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Traderoid

TreynorRatio Node

Excess return per unit of systematic risk

StatisticalPerformanceRisk

Overview

Treynor Ratio measures excess return earned per unit of systematic risk (Beta), not total risk. It's superior to Sharpe Ratio for diversified portfolios where diversifiable risk is eliminated. Treynor > 0.1 is good; Treynor > 0.2 is excellent. It directly answers: "How much excess return per unit of market risk?"

Distinct from Sharpe (which penalizes all volatility), Treynor only penalizes non-diversifiable (systematic) risk. A leveraged but undiversified strategy has high Treynor but risky. A well-diversified strategy with low Beta has lower Treynor but may be superior risk-adjusted.

Formula & Calculation

Treynor Ratio
Treynor = (Return - Risk_Free) / Beta
Excess return / Systematic risk
Beta measures sensitivity to market moves
Comparison to Sharpe
Sharpe = Excess Return / Total Risk
Treynor = Excess Return / Systematic Risk
Use Treynor for diversified portfolios
Use Sharpe for concentrated bets

Parameters

ParameterDefaultDescription
period252Annualization standard
benchmarkSPYMarket proxy for Beta

Common Use Cases

1. Manager Evaluation

Compare diversified portfolio managers: Treynor filters out idiosyncratic risk (luck/skill). High Treynor = true systematic skill.

2. Factor Evaluation

Assess factor premia: If factor Beta is 0.5 and returns 8%, Treynor = 8%/0.5 = 16%. Indicates strong factor premium.

3. Risk-Efficient Ranking

Rank strategies by Treynor: Highest Treynor gets allocated capital. Diversify across high-Treynor strategies for best sharp risk-adjusted returns.

4. Hedge Ratio Optimization

Hedge to maximize portfolio Treynor. If strategy has high Treynor but high Beta, hedge 50% of Beta to improve risk-adjusted returns.

Advantages & Limitations

Advantages

  • Focuses on systematic risk
  • Best for diversified portfolios
  • Penalizes only non-diversifiable
  • Industry standard metric
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Limitations

  • Beta estimation unstable
  • Past Beta ≠ future Beta
  • Assumes CAPM validity
  • Benchmark dependent

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