▾

Regime Library2008 → PresentCondition-aware

Market conditions define the constraint set.

ARC is designed to navigate regime change, adapt to new information, and stay investable across environments that can challenge static portfolios. Instead of forecasting precise turning points, ARC monitors observable conditions in liquidity, real rates, credit spreads, and breadth.

This library examines distinct market regimes across a modern cross-cycle sample from Jan 2008 through Feb 2026. The boundaries are illustrative. Real-world conditions evolve gradually, overlap, and rarely transition cleanly from one state to another.

These regime labels are explanatory tools, not predictive calls. They simplify the dominant constraints and return drivers that were most visible in each period, but real market environments are noisy, overlapping, and only partly knowable in real time.

ARC Overview

Aside from intentionally asymmetric “fun money” sleeves, ARC represents the long-horizon core allocation within the Portfolio Engineers framework.

It is not a performance-chasing portfolio and it is not a macro timing vehicle. It is a rules-based core structure designed to remain investable across environments that challenge static assumptions.

Expand Overview▾

ARC starts from a simple premise: regimes change. Inflation shifts. Liquidity tightens and loosens. Credit spreads expand and contract. Leadership concentrates and then rotates. No single asset class, factor, or geography wins forever, and a “core” that implicitly depends on one environment can become fragile.

ARC is therefore designed to remain rules-based and coherent during both stable and stressful periods. The framework prioritizes structural diversification and disciplined implementation so the portfolio can remain investable when narratives, volatility, and market conditions change.

ARC deliberately diversifies across:

Factors (size, value, momentum, quality)
Cap sizes (large + small)
Regions (U.S. + developed ex-U.S. + emerging)
Diversifiers (e.g., gold)

The structure intentionally sits between two common extremes.

On one end, portfolios concentrated entirely in SPY or VTI implicitly rely on one geography, one market structure, and one leadership cycle. That can work for long stretches, but it also embeds a strong single-market dependency.

On the other end, owning VT (everything, cap-weighted) embraces global diversification but also accepts structural neutrality. A pure total market portfolio captures broad economic growth and global equity beta, but it does not intentionally emphasize specific return drivers or avoid areas that have historically struggled to deliver persistent factor premia. It can also allow index mechanics to amplify concentration when leadership narrows. (See ARC Overlap)

ARC sits deliberately between those poles. It avoids becoming a single-country allocation while also avoiding indiscriminate ownership of the entire equity universe. Instead, it focuses on exposures with identifiable return drivers (size, value, momentum, quality) while maintaining global breadth.

The U.S. equity structure reflects that philosophy: a large-cap core paired with a purposeful small-cap value tilt (AVUV). Momentum exposure (MTUM) acts as a systematic adapter that naturally tilts toward stronger trends and gradually reallocates as leadership rotates.

International exposure is included to reduce reliance on a single country’s valuation environment, policy dynamics, or leadership cycle. Geographic diversification helps reduce dependence on any single market structure.

Gold (IAUM) serves as a structural diversifier. Its role is not to drive equity-like growth but to provide exposure to an asset that historically behaves differently during certain inflation, liquidity, or credibility shocks.

ARC’s macro overlay is intentionally light. It does not attempt to forecast turning points. Instead it functions as a conditions filter, guiding incremental tilts using observable signals such as liquidity conditions, real rates, credit spreads, and market breadth.

ARC is not a low-risk strategy. It remains equity-heavy and will experience meaningful drawdowns. The framework’s objective is not to eliminate volatility, but to maintain diversification and structural coherence across different market environments.

Dispersion across holdings is part of the design. Value vs growth, U.S. vs international, equity vs gold, and momentum vs mean reversion can all behave differently across environments. That dispersion creates opportunities for systematic rebalancing and TDCA over time.

Fund selection follows the same logic: liquidity, mandate clarity, reasonable implementation costs, and vehicles that reliably deliver the exposures they claim to represent.

