What Recent Returns Don't Tell You: The Case for Risk-Adjusted Thinking

Your friend tells you about a PMS that returned 45% last year. Your current PMS returned 22%. The difference is ₹23 lakhs on a ₹1 crore portfolio. Your immediate impulse is to switch. But before you do, there is a critical question you need to ask: How much risk did that 45% return require?

This is the fundamental problem with how most investors evaluate returns. They look at the number and assume higher is always better. But a 45% return achieved with 60% drawdown potential is not the same as a 22% return achieved with 15% drawdown potential. The first is speculation masquerading as investing. The second is intelligent wealth creation.

Risk-adjusted returns measure how much return you achieved per unit of risk taken. It's the difference between asking "how much did you make?" and asking "how much did you make for every rupee of volatility you endured?" The second question is far more important, and yet it's the one that most investors never ask.

The Problem With Chasing Headline Returns

Consider a real historical example. In 2020, Indian markets experienced a dramatic V-shaped recovery. Some aggressive mid-cap and small-cap funds returned 60-80% that year. Meanwhile, conservative large-cap funds returned 15-25%. The marketing materials from those high-returning funds screamed about the performance gap. Investors saw the numbers and wanted in.

But what they didn't see in the marketing was that those high returns came from taking massive concentration bets on 2-3 stocks. When 2022 arrived and growth stocks corrected sharply, those same funds fell by 40-50%. Investors who chased the 2020 returns experienced catastrophic losses in 2022. The conservative funds that had returned 15-25% in 2020 dropped only 12-15% in 2022. Over the two-year period, the "boring" conservative approach significantly outperformed.

What is Risk-Adjusted Return?

Risk-adjusted return is a framework for evaluating investment performance that accounts for the volatility and drawdown risk taken to achieve those returns. Instead of just looking at absolute returns, it asks: "Per unit of risk, how much return did you generate?"

Imagine two portfolios:

• Portfolio A: Returned 24% with a maximum drawdown of 18% and annual volatility of 14%
• Portfolio B: Returned 24% with a maximum drawdown of 45% and annual volatility of 32%

Both returned exactly 24%. But Portfolio A did it with far less risk. Portfolio A is the better investment. Risk-adjusted metrics quantify this intuition numerically.

Key Metrics Explained

Sharpe Ratio

The Sharpe Ratio measures excess return per unit of volatility. Formula: (Portfolio Return - Risk-Free Rate) / Portfolio Volatility.

If your PMS returned 18% with 12% annual volatility and the risk-free rate is 6%, your Sharpe Ratio is (18% - 6%) / 12% = 1.0. A Sharpe Ratio above 1.0 is good. Above 1.5 is excellent. Below 0.5 suggests you're taking too much risk for the return.

The Sharpe Ratio is useful but has a flaw: it treats upside volatility the same as downside volatility. It penalizes you for having great months just as much as terrible months.

Sortino Ratio

The Sortino Ratio is like the Sharpe Ratio's smarter cousin. It only penalizes downside volatility (the bad kind), not upside volatility (the good kind). Formula: (Portfolio Return - Risk-Free Rate) / Downside Volatility.

A PMS with a Sortino Ratio of 1.5 means for every 1% of downside volatility, you earned 1.5% of excess return. This is a more investor-friendly metric because it recognizes that not all volatility is bad. Doubling your money in a great month is volatility, but it's the kind you want.

Information Ratio

The Information Ratio measures how much excess return you earn per unit of tracking error (deviation from your benchmark). Formula: (Portfolio Return - Benchmark Return) / Tracking Error.

If your PMS returned 20%, the Nifty 50 returned 16%, and your tracking error is 8%, your Information Ratio is (20% - 16%) / 8% = 0.5. An Information Ratio above 0.5 is good for active management. Above 1.0 is exceptional.

This metric is particularly useful for PMS evaluation because it answers: "Beyond just beating the index, how efficiently are you beating it? Are you taking large bets to generate small outperformance, or small bets to generate large outperformance?"

Maximum Drawdown

Maximum drawdown is the largest peak-to-trough decline experienced by the portfolio. If your portfolio reached ₹1.5 crores at its peak and subsequently fell to ₹1.2 crores, the maximum drawdown is 20%.

This metric is psychologically important. It tells you the worst-case scenario you would have faced in the past. If you can't tolerate a 25% drawdown psychologically, a strategy with a 35% maximum drawdown is not suitable for you, regardless of its returns.

Calmar Ratio

The Calmar Ratio divides annual return by maximum drawdown. Formula: Annual Return / Maximum Drawdown.

If a PMS returned 20% annually and had a maximum drawdown of 25%, its Calmar Ratio is 20% / 25% = 0.8. A Calmar Ratio above 1.0 means you're earning more than 1% of return for every 1% of drawdown risk — which is excellent. Below 0.5 suggests the drawdown risk is not adequately compensated by returns.

Comparison Table: Understanding These Metrics

Real-World Examples With Calculations

Scenario 1: The Aggressive Growth Fund

Fund A returned 32% last year. Your immediate reaction: "Wow!" But now you investigate further:

• Annual volatility: 28%
• Maximum drawdown: 42%
• Risk-free rate: 6%
• Sharpe Ratio: (32% - 6%) / 28% = 0.93
• Calmar Ratio: 32% / 42% = 0.76

The headline return looks impressive. But a Sharpe Ratio of 0.93 and Calmar Ratio of 0.76 suggest that the risk taken wasn't adequately compensated. You were taking substantial risk to earn that 32%.

