Wochentage — ^GSPC

Shows how the weekly return builds from Monday to Friday. The yellow line shows the current week for comparison. If the curve rises mainly at the start of the week, this suggests early buying pressure (e.g. institutional allocation on Monday).

Weekday	Avg Return	Median	Std. Dev.	Win Rate	n

Breaks down the daily return into Overnight (yesterday's close → today's open) and Intraday (open → close). If the return comes mainly overnight, buy-and-hold investors benefit. If intraday dominates, active trading is relevant.

Probability that the following day is positive, depending on whether the previous day was positive (↑) or negative (↓). Values above 55% indicate trend continuation, below 45% mean reversion.

Shows whether weekday effects vary seasonally. E.g. the Monday effect may only be significant in Q4 (window dressing, year-end rally), while disappearing in Q2/Q3.

Measures the return over the weekend (Friday close → Monday open, residual method). Historically a negative weekend effect is often observed for equities — Mondays open below Friday's close.

• Weekday Return: For each trading day the return is calculated according to the selected mode.
• Cumulative Weekly Progression: Per week the log-returns are cumulated, then averaged across all weeks per weekday position.
• Overnight vs. Intraday: Residual method (overnight = total - intraday). Avoids distortion from differing dividend adjustments between Open[t] and Close[t-1].
• Weekend Effect: (Mon Close / Fri Close - 1) × 100 minus Mon Intraday — residual method.
• Consecutive Analysis: P(next day↑ | prev day↑) and P(next day↑ | prev day↓). Conditional probability.
• Streak: Current win/loss series per weekday (W = Close > prev day, L = loss).
• Trend Filter (SMA): Only days count where Close[t-1] > SMA[t-1].
• OBOS Filter (RSI): Only days count where RSI[t-1] < threshold (oversold condition).
• Crypto Detection: If weekend data is available, Sat+Sun are included (otherwise Mon–Fri).