Current fund roles

AVUV provides U.S. small-cap value exposure using a quality-aware screening methodology.
QQQM provides concentrated exposure to large U.S. technology and growth companies.
MTUM provides systematic momentum exposure, allowing allocations to shift as leadership trends evolve.
RSP provides equal-weighted exposure to the S&P 500, reducing dependence on cap-weighted concentration.
SOXQ / XSD provide semiconductor industry exposure, increasing sensitivity to global technology investment cycles.
AVDV / AVES / IMTM provide diversified international equity exposure with factor-aware tilts.
IAUM provides gold exposure as a structural diversifier within the portfolio.

ARC is presented as a reference implementation of the Portfolio Engineers framework’s long-horizon core allocation. It reflects the current research view on how diversified factor exposures, global breadth, and a light macro overlay can be combined within a coherent structure.

If the underlying evidence or research conclusions evolve, the framework and its implementations may evolve as well.

Bottom line: ARC is not designed to predict every market turn. Its goal is to remain systematic, diversified, and investable across a wide range of environments.

Factor DiversifiedGlobally DiversifiedIntentional ExposureConcentration AwareRules Based CoreLong-Horizon Design

Regime Library

Each regime entry summarizes the backdrop, the key macro pressures, how markets behaved, and how ARC was designed to interpret and respond to those conditions relative to common benchmark exposures.

Want to adjust the timeline yourself?

The regime windows on this page are illustrative. To test different start and end dates, compare alternate market windows, or inspect the same portfolio over a custom period, use the backtest directly in testfol.io.

Open testfol.io and adjust dates

Historical Proxy Disclosure

Some live holdings do not have full return histories back to the start of the test window. Where needed, earlier funds with similar market segment and style exposure are used as historical proxies to extend the analysis.

View mappings

Important: these pairings are selected for directional similarity, not identity. Holdings, methodology, index rules, profitability screens, rebalancing cadence, and fees can differ meaningfully from the live funds.

AVUV←DFSVX

Close proxy

Used to extend U.S. small-cap value exposure farther back in time. Both target smaller, lower-valuation U.S. companies, though implementation details and portfolio construction differ.

MTUM←PDP

Close proxy

Used as a historical momentum proxy. Both represent U.S. equity momentum exposure, though index methodology, universe selection, and rebalancing rules differ.

SOXQ←SOXX

Close proxy

Used to extend semiconductor exposure. Both track the semiconductor industry, though the specific index methodology and holdings can vary.

AVDV←DISVX

Close proxy

Used to extend developed international small-cap value exposure farther back in time. Both focus on smaller developed-market companies with value characteristics, though portfolio construction differs.

AVES←DFEVX

Reasonable proxy

Used as an emerging-markets value proxy. Both emphasize lower-valuation emerging-market companies, though differences in profitability screens, weighting, and market-cap exposure can lead to variation.

IMTM←PIZ

Reasonable proxy

Used as a developed international momentum proxy. Both target momentum exposure outside the U.S., though index construction and security selection differ.

Proxy-based results should be read as illustrative historical approximations of the current allocation concept, not as a perfect reconstruction of the live implementation.

Scan FirstExpand for DetailsBenchmarks Included

These regime windows are analytical frames, not claims that market states begin and end on exact dates. Conditions usually transition gradually and can carry features of multiple regimes at once.

Charts and benchmark tables below are descriptive comparisons, not proof that any framework can identify turning points precisely or avoid severe losses.

Adaptive Regime Core (ARC)

Multi-Regime2008 – Present

A globally diversified, factor-aware core with a light macro overlay designed to reduce one-regime dependency and remain investable across materially different market backdrops.

Regime

Regime·Multi-regime (credit shock → QE → reflation → inflation shock → concentration / dispersion)

Drawdown snapshot

ARC·-51.91%

SPY·-51.45%

VT·-55.48%

60/40·-32.57%

3-Fund·-44.06%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Additional context

Design·Global + factor intentional (not SPY-only, not VT-neutral)

Primary constraint (full cycle)Liquidity—Reserves / Balance Sheet / Funding

View regime breakdownExpand▾

What ARC was (2008 → present)

ARC is a robustness-first core: diversified across factors, regions, and return drivers so the portfolio is less dependent on any single style, geography, or market narrative.
The macro overlay is intentionally light: it is not a prediction engine or a regime calling machine. It is a conditions filter that guides small, systematic tilts using inflation momentum, real rates, liquidity / credit conditions, and market breadth.
ARC’s north star is staying investable: preserving a rules-based structure that reduces the odds of destructive behavioral mistakes during deep drawdowns, leadership whipsaws, and narrative-heavy environments.

