Measure
Tracking error
The annualised volatility of a fund's return difference from its benchmark. Formula: TE = σ( r_fund − r_benchmark ) × √(periods per year).
Definition
The annualised volatility of a fund's return difference from its benchmark.
Formula
TE = σ( r_fund − r_benchmark ) × √(periods per year)
How to read it
For an index fund, low is the goal; for an active one, it measures how much it dares differ.
What it does not tell you
Low tracking error is only a virtue against the right benchmark. A fund can track a poorly chosen index perfectly, and the figure says nothing about whether that index deserves the money.
Applied in 51 articles
51- Factor Crowding and Alpha Decay: What Happens to a Premium After Everyone Reads the Paper
- The Real Cost of Tail-Risk Hedging: Put Options vs Cash vs Trend Following
- Direct Indexing vs ETFs: When Owning the Stocks Beats Owning the Fund for Tax-Loss Harvesting
- IJR vs IWM vs VB: Three Small-Cap Blend ETFs and Why Their Indexes Diverge
- VO vs IJH: The Overlooked Mid-Cap Allocation — Does It Add Anything to VOO?
- DGRO vs SCHD: Two Dividend-Growth Approaches — Breadth vs Concentration
- VGT vs XLK: Two Large Technology ETFs — Where the 0.10% Fee Gap Goes
- AVUV vs VBR: Small-Cap Value — Active Selection vs the Index Approach
- IBIT vs FBTC: Comparing the Two Largest Spot Bitcoin ETFs — Fees, Spreads, and What You Actually Own
- SMH vs SOXX: Two Semiconductor ETFs, Two Very Different Concentration Profiles
- VOO vs VTI: S&P 500 vs Total US Market — What the Difference Actually Costs Over Decades
- What 'AI in Investing' Actually Means in 2026 (Without the Marketing)
- Why Tracking Error Matters More Than Expense Ratio in 2026
- AMOM Explained: How AI Weights Momentum Differently from MTUM
- The Ultimate 2026 Hybrid Portfolio: How to Mix Classic ETFs with AI Quant
- GLD vs. DBMF: Gold vs. AI-Managed Managed Futures (Trend Following)
- QQQM vs. QRFT: Nasdaq 100 vs. AI-Driven Quality Factor Investing
- VOO vs. AMOM: Can AI Momentum Outperform the S&P 500? (2026 Analysis)
- The "All-Weather" AI Portfolio: Combining Diversification with Predictive Power
- Best AI-Managed ETFs for 2026: A Deep Dive into AIEQ and AMOM
- VOO vs. MTUM vs. QUAL: Which Smart Beta ETF Wins Based on Historical Backtests?
- The Master Guide to Evidence-Based ETF Portfolios: Using AI to Optimize Allocation (2026)
- Why "Factor Investing" Still Works: Applying Fama-French Models in the AI Era
- Top 5 Quantitative Investment Papers Every Long-Term Investor Must Read
- The Great Rotation Playbook: Full ETF Strategy for 2026
- Repositioning Without Prediction: A 2026 Rotation Framework for Long-Term ETF Portfolios
- SGOV vs Gold ETFs: Two Defenses That Hedge Different Risks
- XLE vs VDE: Which Energy ETF Benefits Most from Oil Shocks?
- The Rationale Behind a Five-ETF Long-Term Core: VOO, QQQM, SCHD, VXUS, AVUV
- The Final-Decade Asymmetry: How Long-Horizon ETF Compounding Actually Distributes
- Compounding Realistically: What 30 Years of Index Investing Actually Looks Like
- The 0.1% Allocation Question: What Small Decisions Actually Change Over 30 Years
- QLD vs SSO: What 2x Leveraged ETFs Actually Cost a Long-Term Holder
- The Impact of 2026 Energy Policies on Your Long-Term Portfolio
- Data Center REITs vs. Infrastructure ETFs: Which One for Consistent Cash Flow?
- The 90/10 Allocation Framework: Pairing Broad Equity, AI Infrastructure, and a Cash Sleeve
- Infrastructure ETFs in 2026: What XLU, VPU, IFRA, PAVE, and GRID Actually Own
- BOTZ vs IRBO: Finding the Most Cost-Effective Entry into Automation
- Sizing an AI-Infrastructure Sleeve: VOO, QQQM, XLU, IFRA, and SGOV Through a Long-Horizon Lens
- SCHD vs VOO: What the Data Actually Says About Dividend Yield and Total Return
- Buy and Hold in 2026: What Rebalancing Discipline Actually Adds to Long-Term ETF Returns
- Tax-Loss Harvesting and the After-Tax Compounding Gap: What the Math Actually Shows
- Beyond a One-ETF Equity Core: What AVUV and VXUS Actually Add to VOO
- VOO, QQQM and SCHD: One Behaves Like 52 Holdings, the Other Two Like 32 Each
- SCHD, AVUV, and VXUS During the Iran–U.S. War Shock Dividend Stability, Small-Cap Risk, and Global Exposure — A Data-Driven ETF Analysis
- SGOV, VOO, and QQQM Under Geopolitical Stress: What Oil, Yields, and Volatility Reveal
- Tesla Inside Your Index ETF: How Market-Cap Weighting Translates a Single Stock Into Portfolio Exposure
- The Tesla Ecosystem Through an ETF Lens: How Long-Horizon Investors Should Think About Concentrated Innovation Bets
- KOSPI 200 ETF Strategy: How It Fits in a Long-Term Global Portfolio
- AVUV and the Case for Small-Cap Value Patience
- SCHD and the Power of Dividend Discipline
Every figure computed with this measure on this site follows the conventions set out in the methodology. All measures →