The Launching Pad How a 60-Year Dollar Chart Called 2025 Before It Started

A 60-year pattern. Three confirmation layers. One thesis that called the biggest dollar move before it started.

“If you wait for headlines, you’re late. If you follow regime, you’re early.”

In January 2025, the U.S. Dollar Index sat at 109. Most traders were watching CPI prints. Waiting for the Fed. Refreshing headlines. Doing what they always do—reacting.

I was looking at a different chart. A yearly DXY chart that went back to the 1960s. Every presidency since Lyndon Johnson, color-coded. Sixty years of data. And it was telling a story that nobody else was reading.

That chart—combined with two other confirmation layers—told me the dollar was going lower. Not because of one data point. Not because of one speech. Because of regime. And when the dollar drops, capital moves. It flows into emerging markets. Into gold. Into silver. Into commodities. Into the assets that benefit when the world’s reserve currency weakens.

I positioned my family’s portfolio before the move started. My parents’ retirement. My children’s futures. Real capital. Not paper trades.

Thirteen months later, the Black Star All Weather Macro Portfolio returned +37.72% against the S&P 500’s +14.38%. The options portfolio returned +66.84%. And DXY sits at 97.7—down more than ten points from where it started the year, trading inside the exact zone the chart identified before a single candle of 2025 had printed.

This is the story of how that happened. The thesis, the trades, the mistake I made on crude oil, and why the framework still has more to say.

The macro told you when this was coming. The news just gave people permission to notice.

Before We Start: How I Think

My father is a scientist. He was born in Ghana, earned his PhD in Belgium, and moved our family to the United States with ten thousand dollars. Five people in a one-bedroom apartment in Houston. My brother and I shared a bed. My parents slept on the couch. Dad worked McDonald’s and a gas station at the same time. Mom babysat wealthy children while working church daycares.

We moved from Houston to Mississippi to Maryland—always chasing better schools, always sacrificing comfort for opportunity. In 2002, they bought their first home. First time each of us had our own bedroom.

What does this have to do with trading? Everything.

My father taught me the Scientific Method before I ever heard the word “market.” Observation. Hypothesis. Test. Confirm or invalidate. That is not just how scientists work. It is how I trade. Every thesis follows the same structure. No emotion. No attachment to being right. Just process.

My parents became my first investors. They trusted me with their retirement accounts. That trust sits behind every position I take and every word I publish. There is no paper trading in this story. There is no hypothetical portfolio. There is a family from Ghana whose life savings are managed with the same methodology their father used to earn his doctorate.

One more thing. My technical foundation is built on price action—liquidity, market structure, fair value gaps. These concepts come from a methodology developed by a trader known as ICT. That is the lens through which I read charts. But what I add—what nobody else has built—is the macro layer on top. I connect price action to global capital flows, economic regimes, and cross-asset relationships. The chart tells you where price is. Regime tells you whether it makes sense. That bridge is my edge.

I also want to credit Capital Flows Research. His content gave me the additional layer I was missing and helped shape the way I think about macro. If ICT gave me the technical lens to read price, Capital Flows gave me the framework to understand the forces moving behind it—the capital flows, the regime structures, the cross-asset transmission mechanisms that connect one market to another. The best thing you can do as a trader is be honest about where your education came from. Nobody builds in isolation.

Stanley Druckenmiller is the best macro investor of our time. I have watched every interview the man has done. What I did not realize until later was how many of his philosophies I had already internalized. His concept of “invest and then investigate”—take the position when the setup is there, then let the market confirm or deny your thesis—is exactly how I operate. He taught me that conviction backed by process is not recklessness. It is edge. His willingness to be wrong, to change his mind publicly, to size up when conviction is highest—those principles are in the DNA of how I manage this portfolio.

And Linda Raschke. She is quirky and weird and brilliant. She was the institutional version of ICT for me before I ever found ICT. Many of his concepts tied directly to hers—market structure, the behavior of price around key levels, the rhythm of how markets move. But what I admired most about Linda was that she always showed her flaws. She never hid the losses or the bad reads. She showed you the full picture because she understood that the full picture is what teaches. That honesty is what I try to bring to 34 Macro. If you only see the wins, you learn nothing.