Why ARC is needed (what 2008–present taught us)

2008–09: credit and funding stress became the primary market driver. When funding breaks, correlations often rise and “diversification” across risk assets helps less until liquidity is restored.
In much of the 2010s, policy and financial conditions were major return drivers. Markets were heavily shaped by central bank credibility, liquidity, and repeated volatility-driven repricings.
2020: speed became the defining feature. The COVID shock showed that drawdowns can be violently fast and reversals can be policy-led, which increases the value of pre-defined rules over reactive decision-making.
2021–22: inflation persistence and rising real rates became the dominant pricing axis for many assets. When the discount rate resets, both equities and bonds can reprice together.
From 2023 onward, narrow leadership and dispersion became especially important features of index behavior. Breadth can deteriorate beneath strong headline returns, and macro sensitivity can reappear quickly when conditions shift.

What markets did (full-cycle interpretation)

Multiple distinct regimes, one durable lesson: return drivers rotate over time. The “best” portfolio changes with conditions, so a core should be built to survive and adapt, not to depend on one persistent environment.
Over this period, the largest drawdowns were often tied to credit / liquidity breakdowns or discount-rate shocks, rather than ordinary slowdowns alone.
Some of the strongest benchmark runs also came with hidden concentration, where leadership narrowed even as index returns remained strong.
Over the full cycle, the persistent edge is rarely “calling tops and bottoms.” It is more often staying systematic when narratives are loud, leadership rotates, and price action turns violent.

How ARC is designed to respond across 2008 → present

1. Respect the two major fragility zones: credit / liquidity breaks and real-rate shocks. ARC reduces dependence on high-beta concentration when funding conditions deteriorate, and it avoids excessive duration fragility when real rates rise.
2. Stay diversified when it feels inefficient: ARC avoids turning into a single-factor proxy (all growth, all value, all US, all “AI”). The framework prefers robustness over fragile optimization.
3. Tilt small, not heroic: the overlay guides incremental posture changes, not large discretionary swings. The goal is better balance, not perfect timing.
4. Re-risk systematically: ARC adds risk as conditions improve. The objective is not to catch the exact bottom, but to reduce the odds of remaining underexposed after markets materially stabilize.
5. Behavioral guardrails are part of the design: the framework is meant to reduce regret loops, narrative whipsaws, and emotional reinventions after every difficult period.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	527.62%	10.66%	18.46%	0.57
SPY	592.09%	11.26%	19.90%	0.57
VT	304.64%	8.01%	20.60%	0.41
60/40	320.11%	8.24%	11.77%	0.62
3-Fund	344.73%	8.58%	15.50%	0.52

Swipe to view all columns →

Results vs benchmarks

ARC is not a capital-preservation strategy. It remains equity-first, so severe drawdowns are still possible in systemic shocks. The objective is improved robustness, diversification, and behavioral durability, not the elimination of portfolio pain.
ARC will not lead in every regime. In narrow, benchmark-led advances or in periods where a single style dominates, diversification can look like a temporary drag. That tradeoff is intentional.

Global Financial Crisis

Credit2008 – 2009

Solvency fear turned into a funding crisis. Credit seized. Correlations rose sharply.

Regime

Regime·Credit shock / deleveraging

Drawdown snapshot

ARC·-51.91%

SPY·-51.45%

VT·-55.48%

60/40·-32.57%

3-Fund·-44.06%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Seized / widening

Breadth·Collapsed (risk sold indiscriminately)

Inflation·Disinflation → deflation risk

Liquidity·Sudden contraction → emergency backstop

Main lensCredit Stress—Spreads / Funding Pressure

View regime breakdownExpand▾

What the regime was

A systemic credit and funding shock that forced rapid deleveraging across institutions.
In true liquidity events, correlations often rise and “risk assets” sell together, so diversification helps less in the moment.
The turning point is often driven more by stabilization in funding and credit conditions than by clean economic data.

