Model portfolios & fund range

Four
philosophies.
One standard.

Evidence-based, low-cost, publicly tracked model portfolios — built on the same three-frame analytical discipline used in every research brief. Not a fund. Not investment advice. A transparent exercise in applied methodology.

Fund range ↓ MBD portfolios ↓
00 / Methodology

How the portfolios
are built.

Everything published here is documented openly — how each fund is built, what benchmarks it is compared to, and where the data comes from. Read this before drawing conclusions from any return figure on this site.

01

Purpose & status

Educational research project

The model portfolios are illustrative — they do not represent any live fund, trading account, or advisory product. No client capital is allocated. Returns are simulated and do not constitute investment advice.

M1

Frame · Market structure

Where the marginal trade clears

Order-flow telemetry, dealer positioning, futures–physical linkage, and the microstructure effects that drive short-window price formation.

  • Common failure: confusing flow with edge
  • Over-fitting to a single venue's tape
  • Ignoring funding constraints on structure trades
M2

Frame · Physical tightness

When paper and physical diverge

Inventory buffers, lease and funding regimes, delivery windows, and conditions where the futures curve mis-prices the cash market.

  • Common failure: extrapolating one squeeze cycle
  • Forgetting warehousing arbitrage caps tightness
  • Underestimating how fast tight markets loosen
M3

Frame · Macro transmission

From rates to risk assets

How policy, real yields, dollar liquidity, and credit spreads propagate into commodity, equity, and FX pricing — with attention to lags and non-linearities.

  • Common failure: linear-thinking in regime shifts
  • Reading the curve as forecast, not positioning
02

Portfolio construction

Each portfolio follows a documented mandate

  • MACRO — multi-asset overlay around rate-curve inflections and real-yield decomposition
  • STRUCT — equity dislocations from order-flow and dealer positioning
  • SUPPLY — long physical-tightness premia via inventory and delivery signals
  • FACT — regime-aware factor rotation by rate-cycle classification
03

Benchmarks

Compared to closest passive alternative

Each fund is compared to a benchmark that reflects its closest passive alternative — never cherry-picked to flatter returns.

  • MACRO → 60/40 balanced portfolio
  • STRUCT → S&P 500
  • SUPPLY → Bloomberg Commodity
  • FACT → MSCI World
04

Data sources

Public-by-default

  • Price & market data — LME, CME, ICE, Bloomberg/Refinitiv
  • Inventory & supply — COMEX/LME warehouse stocks, EIA, USDA
  • Macro & rates — FRED, ECB SDW, BIS, central-bank minutes
  • Microstructure — published academic literature and exchange disclosures
05

Scope & independence

No paid promotions. No allocation kickbacks.

The brief is a working analyst's notebook — not a trade-recommendation service or signal feed. If an instrument is referenced, it is because the analysis pointed there, not because anyone paid for the mention.

Corrections are published in the next brief, marked with an erratum, and linked back. No silent edits.

01 / Why these portfolios

Understand the
foundations.

Four principles underpin every allocation decision — low cost, evidence-based construction, institutional-grade custody structure, and a transparent track record.

◈

Low-Cost, Great Value

A multi-manager approach that combines editorial oversight with quantitative sub-management.

  • Clear, simple reporting designed for ease of use
  • No hidden platform or switching costs
  • Full methodology published — no black box
Illustrative OCF from 0.20%
◎

An Evidence-Based, Global Strategy

Built on an eight-point investment philosophy grounded in decades of academic research and empirical evidence.

  • Straightforward, diversified construction
  • Systematic rebalancing to control risk exposure
  • Discipline over speculation — always
  • Factor tilts backed by published academic literature
◻

Built on Strong Foundations

A transparent relationship between portfolio construction, custody, and administration.

  • Full separation of investment and operational functions
  • Independent valuation and NAV calculation
  • Institutional-grade efficiency with zero friction
  • Backed by audited methodology and public track record
◇

Proven Strategy, Trusted Performance

The Classic and Tracker ranges replicate strategies with validated long-run Sharpe ratios above 0.7.

  • Consistent top-quartile risk-adjusted returns vs peers
  • Same strategy, now fully unitised and tracked publicly
  • No survivorship bias — all periods published
02 / Fund families

Four diversified
portfolios.

Four portfolio strategies, three rooted in foundational academic finance (Fama–French, Sharpe, and a Fama–French ESG variant) and one proprietary thematic rotation. Each is fully documented — strategy, holdings, weights, rebalancing rules, and benchmark methodology.

