4%, with a 5% rule applied after modeled daily-close rebalancing.
- The holdings were selected with hindsight; the chart covers actual fund histories in 2021–2025.
- Looking through the funds reveals overlapping companies and shared economic exposures.
- The full report documents every holding, its intended role, risks and the simulation assumptions.

## The storm behind the name

AI can become indispensable while investors earn disappointing returns. Competition, overbuilding, depreciation and the purchase price determine how much of that progress reaches shareholders. Our companion essay, [Is this time different?](/knowledge/is-this-time-different-ai-bubble), explores that gap.

Storm keeps a limited stake in AI and other growth businesses while allocating capital to different economic drivers. It can participate if AI investment succeeds; its construction does not require a crash.

## Diversify the economic drivers

Ray Dalio’s diversification argument is useful because it asks what makes investments behave differently. Bridgewater’s All Weather framework organizes exposures around surprises in growth and inflation. Geographically broad equity funds can still share exposure to the same earnings cycle, interest rates and technology valuations.

Our allocation applies that question to a portfolio with a 54% equity majority. It assigns target capital weights across asset classes; Bridgewater’s institutional approach instead seeks to balance risk contributions.

All return comparisons include price changes and reinvested distributions. Gold contributes through its price; other holdings can also distribute income.

## The allocation and its rules

| Allocation | Target | Intended role |
| --- | --- | --- |
| Equities | 54% | Growth, with several industries and regions |
| Bonds | 20% | Nominal Treasuries and inflation-linked bonds across maturities |
| Gold | 8% | A different response to monetary and confidence shocks |
| Commodities | 7% | Broad commodities and agriculture |
| Managed futures | 7% | Two related strategies with changing long and short futures exposure |
| Treasury bills | 4% | Short-duration liquidity |

Each holding targets either 3% or 4%. The model resets the whole portfolio at completed quarter-ends and whenever a daily closing position exceeds 5%. Market moves can take a position above the limit before correction. In the simulation through September 29, 2026, the largest weight was 5.54% before correction and 4.99% afterward.

**Managed futures: two processes, one related group.** [KMLM](https://kraneshares.com/etf/kmlm/) receives 3% for systematic long and short positions in commodity, currency and bond futures, without equity futures. FMF contributes another 4% through an active managed-futures strategy. Together they can respond to sustained trends in either direction, but reversals and directionless markets can cause losses. The funds are related: their weekly correlation was about 0.68 in 2021–2025.

**Physical gold: two vehicles, one exposure.** [GLDM](https://www.ssga.com/us/en/intermediary/etfs/spdr-gold-minishares-gldm) and IAU each receive 4%. The two instruments respect the position-size rule while expressing one 8% bullion allocation. GLDM’s stated annual expense ratio is 0.10%. Gold introduces a return mechanism independent of corporate earnings, but it still responds to real rates, currencies and investor demand.

**Equities: several routes to earnings.** Casella combines necessary waste services with acquisition-led growth; Lilly offers medical innovation; TGS adds Argentine energy infrastructure; and TPL adds land, royalties and water economics, with an acknowledged AI connection. NVIDIA and QQQ provide bounded participation in a successful AI future. These are intended business roles, not assurances that their share prices will move independently.

## Technology, semiconductors and AI

The individual ticker list understates technology exposure. NVIDIA appears directly and inside funds, while some AI-related businesses sit outside the formal technology sector. Looking through the five equity ETFs gives the following snapshot at target weights, using FMP constituents updated September 29–30, 2026.

Both views show a smaller technology allocation. Those weights describe what the portfolios own; they cannot tell us how either would behave in an AI-led crash.

Technology follows the sector classification. Semiconductors include identified chipmakers and equipment companies. The four lenses overlap and must not be added together. Open the exhibit’s definitions to inspect the AI basket membership.

Combining NVIDIA’s direct position with its fund holdings makes it about 64% of Storm’s identified semiconductor weight. Including the full Samsung Electronics positions, classified separately by FMP, would raise the portfolio’s semiconductor estimate to approximately 5.53%.

Texas Pacific Land is a less obvious connection. Its approximately 3% position has a data-center development link through the [Bolt agreement](https://www.texaspacific.com/investors/news-events/press-releases/detail/176/bolt-and-tpl-announce-strategic-agreement-to-pursue-data). Its existing economics remain tied largely to land, water and energy, so we include the whole holding only in the broader AI interpretation.

Taiwan-linked exposure remains through TSMC, approximately 0.44% via VWO, and NVIDIA’s reliance on [Taiwan’s semiconductor and manufacturing ecosystem](https://blogs.nvidia.com/blog/taiwan-ecosystem-ai-infrastructure/).

These ownership totals are a dated snapshot at target weights. They exclude changing futures exposure in FMF and KMLM.