Why it happened

Excess leverage and maturity mismatch turned asset losses into a solvency and confidence crisis.
Funding markets tightened; forced selling and margin dynamics created self-reinforcing feedback loops.
Once counterparty trust broke, the system repriced risk premia aggressively until policy backstops restored basic market functioning.

What happened in markets

Equities and credit repriced sharply; volatility spiked; spreads widened as investors demanded liquidity and safety.
Treasuries and cash-like collateral were favored during peak stress, then risk assets recovered as policy support stabilized funding.
Early recovery leadership was powerful but uneven, often rewarding those who stayed investable rather than those who tried to perfectly time the turn.

How ARC is designed to respond

Prioritize survivability: de-emphasize fragility when credit stress and liquidity conditions deteriorate.
Accept that this is the regime where “everything trades together.” ARC’s edge here is not immunity, but remaining rules-based and investable through the panic.
Re-risk systematically as stress indicators improve. The goal is not precision at the bottom, but reducing the odds of staying too defensive after conditions materially stabilize.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	-7.06%	-3.63%	30.45%	0.01
SPY	-17.15%	-9.06%	34.84%	-0.12
VT	-18.16%	-9.61%	37.48%	-0.10
60/40	-2.58%	-1.31%	18.89%	-0.01
3-Fund	-9.40%	-4.86%	26.03%	-0.09

Swipe to view all columns →

QE Reflation & Early Recovery

Mixed2009 – 2011

Liquidity returned. Risk premia compressed. Confidence rebuilt, but unevenly.

Regime

Regime·Liquidity-driven reflation

Drawdown snapshot

ARC·-23.80%

SPY·-27.12%

VT·-27.88%

60/40·-17.24%

3-Fund·-22.39%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Repairing / tightening spreads

Breadth·Improving but volatile

Inflation·Rebounding from crisis lows

Liquidity·Expanding aggressively

Main lensFinancial Conditions—Policy Support / Financial Conditions

View regime breakdownExpand▾

What the regime was

A policy-driven reflation as emergency measures stabilized the financial system and restored market functioning.
Risk premia compressed rapidly, but confidence remained fragile enough to produce recurring volatility bursts.
Markets transitioned from survival mode to recovery mode.

Why it happened

Central bank asset purchases and liquidity programs improved funding conditions.
Credit markets healed, enabling investors to move back out the risk spectrum.
Extremely depressed starting sentiment amplified the rebound once systemic stress eased.

What happened in markets

Equities rebounded strongly from oversold levels; early leadership often favored cyclicals and value.
Sharp pullbacks still occurred during growth scares and sovereign stress episodes.
Participation broadened over time as confidence rebuilt, though the path was not linear.

How ARC is designed to respond

Increase risk exposure methodically as liquidity and credit conditions improve.
Avoid chasing only the most explosive early-cycle winners; maintain diversified factor exposure.
Stay systematic so volatility bursts do not derail long-term positioning.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	64.02%	18.00%	23.74%	0.81
SPY	44.21%	13.03%	22.72%	0.65
VT	35.42%	10.67%	26.49%	0.51
60/40	36.90%	11.08%	13.18%	0.57
3-Fund	39.09%	11.67%	18.46%	0.80

Swipe to view all columns →

Euro Crisis & Sovereign Stress

Credit2011 – 2012

Sovereign risk bled into banking and funding pressure. Risk-off came in waves.

Regime

Regime·Sovereign stress / funding fragility

Drawdown snapshot

ARC·-22.95%

SPY·-18.58%

VT·-23.81%

60/40·-10.63%

3-Fund·-16.74%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Stressed (spreads widen in bursts)

Breadth·Narrow / risk-off rotations

Inflation·Disinflation bias

Liquidity·Backstops matter (LTRO / ECB actions)

Main lensSovereign Stress—Periphery Spreads / Funding Pressure

View regime breakdownExpand▾

What the regime was

A multi-year stress episode where sovereign financing concerns spilled into bank balance sheets and funding markets.
Unlike a one-shot crash, the path was episodic: repeated risk-on / risk-off rotations driven by policy headlines and rollover risk.
The regime felt structurally fragile: rallies were sharp, but confidence was repeatedly challenged by solvency narratives.