Everything starts with the chart. Then macro confirms. Then the best vehicle to express the thesis is identified.

ACT 1

The Setup

January 2025

The Chart Nobody Was Looking At

Pull up a yearly DXY chart. Not daily. Not weekly. Yearly. Go back to the 1960s. Color-code every presidency—Republicans in one color, Democrats in another. And then just look.

What you see is a pattern that has held for more than sixty years:

Republican administrations tend to see dollar depreciation or consolidation. Nixon, Ford, Reagan’s early years, both Bushes, Trump’s first term—the dollar either fell or went sideways.

Democrat administrations tend to see dollar appreciation. Clinton oversaw one of the strongest dollar rallies in history. Obama saw a significant dollar rally in his second term. Biden’s presidency coincided with the dollar pushing toward multi-decade highs.

This is not a political statement. It is a pattern. And patterns exist to be tested, not debated.

The Fair Value Gap

Now let me explain a concept that is central to how I read charts. A fair value gap—or FVG—is a price imbalance. It’s a zone on the chart where price moved so aggressively in one direction that it left behind an area where buying and selling didn’t fully meet. Think of it like a gap in a conversation—something was left unsaid, and eventually the market comes back to fill it.

On the yearly DXY chart, there was a fair value gap created during Trump’s first term, roughly in the 94–100 zone. Price had moved through that area without fully balancing. It was sitting there, unfilled, waiting.

Entering 2025, DXY was elevated near 108. That put it well above the imbalance. The technical structure was pointing down toward the gap.

Three Layers of Confirmation

I never trade on one signal. The Scientific Method demands convergence. Here were the three independent layers that confirmed the thesis before 2025 started:

Layer 1: Technical Structure. The unfilled fair value gap from Trump 1.0 in the 94–100 zone. Price tends to return to imbalances. This is a foundational principle of how markets rebalance.

Layer 2: Political Cycle Pattern. Sixty years of data showing Republican administrations correlate with dollar weakness. Trump was entering his second term in January 2025.

Layer 3: Stated Policy. Trump explicitly said he wanted a weaker dollar. He announced the Golden Dome missile defense program and signaled tariff policies that would create uncertainty in global trade. When the most powerful person in the world tells you what they want the dollar to do—and the chart already agrees—you listen.

Three layers. Three independent confirmations. Technical, historical, and rhetorical. This is not a prediction. This is a thesis with evidence.

Not a headline trade. A regime trade.

What Dollar Weakness Means for Global Capital Flows

Here is where most people stop. They see “dollar goes down” and they don’t know what to do with it. But when you understand macro, you understand the rotation. A weakening dollar is not just a currency move. It is a transmission mechanism that flows through every asset class:

Gold and silver are priced in dollars. When the dollar weakens, they become cheaper for the rest of the world to buy. Demand rises. Prices rise.

Emerging market equities benefit because many EM countries carry dollar-denominated debt. A weaker dollar makes that debt cheaper to service, improving corporate balance sheets and sovereign credit conditions across the developing world.

Commodities broadly benefit for the same pricing mechanism as gold—they’re dollar-denominated, so a falling dollar supports prices across the complex.

International equities benefit as capital rotates out of US assets seeking better relative value abroad.

This is what I mean by cross-asset confirmation. The dollar thesis doesn’t live in isolation. It tells you exactly where capital should flow. The chart gave me the direction. The macro told me the vehicles.

The Portfolio Build: February 2025

On February 10, 2025, I started the rotation. I sold down US-centric positions—trimmed NVIDIA, Amazon, Alphabet, Microsoft, and liquidated energy services names like Occidental Petroleum and Schlumberger. I cut consumer and healthcare names. I was clearing the deck.

Then, between February 13 and 14, I built the core thesis positions in a concentrated burst:

Gold: GLD—SPDR Gold Trust. Approximately 70 shares across multiple fills in the $267–270 range.

Silver: SLV—iShares Silver Trust. 60 shares around $29–30.

Emerging Markets: VWO—Vanguard FTSE Emerging Markets ETF. 70 shares at $45.24.

International Equities: VXUS—Vanguard Total International Stock Index. 52 shares at $62.20.

Metals & Mining: PICK—iShares MSCI Global Metals & Mining. 50 shares in the $36–38 range.