## The portfolio and the S&P 500

The portfolio is tested from the December 31, 2020 close through December 31, 2025. KMLM launched in December 2020, so extending this exact fund mix into earlier crises would require a proxy. This comparison uses actual dividend-adjusted fund histories in USD, with distributions reinvested. The portfolio includes modeled trading costs; the benchmark is buy-and-hold SPY.

| 2021–2025 measure | Weather the Storm | S&P 500 proxy (SPY) |
| --- | --- | --- |
| Annualized return | 17.03% | 14.34% |
| Total return | 119.49% | 95.38% |
| Ending value of $10,000 | $21,949 | $19,538 |
| Annualized daily volatility | 9.52% | 17.12% |
| Maximum daily drawdown | −10.14% | −24.50% |

Storm’s five-year backtest combined a higher return with a smaller maximum drawdown. The annual table shows how that result varied: SPY led in 2021 and 2023; Storm led in 2022, 2024 and 2025.

<div id="annual-returns" />

| Calendar year | Weather the Storm | S&P 500 proxy (SPY) |
| --- | --- | --- |
| 2021 | 14.74% | 28.73% |
| 2022 | 4.37% | −18.18% |
| 2023 | 18.10% | 26.18% |
| 2024 | 27.90% | 24.88% |
| 2025 | 21.33% | 17.72% |

All five Storm calendar years ended positive, despite the 10.14% daily drawdown shown above. From January 1 to September 29, 2026, the model returned 9.99%, versus SPY’s 12.94%; both precede the publication decision.

## How to read the backtest

## The exposures that deserve attention

The two physical-gold vehicles form one 8% economic exposure. DRDGOLD adds another 3% in gold-related equities with operating risk. Broad commodities still overlap with the agriculture sleeve. Looking through the instruments reveals those shared drivers.

A shock to inflation and discount rates can hurt both stocks and bonds at once. Long Treasuries remain sensitive to rising yields, and inflation-linked bonds still carry real-rate risk.

The portfolio is USD-based. For an investor whose spending is in euros, unhedged currency movements can dominate a supposedly defensive sleeve. Broker access, product structure, fund documentation and local tax treatment also matter. Implementation depends on the investor’s jurisdiction and access to these US-listed instruments.

An AI crash can also become a recession, a funding shock or an inflation problem. Nominal bonds, commodities and trend strategies respond differently to those paths. Lower direct AI ownership helps limit one dependency; it does not guarantee a positive return in every crash.

Capital weights and risk contributions differ. A volatile 3% stock can contribute more risk than a 4% Treasury-bill position, which is why the allocation should be read alongside its company, currency and interest-rate exposures.

## From allocation to a recorded decision

Investboard keeps the decision beside its evidence. This saved note states what to do, what would prompt an earlier review and when the next check is due. The 5% closing-weight cap applies to individual instruments, including funds, rather than the combined NVIDIA exposure.

## The complete portfolio report

The complete report explains all thirty positions: their weights, economic roles, overlapping exposures and failure cases. It also includes the rebalancing rules and full research methodology.

Use that level of detail to question a portfolio’s construction. A written [investment mandate](/mandate) can connect the allocation to loss tolerance, liquidity needs and review conditions before market stress forces a decision.

*First public edition: October 8, 2026. Ownership snapshot: September 30, 2026; prices through September 29. Educational portfolio research; historical results reflect the selection process and assumptions above.*

## Frequently asked questions

### How much technology, semiconductor and AI exposure does it have?

At target weights, technology represents 7.82% of the whole portfolio, semiconductors 5.44%, the identified AI basket 6.59%, and the broader AI basket 10.17%. These categories overlap. AI measures whole-company ownership within defined baskets, using September 29–30, 2026 constituents.

### How was the historical performance calculated?

The simulation uses FMP dividend-adjusted prices, reinvested distributions and modeled trading costs. The stock search used 2016–2025; the complete allocation is compared over 2021–2025, with hindsight and selection bias. The methodology records the assumptions and limits of this retrospective backtest.

### Who can download the complete portfolio?

Anyone can download the complete 28-page report for free, without registering or signing in. English and German editions include all 30 positions, target weights, rationale, risks and methodology.

## Sources

- [KMLM strategy and fund inception](https://kraneshares.com/etf/kmlm/) · KraneShares
- [SPDR Gold MiniShares fund details](https://www.ssga.com/us/en/intermediary/etfs/spdr-gold-minishares-gldm) · State Street
- [Dividend-adjusted historical prices](https://site.financialmodelingprep.com/developer/docs/stable/historical-price-eod-dividend-adjusted) · Financial Modeling Prep
- [The All Weather Story](https://www.bridgewater.com/research-and-insights/the-all-weather-story) · Bridgewater
- [Bolt and TPL announce data-center development agreement](https://www.texaspacific.com/investors/news-events/press-releases/detail/176/bolt-and-tpl-announce-strategic-agreement-to-pursue-data) · Texas Pacific Land
- [Taiwan’s AI infrastructure ecosystem](https://blogs.nvidia.com/blog/taiwan-ecosystem-ai-infrastructure/) · NVIDIA
- [Managed futures holdings](https://www.ftportfolios.com/Retail/Etf/EtfHoldings.aspx?Ticker=FMF) · First Trust