30-Day Stock Market Series
Day 16 of 30
Sector Rotation: Following Smart Money Through the Economy
Different sectors outperform at different stages of the economic cycle. Day 16 teaches you to position your portfolio ahead of the rotation — not after it.
The Economic Cycle and Sector Performance
The economy moves in cycles: Expansion → Peak → Contraction → Trough → Recovery. Each phase favours different sectors.
Early Cycle (Recovery): Financials, Consumer Discretionary, Real EstateInterest rates bottoming out. Credit growth picking up. Consumer confidence returning. Banks and NBFCs lead the rally.
Mid Cycle (Expansion): Technology, Industrials, MaterialsCorporate capex accelerating. IT spending rising. Infrastructure buildout. This is the longest phase.
Late Cycle (Peak): Energy, Commodities, HealthcareInflation rising. Commodity demand at peak. Defensives start outperforming. Reduce cyclicals.
Contraction/Bear: Consumer Staples, Utilities, PharmaRevenue visibility. Inelastic demand. Cash-generating businesses. These sectors protect capital.
India-Specific Sector Dynamics
- IT: Tracks US tech spending and USD/INR. Outperforms when dollar is strong
- Pharma: Defensive + export-driven. Outperforms in global risk-off periods
- PSU Banks: Track credit growth and NPA cycles. Best in early recovery
- FMCG: Rural demand + inflation pass-through. Defensive in downturns
- Capital Goods: Government capex driven. Tracks union budget announcements
# Track sector momentum using NSE sector indices
sectors = {
'NIFTY_BANK': '^NSEBANK',
'NIFTY_IT': '^CNXIT',
'NIFTY_PHARMA': '^CNXPHARMA',
'NIFTY_FMCG': '^CNXFMCG'
}
import yfinance as yf
for name, ticker in sectors.items():
data = yf.Ticker(ticker).history(period='3mo')
ret_3m = (data['Close'].iloc[-1] / data['Close'].iloc[0] - 1) * 100
print(f"{name}: {ret_3m:.1f}%")
Today's Task
Look at the last 6 months of NSE sector index returns. Which sectors led? Which lagged? Cross-reference with RBI's latest policy stance to identify where we are in the cycle.