NISM Professor

Smart beta

Index-based investing that deviates from traditional market-cap weighting to emphasise factor exposure such as value, momentum, quality or low volatility. Sits between active and passive.

In plain language

A normal index fund buys stocks based on their market capitalisation, which is their total market value. The biggest company gets the biggest weight, whatever its qualities.

Smart beta keeps the fixed, index-like rules. But it changes how stocks are picked and weighted.

In the workbook's terms, smart beta is index-based investing that moves away from market-cap weighting to focus on factors. A factor is a trait that stocks share, such as value.

Chapter 6 says factor funds are "also known as smart beta funds". They follow number-based factors such as value, momentum and volatility. Maths rules decide which stocks to buy and how much of each.

That puts smart beta between active and passive investing. The fixed rules make it look passive. But it re-picks stocks often, in a set way, and that makes it look active.

How it works

Factors (Chapter 9, section 9.4.4). Factors are broad, systematic drivers of risk and return.

  • Macroeconomic factors affect all asset classes: inflation, economic growth, interest rates, liquidity.
  • Style factors influence individual securities:
FactorWorkbook description
ValueUndervalued relative to fundamentals (low P/E or P/B) tend to outperform over time
MomentumStrong past performers tend to continue upward in the short term
SizeSmaller companies tend to outperform large caps over the long run
QualityStrong profitability, low debt, stable earnings growth; resilient in downturns
Low volatilityLower price fluctuations; historically better risk-adjusted returns

Ways to build factor exposure. Single-factor investing (e.g., only low-volatility stocks); multi-factor investing (e.g., quality + momentum + value); and smart beta strategies.

Factor funds by type (Chapter 6). Momentum funds rebalance periodically to adapt to sector shifts and are described as particularly effective in bull markets; low volatility funds are robust in downturns; value funds perform well in recovery phases and bull markets; quality funds perform well in bear markets.

Benefits. Enhanced risk-adjusted returns; diversification because different factors work in different cycles; a rules-based approach that removes emotional bias; and cost-effectiveness — smart beta ETFs and factor funds offer active-like returns at lower fees.

Challenges. Factor cyclicality (not all factors work at all times; some underperform for extended periods), data and implementation complexity, and overcrowding in popular factors.

Benchmarking (Chapter 10, section 10.4.2). Market-based indices may not suit factor-based strategies, which can call for a customised benchmark.

A worked example

Illustrative stocks and weights — built to show how smart beta re-weights an index. The workbook gives no worked example.

A three-stock universe:

StockMarket capMarket-cap weight1-year price volatilityLow-volatility weight (illustrative rule)
A₹6,00,000 crore60%High20%
B₹3,00,000 crore30%Medium30%
C₹1,00,000 crore10%Low50%

A traditional index fund of ₹10,00,000 buys ₹6,00,000 of A, ₹3,00,000 of B and ₹1,00,000 of C — size alone decides.

A low-volatility smart beta fund following a rule that tilts towards steadier stocks buys ₹2,00,000 of A, ₹3,00,000 of B and ₹5,00,000 of C. The rule is fixed and mechanical — no fund manager judgement on each stock — but the result is a portfolio that looks nothing like the market-cap index.

If markets fall sharply, the workbook's description suggests the low-volatility tilt should be more robust. If a strong bull market is led by A, it may lag — an example of factor cyclicality. And comparing it with a plain market-cap index may not be a fair test, which is why a customised benchmark can be needed.

Why NISM asks about it

Smart beta appears in Chapter 6 (Collective Investment Vehicles), where factor funds are "also known as smart beta funds", and in Chapter 9 (Portfolio Management Process), section 9.4.4 on factor-based investing, among the ways a portfolio manager decides asset allocation. Chapter 10 (Performance Measurement and Evaluation) names factor-based investing as a case where a customised benchmark may be needed. Expect questions on where smart beta sits between active and passive, and on factor cyclicality.

Common exam traps

  • Smart beta is not market-cap weighting. That departure is its definition.
  • It is rules-based but not purely passive — the workbook places factor funds between active and passive.
  • Factors don't work all the time. Factor cyclicality can mean extended underperformance.
  • Overcrowding can reduce a popular factor's effectiveness.
  • Momentum = continuation of past performance; value = cheapness relative to fundamentals. Don't swap them.
  • "Active-like returns at lower fees" is the workbook's cost claim, not a guarantee of outperformance.

Check yourself

  1. 1.Where does the workbook place factor (smart beta) funds?

    1. a)Purely active funds
    2. b)Purely passive funds
    3. c)Between active and passive funds
    4. d)A type of AIF
    Show the answer

    Answer: (c) Between active and passive funds

    Factor funds "fall between Active and Passive funds". The rule-based approach mimics passive investing, while frequent systematic selection of stocks mimics active investing.

    They are described under mutual funds, not AIFs.

Where this is taught

Free preparation for NISM Series XXI-B

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