Scenario 2: The Conservative Value Fund

Fund B returned 18% last year. Less impressive headline number. But:

• Annual volatility: 10%
• Maximum drawdown: 14%
• Risk-free rate: 6%
• Sharpe Ratio: (18% - 6%) / 10% = 1.2
• Calmar Ratio: 18% / 14% = 1.29

Fund B's Sharpe Ratio of 1.2 and Calmar Ratio of 1.29 tell a different story. You're earning excellent risk-adjusted returns. The 18% return came from intelligent risk management, not excessive leverage or concentration.

Over a full market cycle, Fund B will likely outperform Fund A because the risk it takes will be better compensated.

Why a 45% Return Might Be Worse Than 25%

Let's make this concrete. Consider two PMS portfolios over a 3-year period:

• PMS A: Year 1: +45%, Year 2: -35%, Year 3: +20%. CAGR: 8%
• PMS B: Year 1: +22%, Year 2: +18%, Year 3: +15%. CAGR: 18%

PMS A delivered a spectacular 45% return in year 1, but then gave back 35% in year 2. The average investor in PMS A watched their portfolio grow 45% and then shrink 35%. The emotional toll is significant. Many would have panic-sold in year 2, locking in losses.

PMS B delivered steady 15-22% returns. Less exciting, but far more predictable. An investor in PMS B would have slept well, knowing their portfolio was compounding steadily.

The CAGR tells the real story: PMS B (18% CAGR) dramatically outperformed PMS A (8% CAGR). The higher volatility in PMS A actually reduced long-term wealth creation because of the mathematical effect of drawdowns. A 35% loss requires a 54% gain to get back to even.

Types of Risk That Matter

Concentration Risk

A PMS that has 40% of its portfolio in 3 stocks is taking enormous concentration risk. If those 3 stocks underperform, the entire portfolio suffers. Many high-performing PMS funds are actually taking massive concentration bets. When the market rewards those specific bets, they deliver spectacular returns. When the market rotates, they crash.

Good risk-adjusted managers limit position sizes to 5-7% and ensure diversified exposure across sectors and market capitalizations.

Market Cap Risk

A PMS focused exclusively on small-cap stocks is taking market cap risk. Small-caps outperform in some periods and drastically underperform in others. A PMS that returned 50% in 2020 (a great small-cap year) might return -30% in 2022 (a terrible small-cap year).

Intelligent PMS managers maintain exposure across large-cap, mid-cap, and small-cap, adjusting the allocation based on valuation and risk. This reduces the risk of being in the wrong market cap at the wrong time.

Style Drift Risk

A manager might promise a "value investing" approach but slowly drift toward growth investing. Or vice versa. This style drift means the portfolio's behavior changes over time, and investors don't realize it until performance diverges sharply from expectations.

Good managers maintain consistency in their investment style and communicate clearly if they are making strategic shifts.

How to Evaluate a PMS Using Risk-Adjusted Metrics

When evaluating a PMS, follow this framework:

1. Look at 3-year and 5-year returns, not 1-year. One year is too short to judge anything.
2. Calculate the Sharpe Ratio. It should be above 1.0. Above 1.5 is excellent.
3. Check the maximum drawdown in different market environments. How did the portfolio perform in 2020? 2022? In 2008?
4. Calculate the Calmar Ratio. It should be above 1.0. This ensures the drawdown risk was adequately compensated.
5. Ask about concentration. If the top 5 positions represent more than 35% of the portfolio, dig deeper.
6. Assess style consistency. Has the manager's approach remained consistent, or have they shifted based on what's working?
7. Compare to a relevant benchmark. For a multi-cap PMS, the Nifty 50 is relevant. For a mid-cap focus, the Nifty Midcap 100 is more relevant.
8. Look at worst 12-month and worst 3-month periods. This gives you realistic psychological preparation.

Our Approach to Risk-Adjusted Analysis

When evaluating PMS managers for our clients, we run a comprehensive risk-adjusted analysis. We don't just look at returns. We examine:

• Rolling 3-year returns (how consistently did they outperform?)
• Sharpe and Sortino ratios across different time periods
• Maximum drawdown and recovery time in each major market correction
• Information Ratio (excess return per unit of tracking error)
• Concentration analysis and correlation between positions
• Sector and market-cap allocation drift
• Performance attribution (which decisions drove returns?)
• Worst month and worst quarter ever experienced

Only PMS managers who deliver strong risk-adjusted returns across multiple market cycles are recommended to our clients. A manager who returned 35% in 2021 but -25% in 2022 might have a great 5-year number that masks the underlying volatility and risk.

Conclusion: Return Quality Matters More Than Return Quantity

The next time you see a PMS headline return of 45%, don't be impressed by the number alone. Ask the harder questions: What risk was taken? What was the maximum drawdown? What was the Sharpe Ratio? How did it perform in down markets? Is this return sustainable, or is it a temporary spike that will reverse?

The difference between a ₹1 crore portfolio growing to ₹5 crores versus ₹3.5 crores over 20 years is primarily driven by consistency and risk management, not spectacular annual returns. A manager delivering 16% annually with a Sharpe Ratio of 1.2 will create more wealth than a manager delivering 22% annually with a Sharpe Ratio of 0.6.

Start thinking in terms of risk-adjusted returns. Your wealth creation depends on it.

"The real investment question is not "how much can I make?" but "how much can I afford to lose?" Risk-adjusted thinking means understanding your returns in context of that risk."

— Adapted from Howard Marks