FlexShares Quality Competition
| QDF Etf | USD 79.19 -0.03 -0.04% |
Pair Correlation for FlexShares Quality and T Rowe Details
Very poor diversification
The correlation between FlexShares Quality and T Rowe is 0.84, which Macroaxis classifies as Very poor diversification for the selected horizon. Lower overlap tends to improve diversification, while higher overlap means both positions carry similar risk.
Moving together with FlexShares Etf
Experienced investors tracking FlexShares Quality's watch for mean reversion setups where price has deviated from its long-run average. Sentiment extremes, news events, or liquidity shocks are common catalysts for these temporary dislocations in FlexShares Quality. Prices periodically overshoot their intrinsic value in both directions, creating mean reversion opportunities in FlexShares Quality. The mean reversion signal is most useful when combined with fundamental confirmation for FlexShares Quality's.
FlexShares Quality Competition Correlation Matrix
Correlation analysis between FlexShares Quality Dividend and its competitors provides context for understanding whether diversification is real or only superficial inside the same peer group. The current classification points to the Large Value category. In practical terms, lower correlation may offer better diversification while higher correlation may leave the portfolio more exposed to one shared driver.
High positive correlations
| High negative correlations
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FlexShares Quality Constituents Risk-Adjusted Indicators
FlexShares Quality ETF can look attractive on recent price action while risk efficiency lags the peer group. Reviewing FlexShares Quality's risk-adjusted indicators gives a clearer view of whether returns are being earned efficiently. These indicators are quantitative in nature and help investors evaluate volatility and risk-adjusted expected returns across different positions.| Mean Deviation | Jensen Alpha | Sortino Ratio | Treynor Ratio | Semi Deviation | Expected Shortfall | Potential Upside | Value @Risk | Maximum Drawdown | ||
|---|---|---|---|---|---|---|---|---|---|---|
| TILT | 0.59 | 0.03 | 0.00 | -0.03 | 0.00 | 0.88 | 3.85 | |||
| QGRO | 0.84 | -0.03 | 0.00 | -0.09 | 0.00 | 1.28 | 4.73 | |||
| EWG | 0.86 | -0.04 | 0.00 | -0.11 | 0.00 | 1.61 | 5.57 | |||
| FUTY | 0.75 | 0.10 | 0.13 | 0.39 | 1.08 | 1.45 | 6.70 | |||
| FDIS | 0.83 | -0.08 | 0.00 | -0.14 | 0.00 | 1.81 | 4.40 | |||
| EWW | 1.24 | 0.18 | 0.09 | 0.10 | 1.84 | 2.28 | 9.56 | |||
| ESML | 0.81 | 0.10 | 0.09 | 0.03 | 1.04 | 1.57 | 5.23 | |||
| FTLS | 0.42 | 0.02 | 0.10 | -0.02 | 0.56 | 0.83 | 2.48 | |||
| DES | 0.81 | 0.14 | 0.13 | 0.07 | 0.91 | 2.01 | 5.63 | |||
| TSPA | 0.62 | 0.02 | 0.00 | -0.04 | 0.00 | 1.07 | 3.72 |
FlexShares Quality Competitive Analysis
| Better Than Average | Worse Than Peers | View Performance Chart |
FlexShares Quality Competition Peer Performance Charts
How to Analyze FlexShares Quality Against Peers
FlexShares Quality's peer analysis compares FlexShares Quality with related companies to put valuation, quality, and risk metrics in context. This helps determine whether recent performance is company-specific or broadly sector-driven. A practical workflow includes:- Set a relevant peer group: Include direct competitors and close alternatives with comparable business exposure.
- Benchmark core financials: Compare profitability, growth, capital structure, and cash flow quality.
- Check valuation dispersion: Review whether FlexShares Quality trades at a premium or discount versus peers and why.
- Evaluate risk profile: Compare volatility, drawdowns, and correlation to avoid false diversification assumptions.
- Document the thesis: Record where FlexShares Quality leads or lags and what catalysts could close or widen the gap.
Peer Comparison Metrics & Methodology
FlexShares Quality carries less net debt relative to EBITDA than most competitors, giving it more room to invest or weather downturns. Peer benchmarking can improve context for valuation without relying only on standalone multiples.
The analytics block for FlexShares Quality Dividend relies on fund disclosures and market reference feeds, with quality checks and normalization applied before rendering. Timing can vary by data vendor.