A framework that sized positions in dollars would systematically mis-state what the book is actually exposed to. Every limit in this document is therefore derived from a measurement, and every measurement is one we publish.
This document sets out how positions are sized, how exposure limits are set, and what the firm measures to know whether either is working. It governs the paper book as it stands today — nine ETF lines, four sleeves, $100,000 of notional capital — and it binds from the first trade placed after its issue.
The order of what follows is deliberate. Measurement comes first, because in this framework the limits are not policy preferences that happen to be expressed as numbers; they are consequences of what the covariance matrix says about the book. Change the measurement and the limits move. That is the intended behaviour.
Equities account for 50% of the book's capital but an estimated 86% of its risk, because equity volatility and intercorrelation dwarf those of the defensive sleeves. The cash sleeve adds essentially no risk. The Treasury sleeve contributes about 2%. In risk terms the book is not the conservative portfolio its 35% cash-and-bonds weight implies.
That is intentional for a book built to showcase equity research. The defensive sleeves diversify and provide dry powder; they do not neutralise equity risk, and were never intended to. But it means a dollar-denominated limit framework would describe a portfolio that does not exist.
Interpretation. BIL is a fifth of the book and none of its risk. SPY is a fifth of the book and roughly a third of its risk. Any rule expressed as "no more than X% of the portfolio" is, for a position like BIL, not a risk limit at all — and for a volatile single name, a far looser one than it appears. The sizing rules below resolve this by making the binding constraint a risk constraint, with the capital cap retained only as a backstop.
Every limit downstream depends on the covariance matrix, so the estimation procedure is specified rather than assumed. The inputs below are recomputed monthly and on any change to holdings.
| Price history | Daily adjusted close on a rolling ~3-year window — 752 observations at the 18 June 2026 build (21 Jun 2023 – 18 Jun 2026). |
|---|---|
| Source | Yahoo Finance, pasted into the Price Data sheet of the HRP workbook. |
| Estimator | Ledoit–Wolf shrinkage applied to the covariance matrix before any risk-parity step. Sample covariance across a handful of single stocks is too noisy to cluster on. |
| Recompute | Monthly, and on any change to holdings. |
| Minimum history | 250 trading days before any single name may be sized. Without it the covariance input does not exist. |
Reference volatilities from the 18 June build, used throughout the sizing rules below:
These are the definitions used wherever a figure appears on the site or in a report. No metric is published that cannot be reconstructed from a stated source and a stated method.
| Exposure | % of net asset value |
| Beta | Against S&P 500 total-return index |
| Volatility | Annualised σ of daily returns, rolling ~3y |
| Risk contribution | Share of total variance, full covariance matrix |
| Maximum drawdown | Peak-to-trough on stitched daily + 15-min NAV |
| Sharpe ratio | Stated with the risk-free rate used — currently 4% |
| Returns | Paper account · no fees · no slippage assumption |
True hierarchical risk parity — the dendrogram and recursive bisection — cannot be performed in native Excel formulas. Sleeve tagging supplies the hierarchy and the sheet performs the inverse-variance allocation within and across sleeves. This is a transparent, macro-aware risk-parity weighting, not textbook HRP, and it is described that way in anything published. When the researched sleeve reaches eight or more names, the clustering step moves to Python where the dendrogram can actually be computed.
Risk contribution is measured from the full covariance matrix rather than standalone volatility. The distinction matters: a name's own volatility says what it does in isolation, while its marginal contribution says what it does to this book, given everything already in it. Only the second is a risk number.
Assets are tagged to exactly one of five sleeves. The sleeve is the hierarchy — it is supplied by judgement rather than discovered by an algorithm, and that is stated openly rather than presented as an output of the model.
Held at a fixed weight, outside risk parity, so a near-zero-volatility instrument cannot distort the optimisation.
Inverse-variance within sleeve, inverse cluster-variance across sleeves.
As above. Gold is sized at twice commodities, being the lower-correlation and more reliable diversifier.
As above, with the SPY floor binding before the risk-parity weight does.
As above, subject to every single-name limit in the sizing section. Currently empty; the book is 100% ETFs at the issue date.
Capital balances risk within each sleeve by inverse variance, then across sleeves by inverse cluster-variance, with cash held at a fixed weight. Holding cash outside the optimisation is not a convenience: an instrument with near-zero volatility attracts an unbounded inverse-variance weight, and would otherwise consume the book.
