spring scaries

spring-scaries.py

import yfinance as yf
import pandas as pd
from datetime import datetime, timedelta
from scipy import stats

def get_um_break_dates(year):
    first_day_ny = pd.Timestamp(year, 1, 1)

    # Break starts on the Saturday after seventh week
    break_start_sat = first_day_ny + timedelta(weeks=7)
    while break_start_sat.weekday() != 5:
        break_start_sat += timedelta(days=1)
    
    day_before_break = break_start_sat - timedelta(days=1)
    # This is a two week window to account for UM sliding its start date around
    # Could narrow this if we have a programmatic way to tell when semester starts
    # Swap to 9 for 1 week.
    day_after_break = break_start_sat + timedelta(days=16)
    
    return day_before_break, day_after_break

def analyze_sp500_swing(ticker, years):
    ticker = yf.Ticker(ticker)
    results = []

    for year in years:
        start, end = get_um_break_dates(year)
        
        # Download data for the range (add a buffer to ensure we catch the end day)
        data = ticker.history(start=start.strftime('%Y-%m-%d'), 
                              end=(end + timedelta(days=1)).strftime('%Y-%m-%d'),
                              interval="1d")
        
        try:
            # Extract specific prices
            start_price = data.iloc[0]['Close']
            end_price = data.iloc[-1]['Open']
            
            pct_change = ((end_price - start_price) / start_price) * 100
            
            results.append({
                "Year": year,
                "Start Date": start.date(),
                "End Date": end.date(),
                "Start Price": round(start_price, 2),
                "End Price": round(end_price, 2),
                "Change %": round(pct_change, 2)
            })
        except IndexError as e:
            # This happens if the ticker wasn't listed or no data?
            continue
        except KeyError as e:
            # This happens if the market was closed on those dates?
            continue

    return pd.DataFrame(results)

tickers = {
    "^VIX": "Volatility Index",
}

for ticker, desc in tickers.items():
    skip_years = [2007, 2020]
    df = analyze_sp500_swing(ticker, [i for i in range(1990, 2027) if i not in skip_years])

    print(df.to_string(index=False))
    median_change = df['Change %'].median()
    t_stat, p_value = stats.ttest_1samp(df['Change %'], 0)
    print(f"{ticker} ({desc}) Median Change: {median_change:,.2f}%")
    print(f"T-Statistic: {t_stat:.4f}")
    print(f"P-Value: {p_value:.4f}")