Chapter 12 — Bodie, Kane & Marcus
Monmouth University
International markets, exchange rates, political risk
GDP, unemployment, inflation, interest rates, fiscal & monetary policy
Peaks, troughs, leading/coincident/lagging indicators
Cyclical vs. defensive, sector rotation, life cycles, Porter’s Five Forces
Core idea: Security analysis follows a top-down approach — the macro environment sets the stage for industry and firm performance.
International factors that move markets
The international economy affects a firm through:
Foreign demand for domestic goods depends on relative economic strength.
Exchange rates determine how expensive domestic goods are abroad (and vice versa).
Returns on foreign investments depend on local conditions & currency movements.
Key observation: Stock market returns may not mirror economic growth — they are driven by the ability to beat prior expectations, not by the level of GDP itself.
Political risk matters: Government bailouts, budget deficits, trade policy, protectionism, and workforce policies all shape the investing landscape.
The exchange rate is the rate at which domestic currency converts to foreign currency.
Example: If EUR/USD rises from 1.10 to 1.25, European goods become more expensive for U.S. consumers — affecting firms with European supply chains.
Key variables that move markets at home
Total market value of goods & services produced. The broadest measure of economic activity.
Ratio of unemployed to total labor force. High unemployment → weak consumer spending.
Rate of rising prices. High inflation = demand exceeds productive capacity.
The trade-off: Governments walk a fine line — policies to reduce unemployment can increase inflation, and vice versa (Phillips Curve).
Stock prices tend to rise with earnings, but P/E ratios fluctuate (12–25×) based on interest rates, risk appetite, and inflation expectations.
Demand shock: Event affecting demand for goods (e.g., tax cuts, pandemic stimulus)
Supply shock: Event affecting production capacity (e.g., oil embargo, supply chain disruption)
Key insight: The real interest rate is where supply of savings meets demand for borrowing — government policy shifts these curves.
Government's taxing & spending decisions.
Federal Reserve controls the money supply.
In a recession: Expansionary fiscal policy (lower taxes, more spending) + expansionary monetary policy (lower rates) work together to stimulate recovery. In a boom, the opposite is used to prevent overheating.
Select the best explanation:
Which firm will have higher profits in a recession?
Which stock has the higher beta?
Peaks, troughs, and how to see them coming
Business cycles are recurring patterns of recession and recovery in economic activity.
Transition from expansion to contraction. Economic activity at its highest.
Transition from recession to recovery. Economic activity at its lowest.
Timing problem: NBER doesn't declare recessions until several months after they start — by the time it's official, markets have already moved.
Above-average sensitivity to the business cycle. Profits swing dramatically with the economy.
Below-average sensitivity. Demand is relatively stable regardless of economic conditions.
Choose industry based on business cycle stage — but how sure are you about timing?
Economic series that tend to rise or fall in advance of the rest of the economy:
Why these lead: They capture decisions made today that affect economic activity tomorrow — new orders placed, permits filed, expectations formed.
Move in tandem with the economy:
Rise or fall after the rest of the economy:
Analogy: Leading indicators are the headlights. Coincident indicators are the dashboard. Lagging indicators are the rearview mirror.
Key releases and their typical schedule:
| Release | Frequency | Type | Market Impact |
|---|---|---|---|
| Nonfarm Payrolls | Monthly (1st Fri) | Coincident | Very High |
| CPI / Inflation | Monthly | Lagging | Very High |
| GDP | Quarterly | Coincident | High |
| FOMC Decision | 8× per year | Policy | Very High |
| ISM Manufacturing | Monthly | Leading | High |
| Consumer Confidence | Monthly | Leading | Moderate |
| Housing Starts | Monthly | Leading | Moderate |
| Initial Jobless Claims | Weekly | Leading | High |
Markets react to surprises, not the data itself. If unemployment comes in at 4.0% when the consensus expected 4.2%, that's bullish — even though 4% is "high" in absolute terms.
| Indicator | Your Answer | Feedback |
|---|---|---|
| S&P 500 stock prices | ||
| Industrial production | ||
| Average prime rate | ||
| Housing permits | ||
| Average duration of unemployment |
From the macro to the sector level
Not all industries are equally sensitive. Three factors determine sensitivity:
Necessities (food, medicine) are stable. Discretionary items (vacations, luxury goods) fluctuate with income.
High fixed costs → profits swing more with revenue changes. Low fixed costs → more stable profits.
High debt → fixed interest payments amplify profit swings. Interest is a fixed cost!
Rule of thumb: High sales sensitivity + high operating leverage + high financial leverage = highly cyclical stock (high beta).
Shift your portfolio into sectors expected to outperform based on the business cycle stage:
| Stage | Favored Sectors |
|---|---|
| Early Recovery | Cyclicals, small caps, transports |
| Expansion | Tech, capital goods, industrials |
| Late Expansion | Energy, commodities, materials |
| Recession | Defensives: utilities, healthcare, staples |
Caveat: Sector rotation sounds easy in theory, but timing the cycle is extremely difficult in practice.
Stages firms pass through on the way to maturity:
New technology or product. High growth potential, but also high risk. Often unprofitable initially. Example: Electric vehicles in 2015.
Industry leaders emerge. Growth remains above average. Market share battles intensify. Example: Streaming services 2018–2022.
Product has reached full market potential. Growth matches the overall economy. Stable cash flows, lower reinvestment. Example: Automobiles.
Grows slower than the overall economy, or shrinks outright. Products replaced by newer alternatives. Example: Print newspapers.
Industry structure determines long-run profitability:
Threat of Entry — New entrants pressure prices & profits
Bargaining Power of Suppliers
Industry Rivalry
Market share competition pressures price & profits
Bargaining Power of Buyers
Threat of Substitutes — Related products can steal market share
Investment implication: Industries with high barriers to entry, weak suppliers/buyers, few substitutes, and limited rivalry → sustained high profitability.
The North American Industry Classification System uses numerical codes to group firms by activity.
| Code | Sector |
|---|---|
| 31–33 | Manufacturing |
| 44–45 | Retail Trade |
| 51 | Information |
| 52 | Finance & Insurance |
| 54 | Professional Services |
The classification problem: Where do you put Amazon? Retail? Cloud computing? Entertainment? Logistics?
Modern conglomerates don't fit neatly into single codes. Industry analysis requires judgment about which segment matters most.
Bloomberg tip: Use BI GO (Bloomberg Intelligence) for sector-level analysis and peer comparisons.
Next up: Chapter 13 — Equity Valuation. We'll use macro & industry analysis to inform DCF and DDM models.