Classic fund MBD-CLASSIC Classic
Three-factor model · Fama–French (1993)

Globally diversified equity portfolio targeting the size and value premia documented by Fama & French. Systematic tilts toward small-cap and value, paired with investment-grade fixed income for risk control. Rebalanced quarterly to factor-weight targets.

YTD
+12.0%
Sharpe
0.84
OCF
0.22%
MBD-Classic MSCI World
SMB · HML factor tilts Quarterly rebalance 10 holdings 5 risk variants
Learn more about this product →
Classic ESG fund MBD-ESG ESG Classic ESG
Fama–French + ESG-screened universe

The Classic factor framework applied to an ESG-screened investable universe. Same size and value tilts, but using MSCI ESG-leader and Article 8 SFDR-aligned funds. Excludes tobacco, controversial weapons, thermal coal, and worst-decile ESG scorers.

YTD
+9.0%
Sharpe
0.77
OCF
0.28%
MBD-ESG MSCI World ESG
ESG-screened SFDR Article 8 Low-carbon tilt Factor-aware
Learn more about this product →
Tracker fund MBD-TRACK Tracker
Market portfolio · Sharpe CAPM (1964)

Pure market-cap-weighted global market portfolio implementing the Sharpe CAPM result that the market portfolio is mean-variance efficient. No factor bets, no active selection — just the lowest-cost expression of the aggregate equity and bond market.

YTD
+10.5%
Sharpe
0.79
OCF
0.15%
MBD-Tracker 60/40 benchmark
Market-cap weighted Pure passive Lowest OCF 5 risk profiles
Learn more about this product →
Rotational thematic fund MBD-ROTATE FLAGSHIP Rotational
Thematic rotation · proprietary · 19 holdings

A high-conviction thematic portfolio built around the "picks & shovels" of the AI build-out — data-centre power & cooling (Vertiv, Constellation, Eaton), networking & interconnect (Arista, Marvell, Astera Labs), semis equipment, and the cybersecurity fabric — balanced with an early-stage quantum sleeve (IonQ, Rigetti, D-Wave), precious metals, clean energy, and defensive EU staples. Tilts adjust by macro regime, not by calendar.

YTD
+18.6%
Sharpe
1.12
OCF
0.34%
MBD-Rotate MSCI World
AI picks & shovels Quantum computing Cybersecurity Precious metals Clean energy EU staples
Learn more about this product →
03 / Asset-class strategies

Single-mandate
specialists.

Four focused single-asset-class strategies designed for investors who already own broad diversification and want a specialist sleeve. Each mandate runs independently — discrete return profile, discrete benchmark, discrete risk budget.

Fixed Income strategy MBD-FI Fixed Income
Duration-managed credit barbell

Barbell allocation between long-duration Treasuries (rate-cut hedge) and short-duration credit (carry). Adds opportunistic IG / HY, TIPS, and EM USD exposure. Duration target: 5–7 years. Credit overlay rotates by spread regime.

YTD
+4.2%
Sharpe
0.68
Duration
6.1y
MBD-FI Bloomberg US Agg
Treasuries IG / HY credit TIPS EM USD bonds
Learn more about this product →
Equities strategy MBD-EQ Equities
Multi-factor · quality & momentum

Global equity sleeve combining quality, momentum, low-volatility, and value factor ETFs in a regime-aware blend. Factor weights shift with the rate cycle and credit conditions. No single-stock selection — pure factor expression at the portfolio level.

YTD
+9.5%
Sharpe
0.91
Beta
0.92
MBD-EQ MSCI World
Quality Momentum Min vol Value
Learn more about this product →
Commodities strategy MBD-CM Commodities
Diversified physical exposure

Broad commodity sleeve: precious metals (gold, silver, platinum), energy (oil, natural gas, uranium), industrial metals (copper), and softs (agriculture, wheat). Targeted exposure to roll-yield in backwardated curves; risk-off rotation in contango regimes.

YTD
+11.4%
Sharpe
0.86
OCF
0.41%
MBD-CM Bloomberg Cmdty
Precious metals Energy Base metals Agriculture
Learn more about this product →
Options & Derivatives strategy MBD-OPT VOL ARB Options & Derivatives
Earnings volatility crush · short premium

Systematic short-volatility strategy harvesting the implied-volatility risk premium around single-stock earnings events. Filters for IV30/RV30 ≥ 1.25, term-structure backwardation, and adequate liquidity. Positions held through earnings, closed on IV collapse.

YTD
+14.2%
Sharpe
1.38
Win rate
71%
MBD-OPT S&P 500
Short straddle Iron condor Term-structure Yang–Zhang RV
Learn more about this product →
04 / Research portfolios

The four MBD
model portfolios.