Why it happened

High debt loads and weak growth left peripheral sovereigns vulnerable to refinancing stress.
Banks held meaningful sovereign exposure, tightening the sovereign–bank feedback loop.
Policy credibility, and the perceived limits of support, became one of the main variables markets repriced day to day.

What happened in markets

Equities chopped through multiple drawdowns as spreads widened; quality and defensives often held up better than cyclicals.
Safe-haven duration and high-quality collateral were rewarded during flare-ups; risk assets rallied sharply when policy backstops appeared more credible.
Cross-asset correlations rose during stress windows; diversification worked best when it included genuine ballast.

How ARC is designed to respond

Treat it as a fragility regime: when funding stress rises, prioritize robustness over maximum upside capture.
Expect whipsaws. Use systematic, staged posture changes rather than headline-driven timing.
Re-risk as stress indicators improve, not only when narratives feel fully resolved.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	8.78%	4.31%	19.61%	0.31
SPY	17.19%	8.28%	18.59%	0.52
VT	7.54%	3.71%	21.61%	0.27
60/40	15.00%	7.26%	10.69%	0.70
3-Fund	12.83%	6.25%	15.47%	0.47

Swipe to view all columns →

Commodity Collapse & Deflation Scare

Credit2014 – 2016

Energy credit stress and global growth fears drove repeated risk-off waves.

Regime

Regime·Commodity / credit stress

Drawdown snapshot

ARC·-18.33%

SPY·-12.97%

VT·-19.75%

60/40·-8.45%

3-Fund·-13.73%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Widening (energy-led)

Breadth·Narrow / unstable

Inflation·Falling / deflation impulse

Liquidity·Neutral → supportive

Main lensCredit Stress—High Yield Spreads (energy-heavy)

View regime breakdownExpand▾

What the regime was

A commodity collapse that transmitted into credit markets, particularly high-yield energy issuers.
Global growth concerns, including China sensitivity, produced recurring risk-off episodes.
Leadership became inconsistent and at times unusually concentrated.

Why it happened

Oil oversupply met softer global demand, pressuring commodity prices sharply lower.
Falling energy revenues weakened balance sheets and widened spreads in vulnerable credit pockets.
A stronger dollar likely reinforced tightening conditions globally.

What happened in markets

Energy, materials, and many international equities struggled significantly.
US mega-cap growth often looked relatively defensive by comparison.
Volatility rose in bursts rather than in one sustained bear phase.

How ARC is designed to respond

Avoid overconcentration in commodity- or credit-sensitive areas as spreads deteriorate.
Maintain diversified exposure even if narrow leadership temporarily looks more efficient.
Let stabilization in credit conditions guide incremental re-risking.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	16.27%	5.17%	12.56%	0.45
SPY	30.28%	9.24%	13.34%	0.72
VT	12.34%	3.96%	14.02%	0.34
60/40	20.62%	6.47%	7.82%	0.82
3-Fund	18.11%	5.72%	10.76%	0.56

Swipe to view all columns →

QT Tightening & Powell Pivot

Liquidity2018 – 2019

Liquidity tightened, volatility returned, then policy pivoted and risk repriced quickly.

Regime

Regime·Late-cycle tightening → pivot

Drawdown snapshot

ARC·-20.28%

SPY·-19.32%

VT·-19.91%

60/40·-12.07%

3-Fund·-15.12%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Widened into Q4 '18; eased after pivot

Breadth·Deteriorated into drawdown; improved after pivot

Inflation·Muted / disinflation drift

Liquidity·Tightening → easing (pivot-driven)

Main lensLiquidity Tightening—QT / Reserves / Funding Stress

View regime breakdownExpand▾

What the regime was

A late-cycle tightening regime where policy normalization tightened financial conditions.
Markets repriced growth and duration risk as the “liquidity put” felt less reliable.
The regime flipped when the Fed pivoted and conditions loosened enough for risk assets to recover rapidly.