Four principles govern sizing. A position is sized by what it contributes to portfolio variance, not by what it costs. Every single name faces both a capital cap and a risk cap, and the binding limit is whichever is smaller — there is no averaging between them. Floors are as binding as ceilings, because the framework fails as easily by abandoning the defensive base as by over-concentrating. And limits are checked before the order, not after the fill.
| Limit, as % of NAV | Floor | Target | Ceiling | Type |
|---|---|---|---|---|
| Single researched name, at cost | 2.5% | 3.5–4.5% | 6.0% | Hard |
| Single researched name, at market | — | — | 7.5% | Hard |
| Single ETF line | — | — | 20.0% | Hard |
| Researched sleeve, total | — | 50% | 55% | Hard |
| SPY anchor | 10% | 12% | 20% | Hard |
| Defensive base (IEF + GLD + DBC) | 25% | 30% | 35% | Hard |
| Cash sleeve (BIL) | 8% | 8–10% | no cap | Hard |
| Total equity (base + researched) | — | 62% | 70% | Hard |
| Gross exposure | — | 100% | 100% | Hard |
| Number of researched names | 8 | 10–14 | 16 | Soft |
The governing rule is that no single researched name may contribute more risk than the SPY sleeve. SPY is the benchmark; a name the firm has researched may be sized to matter, but not to matter more than the thing it is measured against.
At the SPY anchor of 12% and SPY volatility of 15%, the sleeve's volatility-weighted contribution is 12 × 15 = 180. A candidate name is therefore capped at:
The risk cap and the 2.5% minimum position cross at approximately 72% annualised volatility. A name more volatile than that cannot be sized large enough to be worth holding without breaching the risk cap, and is therefore outside the investable universe regardless of conviction. This is the framework's answer to the pre-revenue biotech question, and it is an answer given in advance.
Proxy versus true contribution. The w × σ formulation above is correlation-blind, and deliberately so: it is the pre-trade screen. It is computable in seconds, it is conservative for names correlated to the book, and it never requires a model run to answer "can I own this at all". The binding measure at monthly review is the true marginal risk contribution from the full shrunk covariance matrix. Where the two disagree, the covariance figure governs and the position is adjusted at the next review. A name that passes the proxy but fails on true contribution is almost always a name highly correlated to something already held — which is information about the book, not just about the name.
IEF, GLD and DBC are off-limits to the deployment programme and may not be sold to fund a researched position under any circumstance. SPY may be trimmed but never zeroed, with a floor of 10% of NAV.
These are the only holdings in the book that are not for sale, and the reason is structural: the defensive base is what allows a concentrated single-name book to be run at all, and the SPY anchor is what makes benchmark attribution honest. A firm that sells its benchmark to buy its own ideas has stopped measuring itself.
Sector limits apply on a look-through basis. A portfolio can hold no technology stocks and still be at a technology ceiling, and a framework that only counted direct holdings would not notice.
| Exposure | Ceiling | Type | Basis |
|---|---|---|---|
| Any one GICS sector, incl. ETF look-through | 20% | Hard | Look-through weights from published fund holdings |
| Any one GICS industry group | 12% | Soft | Single names only |
| Any one country outside the US | 25% | Soft | Domicile of primary listing |
| Unhedged non-USD revenue exposure | 30% | Soft | Reported revenue mix, not listing venue |
| Top five positions combined | 35% | Soft | Excludes BIL |
| Any one theme with a shared driver | 25% | Soft | Declared in the note; e.g. AI capex, China consumer |
Two consequences follow directly. First, the book sits at its technology ceiling before a single technology stock has been researched — which is the quantitative justification for XLK sitting second in the recycle queue. Second, no researched technology name may be added until XLK is recycled. Neither of those is a judgement call made at the time; both fall out of the measurement.
| Metric | Current | Target band | Ceiling | Type |
|---|---|---|---|---|
| Annualised portfolio volatility | 9.5% | 8–12% | 14% | Hard |
| Equity share of total risk | ~86% | 80–90% | 92% | Soft |
| Beta to SPY | ~0.6 | 0.5–0.9 | 1.0 | Soft |
| Effective number of bets | — | ≥ 5 | ≥ 4 floor | Soft |
| Net exposure | 100% | 100% | 100% | Hard |
The volatility ceiling will bind before the capital limits do. Replacing ETFs at 15–24% volatility with single names at 25–40% raises book volatility even after diversification across ten to fourteen names. A reasonable expectation for a fully deployed researched book is 11–13% against a 14% ceiling. If the projected figure exceeds 14%, the response is to hold fewer, lower-volatility names, or to run the researched sleeve below its 50% target — not to raise the ceiling. This is modelled in the workbook before deployment begins, not discovered after it.
A name must clear all of the following before it can be sized at all: 250 trading days of price history Hard; $2bn minimum market capitalisation Soft; $10m median daily traded value over 60 days Soft; and a position no greater than 1% of median daily volume Soft. Non-US businesses are held via ADR or US listing. At a $6,000 maximum position the volume constraint is non-binding for any name meeting the others, and is stated so that it scales with the book rather than needing to be invented later.
An ETF is exposure you rebalance. A single stock is a bet you exit at a target.