Agriculture: DBA—Invesco DB Agriculture Fund. Built to over 200 shares across February at $26–28.

Energy: XLE—Energy Select Sector SPDR. 72 shares at $88–91.

Industrials: XLI—Industrial Select Sector SPDR. Built to over 100 shares through February.

Every one of these positions was an expression of the same thesis: dollar weakness drives capital into commodities, emerging markets, and real assets. The chart told me the direction. The macro told me the vehicles. The Scientific Method said: test it.

In the options portfolio, the signal came even earlier. On January 6—the first trading week of the year—I opened SLV $28 calls. Silver bullish before anyone was talking about it. Those calls were bought at $0.95–1.21 and would be sold in March at $2.15–2.99. The options were the leading edge of the thesis.

By late March, I was expanding the international leg: Japan (EWJ), India (INDA), Latin America (ILF), Europe (FEZ), and copper (CPER—200 shares). I also added PLTR and started building positions in Chinese ADRs like FUTU and ATAT. The thesis was widening its expression as confirmation accumulated.

ACT 2

Liberation Day

April 2, 2025

April 2, 2025. The Trump administration announced sweeping tariffs. Markets panicked. The S&P 500 dropped hard. Headlines screamed about trade wars and recession risk. Twitter was on fire. Everyone was running.

I leaned in.

On Liberation Day itself, I bought 100 shares of Palantir across fills from $81 to $88. I added more India (INDA), more Latin America (ILF), more Japan (EWJ), more Europe (FEZ). I bought META at $560. By April 4, as the selloff deepened, I bought META again at $500. I added Newmont (gold miner), Pan American Silver, and more EM exposure.

Why? Because the framework said this was not a regime change. This was a headline event within an existing regime. The dollar weakness thesis was not broken by tariffs—it was reinforced by them. Tariff uncertainty weakens the dollar. Trade disruption accelerates capital rotation out of US-centric assets. The macro was screaming the same thing it had been screaming since January. The news was just louder.

Pressure, not panic. The market moves before the headlines make sense.

In the options portfolio, the hedge I’d placed pre-Liberation Day paid off perfectly. In late March, I had bought SLV $28.50 puts—a protective bet against a short-term silver pullback. When silver dropped on the April panic, I sold those puts for a profit: bought at $0.11 average, sold at $1.31–1.35. The hedge worked exactly as designed. Discipline, not prediction.

The Crude Oil Mistake

Now let me tell you where I was wrong. Because if this were a highlight reel, it would be worthless.

Going into Liberation Day, I was long crude oil. I had bought ConocoPhillips (COP), EOG Resources, Baker Hughes (BKR), and I was adding to those positions into early April. I had emotional attachment to crude from day trading it. I was leaning on an energy thesis that didn’t have the same structural confirmation as the dollar weakness trade.

When Liberation Day hit, crude oil got destroyed. Tariffs mean slower global growth. Slower growth means less energy demand. The macro was clear, and I had ignored it because I was attached to the name.

Here is what I did: I cut. On April 3, I sold EOG. Over the following days, I trimmed COP. I took the loss, accepted it, and reallocated that capital into positions that were aligned with the regime—more gold miners, more silver miners, more defense.

The Scientific Method does not have an ego. Observation said the timing was wrong. I invalidated and moved on. The portfolio still returned +37.72% over the year because the core thesis was right and the discipline to cut the mistimed trade was immediate.

But here is the thing I have learned about myself over the years, and it is one of the most important things I can share with you: I tend to be early. Not wrong. Early. The oil thesis was not broken—the timing was off. I was positioned for energy strength heading into a tariff shock that temporarily crushed demand expectations. The macro eventually caught up. Baker Hughes and Schlumberger—names I held through or re-entered—are performing. I also pivoted the energy thesis toward natural gas through EQT, recognizing that AI data center power demand and geopolitical risk were the stronger structural drivers than crude oil price direction. The thesis was right. The entry was premature. The expression evolved.

Being early is uncomfortable. It tests your conviction. It makes you question whether you are seeing something real or seeing what you want to see. But if the framework is sound—if the observation, hypothesis, and confirmation layers are intact—then being early is a timing problem, not a thesis problem. And timing problems are solved with discipline: cut when the evidence says cut, re-enter when the evidence says re-enter.