Why it happened

Policy tightened into slowing global momentum, making risk premia more sensitive to rates and liquidity.
Balance-sheet runoff and rising real rates increased discount-rate pressure, especially on longer-duration assets.
The pivot restored confidence that policy would respond to tightening conditions, helping compress risk premia again.

What happened in markets

Q4 2018 delivered a sharp equity drawdown with widening spreads and elevated volatility.
After the pivot, markets rebounded strongly, often led by duration-sensitive assets and quality growth.
Factor behavior rotated quickly: tightening favored defensiveness; easing rewarded risk and duration again.

How ARC is designed to respond

When liquidity tightens, manage fragility and avoid becoming overly dependent on long-duration leadership.
Use diversified factor exposure so leadership rotations do not force narrative-driven reallocations.
When conditions improve, re-risk systematically. Fast recoveries can punish hesitation just as badly as drawdowns punish complacency.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	10.82%	5.29%	13.21%	0.31
SPY	24.59%	11.66%	14.95%	0.68
VT	13.63%	6.62%	13.68%	0.39
60/40	17.76%	8.55%	8.79%	0.75
3-Fund	16.43%	7.93%	11.22%	0.56

Swipe to view all columns →

COVID Crash & Policy Rescue

Mixed2020

Liquidity broke, policy backstopped markets, and recovery accelerated unusually fast.

Regime

Regime·Liquidity shock / policy rescue

Drawdown snapshot

ARC·-33.85%

SPY·-33.69%

VT·-34.22%

60/40·-21.76%

3-Fund·-28.02%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Severely stressed → repaired

Breadth·Collapse → explosive recovery

Inflation·Falling → reflation expectations

Liquidity·Massively expanding

Main lensFinancial Conditions—Stress → Rapid Easing

View regime breakdownExpand▾

What the regime was

An exogenous shutdown shock that rapidly became a global liquidity event.
Forced selling and uncertainty pushed cross-asset correlations higher across risk markets.
Stabilization arrived once policy support restored basic market functioning.

Why it happened

A sudden economic stoppage created extreme uncertainty around demand, cash flows, and credit.
Funding pressures triggered a dash for liquidity across markets.
Aggressive fiscal and monetary intervention reversed the tightening impulse quickly.

What happened in markets

One of the fastest bear markets on record was followed by one of the fastest recoveries.
Leadership shifted quickly toward duration-sensitive growth as rates fell and liquidity surged.
Participation broadened as confidence returned, though the earliest rebound was highly concentrated.

How ARC is designed to respond

Respect stress signals during liquidity breakdowns rather than assuming immediate mean reversion.
Re-risk systematically as financial conditions improve instead of waiting for perfect clarity.
Maintain diversified exposure so recovery participation does not require rebuilding the portfolio after the turn.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	17.78%	17.84%	28.78%	0.70
SPY	17.39%	17.45%	33.38%	0.64
VT	15.53%	15.59%	32.64%	0.60
60/40	15.07%	15.12%	20.37%	0.77
3-Fund	15.46%	15.52%	25.95%	0.67

Swipe to view all columns →

Reopening → Inflation Shock

Rates2021 – 2022

Inflation built through 2021; policy caught up in 2022 as real yields reset valuations.

Drawdown snapshot

ARC·-24.28%

SPY·-24.44%

VT·-26.34%

60/40·-21.57%

3-Fund·-23.97%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Phase 1·Reopening / inflation build

Phase 2·Policy catch-up / tightening

Credit·Widening but functional

Breadth·Deteriorating

Inflation·High / persistent

Liquidity·Contracting

Main lensReal Rates—10Y TIPS Yield

View regime breakdownExpand▾

What the regime was

A transition from reflation optimism to a discount-rate shock.
As inflation persisted, markets repriced the policy path and real yields moved sharply higher.
The defining feature was that duration broke, pressuring both equities and bonds.

