7.2 Security Market Indexes and Efficiency

What an index measures

A security market index is a notional portfolio built to represent a market or segment. It can track large-cap, small-cap, a country, a sector, a style, a factor, or a custom strategy. Five uses recur on the exam: a benchmark for active managers, a measure of market sentiment, a basis for performance attribution, a proxy for an asset class in studies of risk and return, and a model portfolio for index funds and exchange-traded funds (ETFs) and their derivatives.

Four construction decisions define every index. (1) The target market — what is represented. (2) Selection rules — which securities qualify (size, liquidity, domicile). (3) The weighting method. (4) Maintenance — how the index responds when prices move, shares change, mergers occur, or constituents enter and leave.

Weighting methods and arithmetic

A price-weighted index sums constituent prices and divides by a divisor; a high-priced stock dominates regardless of company size. After a 2-for-1 split, the divisor is reset so the index level is unchanged — a classic exam calculation. An equal-weighted index assigns each constituent the same weight at each rebalance; it tilts toward smaller firms and needs frequent rebalancing because prices push weights away from equality. A market-cap (value-weighted) index weights by market value; a float-adjusted version counts only freely tradable shares, excluding founder, government, or strategic blocks.

Worked example: three stocks priced 100, 50, 10 with a divisor of 3 give a price-weighted level of 53.3; the same stocks with market caps of 5B, 20B, 30B make the 30B name the largest cap weight even though it has the lowest price — showing why the weighting scheme must be identified before any arithmetic.

Return measurement and maintenance

A price-return index captures only price change; a total-return index assumes dividends or interest are reinvested. For equities the gap compounds materially over a decade. Rebalancing resets weights to the target method; reconstitution changes the membership list. A style index may rebalance quarterly and reconstitute annually, creating turnover, trading costs, and predictable index-effect price pressure that trackers must manage.

Uses, limitations, and free float

Indexes are convenient but not neutral. A benchmark can be too broad, too narrow, or mismatched to a mandate. Survivorship bias inflates historical returns when failed or delisted firms are dropped from a back-tested sample. Concentration risk makes a cap-weighted index lean on a few mega-caps. Free-float adjustment matters because shares held by founders, governments, or strategic owners are not investable; a total-shares index overstates the opportunity set ordinary investors can actually hold.

Market efficiency

An informationally efficient market reflects available information quickly and rationally enough that investors cannot consistently earn abnormal risk-adjusted returns after costs. Efficiency is a statement about competition and information, not a claim that price always equals intrinsic value. Weak-form efficiency means prices already reflect past prices and volume — if it holds, technical analysis cannot consistently beat the market net of costs.

Semi-strong-form efficiency means prices reflect all public information — if it holds, fundamental analysis of public filings cannot consistently add abnormal return; an event study of how fast prices adjust to news tests this form. Strong-form efficiency means prices reflect public and private information — the strictest and least realistic form, generally rejected because insider trading earns abnormal returns.

Anomalies (calendar effects, momentum, value), limits to arbitrage, transaction costs, short-sale constraints, and behavioral biases — overconfidence, herding, anchoring, loss aversion — can weaken efficiency. The exam usually wants a balanced answer: inefficiencies may exist, but exploiting them is costly and uncertain.

Implications and the active-passive debate

The efficiency forms have direct implications for strategy. If markets are semi-strong efficient, active managers cannot consistently beat a benchmark net of fees, which strengthens the case for low-cost passive indexing and explains the growth of index funds and ETFs. Empirically, most active funds underperform their benchmarks after costs over long horizons, consistent with strong informational efficiency in large, liquid markets — and weaker efficiency in small, thinly followed, or emerging markets where information diffuses slowly.

Efficiency tends to improve when there are many profit-seeking analysts, low trading costs, easy short selling, and minimal limits to arbitrage.

Behavioral finance and persistent anomalies

Behavioral finance documents systematic biases that can move prices away from fundamentals. Anchoring makes investors cling to a reference price; representativeness leads them to extrapolate recent trends; loss aversion makes losses hurt more than equivalent gains please, encouraging investors to hold losers too long; and herding amplifies bubbles and crashes. Cataloged anomalies include the value effect (low P/B and P/E stocks earning higher returns), the size effect, momentum, the January effect, and post-earnings-announcement drift.

The exam's nuanced view is that many anomalies shrink or vanish once trading costs, risk adjustment, and out-of-sample testing are applied, so an observed pattern is not automatic evidence of inefficiency. A trader who could reliably exploit an anomaly net of costs would, by the act of trading, push the price back toward efficiency.

Exam focus

Identify the weighting method before computing. Past prices → weak form; public filings and news → semi-strong; private information → strong. Any "abnormal" return must be risk-adjusted and measured after trading costs, otherwise it does not contradict efficiency.