The framework
- RegimeTrack macro inputs before taking risk.
- ThemesSelect durable ideas that survive noise.
- SleevesImplement with liquid ETFs and budgets.
- ReviewDocument changes and invalidation triggers.
Don’t outsource your portfolio to Kevin in Croydon.
(no, not those kind of models, Kevin).
Financial freedom is control: knowing what you own, why you own it, and being able to sleep at night.
We turn macro regime framing into repeatable ETF sleeves, with a review loop that documents what changed and why.
- No signals. No ‘quit your job’ theatre.
- Track a handful of inputs, not 50 indicators and Fibonacci cosplay.
- ETF sleeves like institutions use baskets: clear roles, clear budgets.
Process, not vibes
From regime framing to practical portfolio implementation.
Regime
Track growth, inflation, liquidity, and geopolitics.
Themes
Prioritize durable themes that persist through noise.
Implementation
Build sleeves with liquid ETFs for practical rebalancing.
Review
Re-check risk budgets and invalidation triggers each cycle.
Regime first, theme second, ETF sleeves third, with a review loop that documents what changed and why.
Read the framework
We start at the macro level: growth, inflation, liquidity, and geopolitics. From that regime view we identify a small set of durable themes (the things that keep showing up in earnings, capex, and policy). Then we go micro: we implement each theme with liquid ETFs so the portfolio is repeatable, rebalanceable, and not hostage to single-name risk. Every sleeve has a job, a risk budget, and an explicit ‘what would change our mind’ trigger.
Institutional DNA
Built by a former PM who designed, risk-managed, and marketed macro platforms at firms managing trillions.
Built + scaled macro platforms
- Designed and managed macro/income sleeves.
- Scaled assets from ~£100m to ~£15bn AUM during tenure.
- Built risk framing and operating cadence (budgets, limits, review loop).
Volatility trading + risk architecture
- Founding-era GARS platform context.
- Built risk framework elements.
- Ran a volatility trading book; platform peaked around ~£70bn.
Macro + micro + systematic
- Built an innovative approach combining macro regime, thematic baskets, and systematic sleeves.
- Alpha/models is the retail version: simpler, cheaper, implementable.
Also led UK multi-asset work and helped launch a machine-learning research programme with the University of Edinburgh.
Examples include Aviva Investors, Aberdeen/Standard Life, Franklin Templeton. AUM references are scale/context, not performance.
Current high-level themes
Reviewed quarterly. Themes can change.
🧠 AI hardware
Infrastructure compute demand keeps chip and enabling-hardware capacity in focus across the cycle.
Why it matters: Core input for next-cycle productivity.
Compute cycleCapex-ledEarnings-linked
⚡ Grid / electrification
Power-network upgrades and transmission build-out remain tied to policy support and long-cycle spending.
Why it matters: Demand outpaces legacy infrastructure capacity.
InfrastructurePolicy tailwindLong duration
🛡️ Defence
Security spending priorities continue to support defence exposure across regional and global procurement cycles.
Why it matters: Budget commitments support long-order visibility.
Budget backedGeopoliticsIndustrial base
⛽ Energy (majors + services)
Integrated producers and services remain relevant where supply discipline and cash generation stay central.
Why it matters: Supply discipline still drives sector behaviour.
Supply disciplineCash flowCycle aware
🪙 Commodities + gold
Real-asset sleeves provide macro regime exposure where inflation and policy uncertainty remain live inputs.
Why it matters: Useful in inflation and policy uncertainty regimes.
Real assetsInflation regimeMacro hedge
🧩 Diversifiers
Liquid diversifier sleeves are used to keep total-portfolio behaviour robust through regime transitions.
Why it matters: Helps stabilize portfolio behaviour in transitions.
Portfolio balanceLiquid toolsRisk control
ETF sleeves = institutional baskets
Blunt version: institutions use baskets and sleeves; so do we.
- Institutions express macro views through baskets, not one stock punts.
- We implement similarly with liquid ETFs, not bespoke swaps/custom baskets.
- Each sleeve has a role, a budget, and a documented review loop.
- Rebalances are process-led, not headline-led.
Why ETFs
Execution-first implementation rules.
Liquidity
Rebalance when you need to.
Transparency
Know what you own.
Cost
Institutional exposure without hedge fund fees.
Active ETFs
Active strategies are increasingly available at ETF fee levels, typically without performance fees.
Institutional baskets
ETFs used as sleeves for basket-style implementation.
Operational simplicity
Repeatable across accounts.
What Alpha/models is / isn’t
Clear positioning around process, implementation, and behaviour.
What it is
- A rules-based macro-to-micro portfolio construction process.
- ETF implementation designed for repeatable rebalancing.
- A framework built to reduce decision fatigue and strategy churn.
- Risk-budgeted sleeves with explicit review and invalidation triggers.
What it isn’t
- Not 0DTE option punting or high-frequency tactical churn.
- Not single-name hero trading dressed up as portfolio management.
- Not backtest theatre or performance-marketing narratives.
- Not a strategy that changes every week because headlines changed.
Private implementation
If you have access credentials, you can view the private Alpha/models implementation page with the current portfolio scaffold.
Open private page →