Why it happened

2021: reopening demand collided with supply constraints, pushing price pressures beyond early expectations.
Into 2022: inflation persistence forced a faster shift toward restrictive policy.
Rising real yields increased discount rates, compressing valuations across long-duration assets.

What happened in markets

Phase 1: rotations favored cyclicals and real-economy exposure.
Phase 2: equities and bonds both drew down as higher real rates repriced risk assets.
Leadership shifted toward areas viewed as less sensitive to duration.

How ARC is designed to respond

Treat persistent inflation as a warning that the discount-rate regime may be changing.
Reduce duration fragility through diversified exposure across value, international markets, and real-asset sensitivity.
Use deterioration in breadth and liquidity to manage risk systematically rather than emotionally.
Preserve flexibility so the next expansion can be participated in without rebuilding the portfolio after forced exits.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	4.64%	2.31%	18.10%	0.16
SPY	7.00%	3.47%	19.44%	0.22
VT	-2.32%	-1.17%	18.45%	-0.03
60/40	-3.80%	-1.93%	12.87%	-0.17
3-Fund	-2.81%	-1.42%	15.51%	-0.08

Swipe to view all columns →

AI Melt-Up & Concentration

Breadth2023 – 2024

Index strength was powerful, but participation beneath the surface remained unusually narrow.

Regime

Regime·Narrow leadership / momentum dominance

Drawdown snapshot

ARC·-10.41%

SPY·-9.95%

VT·-11.16%

60/40·-8.42%

3-Fund·-9.82%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Stable

Breadth·Historically narrow

Inflation·Cooling

Liquidity·Improving

Main lensMarket Breadth—Participation / Equal-Weight vs Cap-Weight

View regime breakdownExpand▾

What the regime was

A powerful advance led by a relatively small group of mega-cap technology companies.
Index-level returns were strong even as many stocks and segments lagged.
Dispersion increased meaningfully beneath the surface.

Why it happened

AI investment expectations concentrated capital into a handful of perceived long-duration winners.
Earnings durability, scale, and balance-sheet strength created a scarcity premium.
Cap-weight index construction and benchmark-aware flows likely reinforced existing leadership.

What happened in markets

Major indices rallied strongly while equal-weight and many international exposures lagged.
Breadth metrics often weakened even during periods of index strength.
Index-level volatility remained relatively contained for stretches, but narrow participation increased the risk that benchmark strength overstated underlying market breadth.

How ARC is designed to respond

Participate in upside while avoiding dependency on a single narrative or small handful of stocks.
Maintain diversification even when concentration temporarily looks more efficient.
Treat breadth deterioration as a signal that risk may be rising beneath calm index performance.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	44.22%	20.17%	13.10%	1.09
SPY	58.56%	26.02%	12.81%	1.48
VT	42.29%	19.36%	12.29%	1.10
60/40	35.54%	16.48%	8.93%	1.20
3-Fund	38.75%	17.86%	10.50%	1.14

Swipe to view all columns →

Disinflation & Soft Landing

Inflation2024 – 2025

Inflation cooled as growth held up; rates and earnings drove rotating leadership.

Regime

Regime·Disinflation / soft landing

Drawdown snapshot

ARC·-16.35%

SPY·-18.74%

VT·-16.50%

60/40·-11.62%

3-Fund·-13.80%

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Healthy / contained

Breadth·Improving

Inflation·Cooling, but uneven

Liquidity·Stabilizing / easing bias

Main lensInflation Trend—CPI / PCE Trend

View regime breakdownExpand▾

What the regime was

A disinflation trend with pockets of stickiness, keeping rate expectations reactive.
Economic activity remained resilient enough to avoid a credit unwind, but markets repeatedly repriced the timing and depth of easing.
The marginal driver of leadership was the interaction between real rates and earnings durability.

Why it happened

The lagged effects of prior tightening slowed inflation without collapsing demand.
Supply normalization improved goods inflation while services disinflation progressed more gradually.
As recession was repeatedly deferred, risk premia stayed supported so long as credit conditions remained functional.