Four fully transparent illustrative strategies tracked publicly — macro regime, market microstructure, physical supply, and regime-aware factor. These drive the editorial research direction, not allocatable capital.

⚠
Illustrative only — not a fund, not investment advice. Returns are simulated. Past hypothetical performance is not indicative of future results.
Macro trading screens MBD-MACRO +8.4% YTD Macro Transmission

Multi-asset macro overlay positioned around rate-curve inflections, real-yield decomposition, and dollar-liquidity regime shifts. Adds or subtracts risk based on transmission state, not consensus narrative.

YTD
+8.4%
vs 60/40
+3.3pp
Max DD
−4.8%
MBD-MACRO 60/40
Macro Multi-asset Tactical Rate-driven
View methodology ↑
Market structure data MBD-STRUCT +6.2% YTD Market Structure Alpha

Captures dislocations from order-flow telemetry, dealer positioning, and zero-day option microstructure effects. A short-window equity strategy keyed off how price formation actually clears.

YTD
+6.2%
vs S&P 500
+1.8pp
Max DD
−5.6%
MBD-STRUCT S&P 500
Microstructure Equity Quant Short-window
View methodology ↑
Physical supply premia MBD-SUPPLY +11.7% YTD Physical Supply Premia

Long physical-tightness premia in metals and energy via inventory, lease, and delivery-window signals. Compensates the futures curve for physical scarcity where paper and physical markets diverge.

YTD
+11.7%
vs BCOM
+4.9pp
Max DD
−6.4%
MBD-SUPPLY Bloomberg Cmdty
Commodities Physical Supply cycle Metals & energy
View methodology ↑
Factor analytics MBD-FACT +7.1% YTD Regime-Aware Factor

Rotates value, quality, and low-vol exposure based on rate-cycle regime classification and credit conditions. The factor stack treated as state-dependent — not a permanent allocation.

YTD
+7.1%
vs MSCI W
+1.7pp
Max DD
−5.1%
MBD-FACT MSCI World
Factor Equity Long-only Regime-aware
View methodology ↑
05 / Philosophy

Eight-point
investment framework.

Every allocation in every portfolio can be traced back to one of these eight principles. They don't change with market conditions. They are the discipline that prevents conviction from becoming recklessness.

01

Risk and return are related

Higher exposure to the right risk factors leads to higher expected returns — but is never a guarantee. Risk is the premium investors pay for the expectation of a greater return.

02

The capital markets work

Prices in deep, liquid markets reflect all available public information almost instantaneously. Attempting to systematically trade on public news after the fact is a losing game.

03

Asset allocation drives returns

The most important factor determining the level of risk and variability of return in a portfolio is asset allocation — not individual stock selection or market timing.

04

Consistent outperformance is rare

Economic uncertainties and random market movements mean it is extremely difficult for anyone — including professional fund managers — to beat the market in the long term. Research suggests most outperformance is luck.

05

Costs matter profoundly

Costs reduce an investor's net return and represent a hurdle any fund must clear before delivering value. A fund charging 1% per annum must generate that in alpha before the investor benefits at all.

06

Investor behaviour is decisive

All too often, investors let their emotions dominate — buying high, selling low, abandoning discipline in volatility. The analyst's role is to help clients maintain discipline through extreme market conditions.

07

Diversification is essential

Diversification spreads risk across many companies, sectors, and geographies. Our portfolios hold the shares and bonds of hundreds of companies in dozens of countries — because no single bet is ever worth the concentration risk.

08

Rebalancing should be market-driven

Unnecessary portfolio rebalancing — arbitrarily timed around review meetings — damages returns and generates costs. Rebalancing should be driven by market movements, returning the portfolio to its target risk exposure.

A publication in safe hands
M

The Market Brief Daily

Independent Macro Research · London

One analyst. No house view to defend, no fund flows to protect, no clients to placate. Every portfolio decision, every allocation change, and every research note is published openly — with the full reasoning, the signals that triggered it, and the conditions under which it would be reversed.

The analyst background combines buy-side multi-asset research with quantitative modelling on commodity supply chains and rate-curve dynamics. The publication is the byproduct of that work — what gets read, what gets modelled, what changes minds.

Buy-side research background Multi-asset · Macro · Structural Published since 2024 No paid promotions 0 undisclosed conflicts

No sell-side house view. No fund flow to defend. No clients to placate. When we're wrong, we say so in the next brief — and explain exactly why the model failed.

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