final project

Analysis

• XLE

• XLK

• Volatility

• CPI

Preprocessing

30 days return and spread

• Spread > 0 = XLE (Energy) beat XLK (Tech) over that 30-day window

• Spread < 0 = XLK (Tech) beat XLE (Energy)

• Spread = 0 = they performed identically

Link to CPI event

• CPI release dates are calendar dates — they don't align row-for-row with the price table

• Needed a way to find "the price 30 trading days after this CPI release" using calendar dates

• Why 42: 30 trading days = 6 trading weeks → 6 × 7 calendar days/week = 42 calendar days (converts trading-day count into a calendar-day shift)

• Shifted each CPI release date +42 days, then joined that shifted date to the price table's Date column — this lines up each CPI event with the return that ends ~30 trading days later

The math:

• A trading week = 5 days (Mon–Fri)

• A calendar week = 7 days

• So 30 trading days ÷ 5 days/week = 6 weeks

• 6 weeks × 7 calendar days/week = 42 calendar days

• In normal months, XLE slightly beats XLK on average (+0.8%)

• In surprise months (hot CPI), XLE actually underperforms XLK by 3.1% on average

• Hot CPI surprises don't push Energy (XLE) ahead of Tech (XLK) like expected — actually the opposite happens

• In surprise months, Tech outperforms Energy by ~3-4 percentage points on average

• This contradicts the common "inflation hurts tech, helps energy" narrative

• Possible reasons: tech's AI-driven earnings growth offset rate fears; energy is driven more by oil supply/OPEC than CPI

• p-value = 0.336 — far above the standard 0.05 threshold → the difference is NOT statistically significant

• The 95% confidence interval (−0.045 to 0.124) includes zero — meaning we cannot rule out "no real difference" between surprise and normal months

• In plain terms: the −3.1% vs +0.8% gap you saw earlier could plausibly just be random noise, not a real pattern

This is your key results table — let's read it carefully.

Group Mean Spread Std Dev Count Normal months (Flag=0) +0.008 (0.8%) 0.106 44 Surprise months (Flag=1) −0.031 (−3.1%) 0.120 11

This is the opposite of what your hypothesis predicted.

Your original question expected: when CPI surprises to the upside, XLE should outperform XLK (positive spread). Instead, you're finding:

• In normal months, XLE slightly beats XLK on average (+0.8%)

• In surprise months (hot CPI), XLE actually underperforms XLK by 3.1% on average

This is a genuinely interesting finding — it contradicts the simple "inflation surprise → rotate into energy" story. A few honest possible explanations to discuss in your report:

1. Small sample — only 11 surprise months out of 55. One or two extreme observations could be swinging this a lot.

2. Tech resilience — in 2021–2025, mega-cap tech (driving XLK) may have been resilient to rate fears due to strong earnings, especially AI-driven names.

3. Energy-specific drivers — oil price swings (OPEC decisions, geopolitical shocks) may dominate XLE more than CPI surprises do.