Being early and being wrong are not the same thing. The framework tells you the difference. Discipline tells you what to do about it.

The Reallocation: April–June 2025

After Liberation Day, I redeployed the energy capital and then some. The thesis was evolving—dollar weakness plus geopolitical uncertainty plus the tariff shock meant defense, precious metals, and commodity exposure needed to be heavier. Here is what I built:

Defense & Aerospace: ITA (iShares U.S. Aerospace & Defense ETF), Howmet Aerospace (HWM), RTX Corporation, and Espey Manufacturing (ESP)—a small-cap defense electronics name. The Golden Dome announcement plus rising global defense budgets made this a regime trade, not a headline trade.

Silver Miners: First Majestic Silver (AG)—I bought 750 shares across April 25 at $6.03–6.10. Pan American Silver (PAAS). Coeur Mining (CDE). Silver miners are leveraged expressions of the silver price. When SLV moves 10%, the miners can move 30–50%. This is how you find the best vehicle to express the thesis.

Gold Miners: Newmont (NEM)—52 shares across April at $44–54. When gold is in a regime move, the miners offer asymmetric upside.

Copper: CPER positions were maintained and I added copper calls in the options portfolio. Copper is a 6–12 month leading indicator for global infrastructure buildout—including the AI data center supercycle.

Platinum Group Metals: Sibanye Stillwater (SBSW)—150 shares in June plus October $7 calls in the options book. Diversifying the precious metals exposure beyond gold and silver.

Energy Midstream: ONEOK (OKE) and Archrock (AROC)—pipeline and compression companies that benefit from energy volume regardless of commodity price direction. I would later cut both of these as I refined the energy thesis further, but at the time they represented less directional exposure than my crude positions.

By June, the options portfolio reflected the same macro architecture as the equity portfolio: CPER calls (copper), XLE calls (energy), XLB calls (materials), SBSW calls (PGMs), KIE calls (insurance), AROC calls (midstream), BKR calls (energy services). ETF-based expressions where the macro thesis does the work without idiosyncratic single-stock risk.

ACT 3

The Proof

February 2026

Where DXY Sits Today

DXY closed the week at 97.789.

It was 108 entering 2025. That is a ten-point drop in thirteen months. And the price is now sitting inside the exact fair value gap from Trump’s first term that I identified before the year started. The 94–100 zone. The imbalance that had been sitting unfilled on the yearly chart.

The thesis is not complete. The lower end of that gap is around 94.2, which aligns with the 0.25 Fibonacci retracement of the entire DXY range going back to its all-time low. That level is the next magnet. The regime has not changed. The pattern has not broken.

The Portfolio Numbers

These are the actual returns from my family’s Fidelity accounts. Not backtested. Not hypothetical. Not a demo account.

Black Star All Weather Macro Portfolio: $301,819.16. +10.70% YTD 2026. +37.72% trailing one-year return versus the S&P 500’s +14.38%.

Black Star Macro Options Portfolio: $22,392.86. +73.57% YTD 2026. +66.84% trailing one-year return versus the S&P 500’s +14.38%.

Total Fidelity family accounts: $391,835.83.

The best performers were metals. Gold, silver, and the miners led. The ETF-based options outperformed single-name options because the macro thesis eliminates idiosyncratic risk—when the regime is right, the sector moves, and you don’t need to pick the perfect stock. You need to pick the right expression of the right thesis.

What the Framework Is Saying Now

The DXY thesis is still in progress. Price has entered the fair value gap but has not completed the fill to 94. As long as the regime holds—Republican administration, stated preference for dollar weakness, tariff-driven trade uncertainty—the thesis has further to run.

But the portfolio has not stood still. The framework evolves as the data evolves. Let me walk you through what happened after that initial post-Liberation Day reallocation, because the second half of 2025 and early 2026 show how a macro portfolio adapts in real time.

