Eight metrics are central to the UK Tax Drag ETF tools: Beta, Sharpe ratio, Sortino ratio, maximum drawdown, volatility (standard deviation), tracking error, information ratio, and up/down capture ratios. Each has a dedicated page with the full formula, the precise data inputs we use, the lookback window, the annualisation method, and a step-by-step worked example. Together they form the complete transparency layer — there is no metric used in our tools that isn't documented here.
The 8 metrics at a glance
| Metric | What it tells you | Typical lookback | Full transparency |
|---|---|---|---|
| Beta (β) | Sensitivity to broad-market moves | 3-year monthly returns | Beta page → |
| Sharpe ratio | Return per unit of total risk | 3-year monthly returns | Sharpe page → |
| Sortino ratio | Return per unit of downside risk | 3-year monthly returns | Sortino page → |
| Max drawdown | Worst peak-to-trough loss in the period | 5-year daily prices | Max drawdown page → |
| Volatility (σ) | Annualised standard deviation of returns | 3-year monthly returns | Volatility page → |
| Tracking error | How closely a passive ETF follows its index | 3-year monthly returns | Tracking error page → |
| Information ratio (IR) | Active return per unit of active risk | 3-year monthly returns | Information ratio page → |
| Up/down capture | Behaviour in rising vs falling markets | 3-year monthly returns | Capture ratios page → |
The standard inputs we use
Every metric calculation on UK Tax Drag uses the same standard inputs unless explicitly noted on a specific tool.
Price data
- Source: Issuer factsheets first, then exchange end-of-day closes from London Stock Exchange (LSE) and Xetra cross-checks.
- Currency: GBP — converted from issuer reporting currency at the close FX rate from Bank of England Daily Spot Rates.
- Adjustments: Total return basis (distributions reinvested at the ex-div date) unless a price-return version is explicitly labelled.
Benchmark data
- Equity benchmarks: MSCI ACWI for global, FTSE 100 for UK, S&P 500 for US, MSCI Emerging Markets for EM.
- Bond benchmarks: Bloomberg Global Aggregate (GBP-hedged) for global ballast, FTSE Actuaries UK Gilts All Stocks for , the fu.
- Custom benchmarks: for niche ETFs, the fund's stated benchmark is used; if proprietary, the closest mainstream index is used as a comparator (flagged on the relevant tool).
Risk-free rate
- Source: Bank of England 3-month ), 3-month, average over the lookback window.
- Currency: GBP. Where US risk-free is needed (Sharpe vs S&P 500 for example), 3-month US Treasury yield is used.
- Annualisation: Already annualised in BoE published series.
Return frequency
- Monthly returns are the default for ratio metrics (Sharpe, Sortino, Beta, Information Ratio) — 36 observations over a 3-year window.
- Daily returns are used for max drawdown and intraday-relevant metrics.
- Annualisation: Standard deviation annualised by √12 (monthly) or √252 (daily). Returns annualised geometrically: (1+r)n − 1.
The lookback question — why 3 years
Choice of lookback window materially affects every metric. We default to 3 years of monthly returns (36 data points) for these reasons:
- Statistical stability: 30+ observations is the rule-of-thumb minimum for normal-distribution assumptions to behave reasonably. 36 monthly returns clears this comfortably.
- Reflects current regime: 3 years captures the most recent business cycle without being overwhelmed by 2008-style outliers.
- Industry standard: Morningstar, Bloomberg, and the major factsheet providers all default to 3-year for the same reason.
Some tools optionally show 5-year and 10-year windows. The 3-year is the default and the one shown on summary cards.
How to reproduce any metric yourself
Each per-metric page includes a "how to reproduce this yourself" section. The general workflow:
- Get the price series. Download monthly closes for 36+ months from the issuer page, the LSE website, or via Yahoo Finance / Stooq for the ticker.
- Calculate monthly returns. Returnt = (Pricet − Pricet-1) / Pricet-1. Spreadsheet column.
- Apply the formula from the relevant per-metric page.
- Annualise where needed. The per-metric pages specify exactly which factor.
- Cross-check against issuer factsheet — most ETFs publish their own metrics. Numbers should be within ~5% of each other (small differences from different price sources / FX conversions are normal).
Data freshness commitments
- Daily price data: refreshed daily from issuer + exchange feeds.
- Monthly metric recalculations: all ratio metrics recalculated monthly, by the 10th of each month for the prior month's data.
- Quarterly factsheet cross-checks: we manually cross-check our calculated values against issuer factsheets quarterly. Discrepancies > 5% are investigated and resolved.
- Annual benchmark review: the benchmark used for each ETF is reviewed annually. Any benchmark change is logged in the methodology log.
The professional caveats
Even with full transparency, every metric has limitations. The per-metric pages document these in detail. The headline cautions:
- No metric is a quality score. Beta, Sharpe, Sortino — none of these tell you if an ETF is "good." They describe past behaviour.
- Past performance doesn't predict future performance. Even with 3 years of monthly data, the period may not represent future return distributions.
- Different metrics measure different things. An ETF can have a great Sharpe and a terrible max drawdown if the period was mostly calm but had one big crash. Read multiple metrics together.
- Bond and equity metrics aren't comparable. A bond ETF with Sharpe 1.2 isn't "better" than an equity ETF with Sharpe 0.8 — they're doing different jobs.
Sources and methodology
Risk-free rate from Bank of England daily yields. Benchmark data from index providers (MSCI, FTSE Russell, Bloomberg, S&P Dow Jones, ICE). Price data from issuer factsheets cross-checked with LSE end-of-day closes. The ETF Data Methodology documents data sources in full. The site methodology documents the broader review process.
The 8 per-metric deep dives
- Beta (β) — formula, UK benchmark choice, regression mechanics
- Sharpe ratio — formula, UK risk-free rate, limitations
- Sortino ratio — downside deviation, MAR target
- Maximum drawdown — peak-to-trough mechanics
- Volatility / standard deviation — annualisation
- Tracking error — ex-post vs ex-ante
- Information ratio + alpha
- Up/down capture ratios — asymmetric performance
How UK Tax Drag holds itself to account
Every page is reviewed against the editorial standards, written from primary sources, sourced openly, and corrected publicly. No affiliate revenue. No sponsored content. No paid placements.