Your momentum strategy returned 32% last year. Was that good? It depends entirely on what the benchmark returned, how much risk you took, and whether the performance was driven by your factor signal or just by the market going up.
Performance measurement is the process of answering those questions honestly. It's harder than it sounds | the financial industry has a long history of making performance look better than it is, through selective benchmarks, cherry-picked time periods, and gross-of-cost returns. This module teaches you to cut through that and evaluate performance clearly.
The right benchmark
Every return number is meaningless without a benchmark. The benchmark should represent: what would you have earned if you hadn't run this strategy?
For systematic factor strategies on Nifty 500, the correct benchmark is the Nifty 500 TRI (Total Return Index) | not the Nifty 50, not the price index. Reasons:
- TRI vs Price Index: The price index ignores dividends. The TRI includes dividends reinvested. For a fair comparison, your strategy's returns should also include dividends | and so should the benchmark. Using the TRI as benchmark prevents a spurious "alpha" from simply holding dividend-paying stocks.
- Nifty 500 not Nifty 50: Your strategy selects from Nifty 500, which includes mid and small-cap stocks that systematically outperform large-caps over long periods. Comparing a Nifty 500 factor strategy to the Nifty 50 would show artificial alpha | you'd be taking more risk (mid-cap exposure) and comparing to a lower-risk benchmark.
The five performance metrics you need
How long before you can evaluate a strategy?
This is the most important | and most ignored | question in performance evaluation. Short-period returns are dominated by luck, not skill.
| Evaluation period | Confidence in results | Why |
|---|---|---|
| 1 month | Near zero | Monthly returns are almost pure noise. Even random strategies show 1-month "alpha." |
| 1 year | Very low | 1-year results are dominated by market regime. Anything can look good or bad in 12 months. |
| 3 years | Moderate | Starts to show consistent patterns, but still doesn't cover a full market cycle. |
| 5 years | Meaningful | Covers at least one significant correction. Results start to be statistically significant. |
| 10+ years | High | Covers multiple market cycles. Alpha this persistent is likely real, not luck. |
The practical implication: Do not change your strategy because of 6-month or 12-month underperformance. The expected win rate for most factor strategies is 55 to 65% of months | meaning you should expect to underperform the benchmark in 35 to 45% of all months. A 6-month stretch of underperformance is completely within normal expectations. Evaluating performance and making strategy decisions only at 3 to 5 year intervals is not laziness | it's statistical discipline.
In 2019 I sat in a PMS review meeting in Mumbai where the fund manager showed a 17 percent CAGR over 3 years and everyone applauded. I asked one question. What was Nifty 500 TRI over the same period. Nobody had checked. It was 14.5 percent. So 2.5 percent of gross alpha, minus 2.5 percent expense ratio, minus taxes. A zero alpha fund dressed up as a star performer. Since then I carry one rule. Before I congratulate any strategy, I pull up Nifty 500 TRI for the exact same window, net of every cost. If it does not beat the index after fees, it is not a strategy. It is a story.
Every strategy on RupeeCase shows a rolling 12-month and rolling 36-month alpha chart, monthly win rate vs benchmark, information ratio, and the full performance attribution (how much return came from factor exposure vs stock selection vs market beta). The benchmark is always the Nifty 500 TRI. Net-of-cost returns throughout. Available at invest.rupeecase.com.
Glossary
- Nifty 500 TRI
- The Total Return Index version of Nifty 500 | includes dividends reinvested. The correct benchmark for any strategy selecting from the Nifty 500 universe.
- Information Ratio
- Annualised excess return divided by tracking error. Measures consistency of alpha generation. Above 0.5 is good; above 0.8 is excellent.
- Tracking error
- The standard deviation of the difference between strategy returns and benchmark returns. High tracking error means performance diverges significantly from the benchmark in any given period.
- Rolling alpha
- Alpha calculated over a rolling window (e.g., 36 months), computed at each monthly interval. Shows whether alpha was persistent or concentrated in specific periods.
- Win rate
- The fraction of periods (months or years) in which the strategy outperformed the benchmark. Good systematic strategies typically win 55 to 65% of months.
Sources & further reading
- → NSE Indices — Nifty 500 TRI (benchmark data)
- → SEBI — Performance Benchmarking Guidelines
- → Grinold, R. & Kahn, R. (2000). Active Portfolio Management. McGraw-Hill. (Information Ratio and performance measurement)
- → Sharpe, W.F. (1994). The Sharpe Ratio. Journal of Portfolio Management.
Quick check, Module 4.4
CAGR Calculator
The single annualised number that matches the actual compounding outcome over a multi-year holding.