The Evolution: Q3 2025 – The Agriculture Rotation and Defense Build

By July, the thesis was expanding into agriculture. I sold down the broad DBA position and rotated into more targeted expressions: CF Industries (nitrogen fertilizer), Corteva (crop science), Bunge (grain processing), and the Teucrium Corn Fund (CORN). I also maintained Archer-Daniels-Midland (ADM), which I had been building since February. When you see the same macro pressure—dollar weakness plus supply disruptions plus food security concerns—you don’t just hold the generic ag ETF. You find the specific companies that benefit most from that pressure. That is what I mean by finding the best vehicle to express the thesis.

This was also the moment the portfolio underwent a structural shift. After surviving the tail risk of Liberation Day, I moved from holding ETFs as core positions to concentrating on single names. The market had shown me who the true winners were. The broad sector ETFs—XLI, XLV, XLE, VWO, VXUS—had served their purpose during the initial thesis build when I needed diversified exposure to a directional view. But after April, the dispersion within sectors became wide enough that picking the right individual names offered significantly better risk-reward than owning the basket. The ETFs were the scaffolding. The single names were the building.

The defense build accelerated. I added BWXT (BWX Technologies—nuclear submarines and reactors), Kratos Defense (KTOS—autonomous drones and AI defense), LASR (nLIGHT—laser weapons), and AAR Corp (AIR—aircraft maintenance). TTM Technologies (TTMI) sits at the intersection of defense and AI—they manufacture circuit boards for both military systems and AI servers. The Golden Dome program and the AI drone revolution in Ukraine were not headline trades. They were regime trades. Defense spending was structurally increasing, and I was building the portfolio to capture that.

I also started building positions in AI infrastructure plays: Vertiv (VRT—data center cooling) and Amphenol (APH—connectors for AI servers and data centers). The AI capex supercycle—$660 billion in committed hyperscaler spending—was creating demand for copper, power, and industrial infrastructure. That connected directly to my existing metals and industrials thesis.

Africa entered the portfolio. I bought over 1,000 shares of Jumia Technologies (JMIA)—sometimes called the Amazon of Africa. When the dollar weakens and emerging markets benefit, the frontier markets with the youngest populations and fastest-growing digital economies offer asymmetric upside. Most people weren’t even looking at African e-commerce. The framework said look.

Q4 2025 – The AI Pivot, Cybersecurity Lesson, and Re-engagement

By October, something shifted. I started re-entering US tech names I had sold in February. I bought Constellation Energy (CEG—nuclear power for data centers), Eaton (ETN—electrical infrastructure), Caterpillar (CAT—construction equipment for data center builds). Then in November and December: NVIDIA, Microsoft, Alphabet, Amazon.

I also developed a strong cybersecurity thesis in Q4. The logic was sound: AI creates more sophisticated attacks, which drives more demand for defense. I bought Palo Alto Networks (PANW) and Datadog (DDOG). But SaaS sold off aggressively at the end of the year—the entire traditional software sector was getting repriced as AI replaced what those companies sell. I recognized the macro environment was hostile to the vehicle even though the thesis was valid, and I cut both. Sold PANW around $178. As I write this, it’s below $150. That is the framework working—the thesis can be right and the expression can still be wrong if the regime is working against the sector.

Why the broader re-entry into US tech? Because the AI infrastructure buildout was becoming the dominant macro force alongside dollar weakness. The two themes were not competing—they were converging. A weaker dollar makes US-built AI infrastructure more attractive for global buyers. The $660 billion capex commitment was creating real demand for copper (my FCX position), power (CEG, Bloom Energy), and industrials (CAT, ETN, VRT). The regime was the same. The expression was evolving.

Q1 2026 – Where We Are Today

The most recent trades tell you exactly where the framework is pointing. In January, I bought Freeport-McMoRan (FCX—copper) and Southern Copper (SCCO). Copper is the transmission mechanism between AI infrastructure and the real economy. Every 100-megawatt data center uses approximately $60 million in copper. The global copper deficit is expanding. I also picked up Avino Silver & Gold (ASM), which gives me copper exposure alongside precious metals—a single name that sits at the intersection of two thesis legs. These replaced the CPER ETF position I had cut back in Q3—again, moving from ETFs to the single names that the market had shown me were the better expressions.