ETF sleeves — including the equity sleeves — are broad exposure vehicles and are managed back to target weight. They are never "taken profit on": selling SPY because the market has risen is market timing wearing a risk-management costume. Individual company positions are bought against a fair-value target derived from a published thesis, and therefore have a defined exit. Applying take-profit logic to ETFs, or rebalancing logic to a single name whose thesis has broken, are the two symmetrical errors this rule exists to prevent.
| Trigger | Threshold | Action |
|---|---|---|
| Absolute drift from target | ± 3.0 pp | Rebalance the line to target at the next monthly review |
| Relative drift from target | ± 25% | As above — whichever trigger fires first, for small target weights |
| Sleeve-level drift | ± 4.0 pp | Rebalance within the sleeve before rebalancing across |
| Floor or ceiling breach | any | Per breach policy below |
| Calendar | quarterly | Full rebalance to target regardless of drift |
These rules become operative on the first researched fill. As at the issue date the book is 100% ETFs, so no take-profit rule is currently live.
| Exit type | Trigger | Action |
|---|---|---|
| Target reached | Price meets the published 12-month target | Re-underwrite or exit — never drift. Holding past a target without re-underwriting converts a researched position into an unresearched one. |
| Thesis stop | A published falsifier occurs | Exit within five trading days. Publish a note explaining what was wrong. |
| Risk review | Position −25% from cost | Mandatory written review, not an automatic exit. A price stop on a fundamental thesis would systematically sell exactly the mispricing the thesis predicted. |
| Drift trim | Position exceeds 7.5% of NAV at market | Trim back to 6.0% at the next review. |
| Time stop | 18 months with no measurable thesis progress | Exit or re-underwrite. Capital and, more importantly, coverage capacity are finite. |
| Coverage loss | The analyst can no longer maintain the name to standard | Exit. An unmaintained published position is worse than no position. |
Measured on NAV from the prior peak, using the same equity curve published on the website.
| Level | Response | Detail |
|---|---|---|
| −5% | Note | Recorded and commented on in the monthly risk note. No action. |
| −8% | Written risk review | Full attribution: what lost the money, whether it was the theses or the beta, whether any limit is implicated. Published. |
| −12% | Mandatory de-risk | Restore defensive floors to target. No new single-name positions until the review is complete. |
| −15% | Halt and re-underwrite | All new positions halted. Every open thesis re-underwritten from scratch and the outcome published. The framework is reviewed — but may only be tightened, never loosened, while in drawdown. |
| Breach type | Definition | Required action |
|---|---|---|
| Active | Caused by a trade the firm placed | Must not occur. If it does: unwind to compliance same session, log it, and disclose it in the next published risk note. |
| Passive | Caused by market movement, or by a new limit applying to a pre-existing position | Correct at the next monthly review, or sooner if the excess exceeds 1.5× the limit. No forced intra-month trading. |
| Soft | Any limit tagged Soft | Written explanation in the monthly review. May be carried deliberately if the reason is stated and dated. |
| Daily | Confirm the feed is live and NAV is plausible. No trading decisions are made daily. |
|---|---|
| Weekly | Drift check against the rebalance bands; research pipeline stand-up. |
| Monthly | Full covariance recompute with shrinkage; risk-parity refresh; risk-contribution check against the risk cap; rebalance if outside band; publish the risk snapshot; review the breach log. |
| Quarterly | Full rebalance; thesis-status review of every open name; performance attribution against SPY; review of this framework. |
| Event-driven | Earnings for any held name; any published falsifier; any drawdown level. |
Net asset value and indexed equity curve; open positions with weight, entry and return; net, gross, long and short exposure; largest position; top sector weight; maximum drawdown; cash weight; recent trade activity. These populate from the paper account and are recomputed daily.
Estimated portfolio volatility; risk contribution by position and by sleeve; correlation matrix; effective number of bets; benchmark-relative return with a plain-language attribution; and any breach together with its resolution.
| Benchmark-relative underperformance is reported in the same place, and with the same prominence, as outperformance | 1 |
| The paper-account caveat appears wherever a return is quoted, without exception | 2 |
| Estimates are labelled as estimates, with the sample window stated | 3 |
| Failed theses get a published post-mortem, not silent removal from the site | 4 |
| Methodological limitations are disclosed in the document that relies on them | 5 |
| No metric is published that cannot be reconstructed from a stated source and a stated method | 6 |
The framework is reviewed quarterly. Review is a scheduled task, not a discretionary one: an unreviewed manual past its review date is treated as a soft breach and disclosed in the next risk note. Any amendment that loosens a limit, widens the universe, or changes the mandate requires written agreement and a version increment. Any amendment that tightens a limit may be made unilaterally by the risk owner and ratified at the next review.
A limit is not a target and it is not a suggestion. If a limit is inconvenient, the correct response is to amend it deliberately at a review, in writing, before the trade — never to exceed it and document the exception afterwards. The credibility of published research rests entirely on the claim that the sizing framework was applied as written.
Alvermont Research publishes independent research for educational and informational purposes only. Nothing in this document constitutes financial, investment, legal or tax advice, nor a recommendation or solicitation to buy or sell any security. The portfolio described is a paper account and does not represent real capital or actual trading. Volatility, correlation, return, risk-contribution, beta and Sharpe figures are estimates computed from historical daily data over a finite sample and will differ from future realised values. Sector look-through figures are estimates based on typical index composition rather than current fund fact sheets. Past performance, whether actual or hypothetical, is not indicative of future results. © 2026 Alvermont Research.