What happened in markets

Leadership rotated as markets oscillated between “higher for longer” and “easing ahead,” creating momentum bursts and sharp reversals.
Breadth generally improved versus the prior concentration regime, though rate-sensitive segments still whipsawed around policy expectations.
Earnings revisions and rate volatility, rather than crisis dynamics, were the primary sources of drawdowns.

How ARC is designed to respond

Participate in risk-on when conditions are healthy, but maintain diversification so the portfolio is not hostage to one leadership cohort.
Use real rates, breadth, and credit as a three-check system: avoid overconfidence when leadership narrows or discount-rate pressure returns.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	47.94%	21.68%	14.84%	1.10
SPY	48.11%	21.75%	16.36%	1.01
VT	44.07%	20.07%	14.62%	1.02
60/40	30.68%	14.35%	10.22%	0.93
3-Fund	37.61%	17.34%	12.35%	1.00

Swipe to view all columns →

Emerging / Transitional Regime

Mixed2025 – Feb 2026Provisional

Signals remain mixed and evolving: rates volatility, policy expectations, and earnings durability are driving rotating leadership.

Regime

Regime·Emerging / undeclared (transition zone)

Drawdown snapshot

ARC·-16.37%

SPY·-18.74%

VT·-16.50%

60/40·-11.43%

3-Fund·-13.81%

Because this regime is still forming, the comparative figures below should be treated as provisional and path-dependent.

Performance

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Drawdown

ARC vs SPY vs VT vs 60/40 vs 3-Fund

🔍Click photo to zoom

Macro context

Credit·Tight but functional (watch funding)

Breadth·Rotating / fragile (watch leadership spread)

Inflation·Cooling but sticky pockets (services sensitive)

Liquidity·Normalizing (less tailwind than QE eras)

Real Rates·Volatile / policy-dependent

Main lensFinancial Conditions—Rates Volatility / Credit Stability / Risk Appetite

View regime breakdownExpand▾

What the regime is (so far)

A transition zone where the market is repeatedly repricing the balance between growth resilience, policy expectations, and discount-rate pressure.
Unlike cleaner single-driver regimes, this period features competing signals that can dominate for weeks at a time and then fade.
So far, the most visible feature has been leadership rotation driven by rates volatility, earnings durability, and shifting risk appetite rather than by a single macro variable.

Why it’s happening

Markets are still digesting the post-inflation-shock world: inflation is lower than peak, but the path of rates remains uncertain and highly data- / policy-sensitive.
Liquidity is no longer a persistent tailwind, so earnings quality and balance-sheet strength matter more at the margin.
Narrow leadership risk remains a live issue, which makes breadth a key stability check even when indices appear healthy.

What’s happening in markets

Repeated shifts between “risk-on momentum” and “duration / valuation sensitivity” are creating whipsaw conditions.
Dispersion remains elevated beneath index performance, so stock and sector selection matter more than in broad-beta phases.
At this stage, the most visible near-term vulnerabilities appear to be rates shocks, funding / liquidity surprises, or sudden breadth deterioration, though a more traditional recessionary path cannot be ruled out.

How ARC is designed to respond

Treat this as a probabilistic environment: keep diversification and avoid oversized, narrative-driven bets.
Use a three-check system — financial conditions, real rates, and breadth — to guide incremental de-risking or re-risking.
Stay investable: prioritize rules-based posture over forecast conviction while the regime is still forming.

Benchmarks

Name	Total Return	CAGR	Vol	Sharpe
ARC	39.84%	34.05%	16.17%	1.67
SPY	19.07%	16.48%	18.68%	0.70
VT	28.57%	24.56%	16.42%	1.19
60/40	14.71%	12.74%	11.15%	0.78
3-Fund	22.04%	19.01%	13.72%	1.06

Swipe to view all columns →

Results vs benchmarks

This regime is intentionally marked as undeclared. Any performance figures shown here should be treated as provisional and path-dependent, since both the dominant driver and the eventual regime boundaries remain unsettled.

The Point

ARC is not designed to predict every turn. It is designed to stay investable and rules-based when conditions are unstable, using observable signals rather than narratives, headlines, or static assumptions.

View Portfolios View Framework View Sources