On the energy side, I built a significant position in EQT Corporation—the largest natural gas producer in the United States. This was a deliberate pivot from the crude oil thesis that had been premature. Natural gas has a cleaner structural tailwind: AI data centers need enormous amounts of power, and natural gas is the fastest path to bringing that power online. Add geopolitical risk and European energy insecurity, and natural gas has both the demand floor and the supply constraints that crude oil lacked in April. The thesis evolved. The discipline is the same.

I added Leidos (LDOS—defense IT and AI), more Constellation Energy (nuclear power for data centers), LMB (Limbach—mechanical systems for data centers and mission-critical facilities), and added to Palantir. I took profits on silver miners that had run—AG and Avino Silver—because the asymmetry had compressed. Not because the thesis was wrong, but because the risk-reward had changed. Sell the winners when the edge narrows. Redeploy into the next expression.

That is the framework in motion. It does not stay static. The regime is the anchor. The expressions rotate as the data rotates.

What I’m Watching

NVIDIA earnings on February 25, 2026. This is the health check for the entire AI infrastructure buildout. $660 billion in committed hyperscaler capex is flowing through the system. NVIDIA’s data center revenue tells you whether that flow is accelerating or decelerating. That capex demand connects to copper, power, and the industrial complex that makes up a significant part of my portfolio.

The AI supply chain. TSMC monthly revenue on the 10th of each month. ASML quarterly earnings. These are 12–18 month leading indicators for semiconductor demand. When $660 billion in committed capital is being deployed, the companies that build the infrastructure—chips, memory, packaging, power, copper, cooling—are the transmission mechanism from tech capex to real economy activity.

The dollar regime. DXY at 97.7 is not the end. The FVG target is 94. If the dollar continues lower, the EM, commodity, and metals thesis has further asymmetry. If DXY reverses and reclaims 100+ with conviction, the thesis needs to be re-evaluated. No ego. Just process.

Why I’m Writing This

I grew up not knowing what a stock was because nobody around me owned one. The market was not designed for people like me. It was not designed for first-generation kids in one-bedroom apartments. It was not designed for families where both parents worked two jobs.

But here is what I learned: the market is not inherently hard. It was designed to keep marginalized people out—by using language they don’t know, systems they can’t access, and information that stays behind closed doors.

34 Macro exists to open those doors. Not to create dependence. Not to give you signals to blindly follow. To teach you the framework. To show you how one macro theme connects across asset classes to its best expression. To make institutional-level thinking accessible to the everyday person.

The goal is not for you to depend on me. The goal is for you to not need me.

This is the first piece. Every Sunday, I’ll publish a free weekly that connects the dots most people miss—the economic data, the cross-asset flows, and the regime framework that tells you not just what happened but what it means. If you want the daily portfolio management, the specific levels, and the deep dives, that’s the paid tier.

But the weekly is free. Because the framework should be accessible to everyone.

The tape is telling the story. You just have to learn to read it.

Glossary

DXY (U.S. Dollar Index): A measure of the dollar’s value against a basket of six major currencies (euro, yen, pound, Canadian dollar, Swedish krona, Swiss franc). When DXY rises, the dollar is strengthening. When it falls, the dollar is weakening.

Fair Value Gap (FVG): A price imbalance on a chart where price moved so quickly that buying and selling didn’t fully balance. Markets tend to return to these zones to “fill” them. Think of it as an IOU the market left behind.

Regime: The dominant macroeconomic environment driving markets. A regime trade positions for the structural trend. A headline trade reacts to news. Regime trades last months or years. Headline trades last hours or days.

Transmission Mechanism: How a change in one variable flows through to affect other assets. Example: dollar weakness → cheaper commodities for foreign buyers → higher commodity prices → higher commodity producer stocks.

Cross-Asset Confirmation: When multiple asset classes—equities, currencies, commodities, bonds—are all pointing in the same direction. This convergence increases confidence in a thesis because it means the signal is not isolated to one market.

EM (Emerging Markets): Developing economies like Brazil, India, China, South Africa, Mexico. Their currencies and equity markets are sensitive to dollar movements because many carry dollar-denominated debt.

ETF (Exchange-Traded Fund): A fund that trades like a stock and holds a basket of assets. GLD holds gold. SLV holds silver. VWO holds emerging market stocks. ETFs let you express a macro thesis at the sector or asset class level without picking individual stocks.

34 MACRO

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