The foundational single-period return measure capturing both income and capital gain/loss.
Bond: Coupon = 8%, YTM = 8%, N = 30 years, P₀ = $1,000
Interest rates fall → P₁ = $1,050
HPR = [ 80 + (1,050 − 1,000) ] ÷ 1,000 = 130 ÷ 1,000
8% coupon yield + 5% capital gain. Rates fell → price rose — the Session 2 inverse relationship in action.
Standard deviation (σ) measures how much returns deviate from the mean — the course's primary risk proxy.
| Asset | Avg Annual Return | Std Dev (Risk) | Key Point |
|---|---|---|---|
| Common Stocks | 10.70% | 17.05% | Highest return, highest risk |
| Long Bonds | 8.52% | 9.80% | Intermediate risk/return |
| Treasury Bills ★ | 6.35% | 3.67% | Risk-free rate proxy |
| Inflation | 4.01% | 3.18% | Real return benchmark |
The core insight of MPT: Portfolio return is a weighted average of individual returns — but portfolio risk is NOT.
Correlation is the engine of diversification. It ranges from −1 to +1.
| ρ Value | Relationship | Diversification Benefit |
|---|---|---|
| +1.0 | Perfect positive | None — portfolio risk = weighted average |
| 0 to +1 | Partial positive | Moderate — most real-world asset pairs |
| ~0 | No relationship | Substantial |
| −1.0 | Perfect negative | Maximum — theoretically riskless portfolio possible (basis for hedging) |
| Asset Pair | ρ | Implication |
|---|---|---|
| Canadian vs. U.S. Stocks | 0.686 | Moderate positive — some diversification benefit from going international |
| Canadian Stocks vs. T-Bills | −0.077 | Near zero (slightly negative) — excellent diversifier; holding some T-bills dramatically cuts portfolio risk |
| Type | Also Called | Diversifiable? | Examples |
|---|---|---|---|
| Market Risk | Systematic, Non-diversifiable | No ✗ | Recessions, interest rate changes, inflation shocks |
| Unique Risk | Non-systematic, Diversifiable, Idiosyncratic | Yes ✓ | CEO departure, product recall, lawsuit, fire at plant |
| Source | Recommended Number | Rationale |
|---|---|---|
| Benjamin Graham (1949) | 10–30 stocks | Adequate diversification; beyond this, transaction costs offset marginal benefit |
| Modern studies | 50–100+ | More recent data shows higher number needed for true diversification |
| Practical advice (Bernstein) | Broad index funds | Low cost, hundreds/thousands of stocks, eliminates selection risk |
Adding international stocks to a domestic-only portfolio lowers the systematic risk floor further — domestic-only portfolios plateau at a higher risk level than globally diversified portfolios.
Definition: An efficient market is one where prices quickly and relatively accurately reflect all relevant available information, so prices are correct on average.
Prices reflect all past market data — price history and volume.
Technical analysis (chart patterns) is useless.
Well Supported ✓Prices reflect all publicly available information — earnings, dividends, filings, news.
Fundamental analysis cannot generate consistent excess returns.
Largely Supported (with exceptions) ⚠Prices reflect all information — including private/inside information.
Even insiders cannot earn abnormal returns.
Not Supported ✗| Form | Empirical Verdict | Key Evidence |
|---|---|---|
| Weak | Well supported | Serial correlation tests; price changes largely independent; technical rules don't outperform buy-and-hold after costs |
| Semi-Strong | Largely supported | Active fund managers underperform passive benchmarks by 50–200 bps after fees; event studies show rapid price adjustment |
| Strong | Not supported | Insiders earn abnormal returns; insider trading laws exist to prevent exploitation of private information (e.g., Galleon hedge fund: CEO jailed 11 years) |
Anomalies are exceptions to market efficiency — patterns that persist and could theoretically be exploited. Most violate semi-strong form EMH since they use publicly available information.
Stocks with high returns in the past 3–12 months tend to continue outperforming in the subsequent 3–12 months. "Winners keep winning."
Canadian data: Top 30 momentum → 20.76% vs TSX 6.10% (1980–99, 6-month HPR)
Over longer horizons (3–5 years), prior losers outperform prior winners — stock prices mean revert. Opposite of momentum. Note: Does not hold in Canadian markets (Kryzanowski & Zhang).
Low P/E, low Market-to-Book, high dividend yield stocks ("value stocks") consistently outperform high P/E, high M/B growth stocks — even after risk adjustment. Anomalous because ratios are publicly available.
Small-cap stocks outperform large-cap stocks even after adjusting for risk. Interacts with January effect (up to 50% of size premium occurs in January).
Returns statistically higher in January, especially for small caps. Driven by tax-loss selling in December + "window dressing" by fund managers. Evidence suggests this has weakened as investors have traded it away.
Stock prices continue drifting after positive earnings surprises — the market underreacts to new information. Prices should adjust instantly in semi-strong efficient markets.
If mispricing were recognized and exploited, it should be arbitraged away. But behavioural biases are systematic — they don't disappear with experience. Investors:
HPR directly extends bond pricing. When rates fall, P₁ rises → HPR exceeds coupon yield. The inverse price-yield relationship drives the capital gain component of HPR.
T-bill rate (risk-free) and the equity risk premium (stocks − T-bills = 4.35%) are inputs into cost of equity. Session 6 explains WHY investors demand this premium — compensation for systematic risk.
Beta (β) is the formal measure of a stock's systematic risk. CAPM prices that risk: E(r) = Rf + β × (Rm − Rf). Everything in Session 6 — systematic risk, market risk premium, diversification — is the foundation for CAPM.
Market efficiency assumptions underpin public market comparables. If markets are semi-strong efficient, trading multiples are fair signals of value — making comp analysis a valid valuation tool.
Operational, allocational, and informational efficiency — introduced in Session 1 — reappear here as the three components of market efficiency. Informational efficiency is the EMH focus.
Session 6 is a conceptual bridge. Expect exam questions that test whether you can connect risk measurement → portfolio theory → EMH → why WACC/DCF/comps are valid or invalid valuation tools.