OPEN-SOURCE SCRIPT
Indicator: Profitability by Day & Hour (stacked, non-overlay)

What it does
This tool performs a simple seasonality study on the selected symbol. It measures historical returns and summarizes them in two horizontal heatmaps:
Hours table (top) — Columns 00–23 show the average return of each clock hour, plus sample size, win rate, volatility (SD), and a t-score.
Days table (middle) — Columns 1–7 correspond to Mon–Sun with the same metrics.
Summary (bottom) — Shows the most profitable day and hour in the history loaded on your chart.
Green cells indicate higher average returns; red cells indicate lower/negative averages. The layout is centered on the screen, with the hours table above the days table for quick scanning.
How it works (methodology)
Returns: by default the indicator uses log returns ln(Ct/Ct-1) (you can switch to simple % if you prefer).
Daily aggregation (no look-ahead): day statistics are computed from completed daily closes via a higher timeframe request. Yesterday’s daily close vs. the prior day is added to the appropriate weekday bucket, preventing repaint/forward bias.
Hourly aggregation (intraday only): hour statistics are computed bar-to-bar on the current intraday timeframe and accumulated by clock hour (00–23) of the symbol’s exchange timezone.
Metrics per bucket:
Mean: average return in that bucket.
n: number of observations.
Win%: share of positive returns.
SD: standard deviation of returns (volatility proxy).
t-score: mean / SD * sqrt(n) — a quick stability signal (not a hypothesis test).
The indicator does not rely on future data and does not repaint past values.
Reading the tables
Start with the Mean row in each table: it’s color-mapped (red → yellow → green).
Check n (sample size). A bright green cell with very low n is less meaningful than a mild green cell with large n.
Use Win% and SD to judge consistency and noise.
t-score is a compact “signal-to-noise × sample size” measure; higher absolute values suggest more stable effects.
Typical observations traders look for (purely illustrative): for some equity indices, the first hour after the cash open can dominate; for FX/crypto, certain late-US or early-Asia hours sometimes stand out. Always verify on your symbol and timeframe.
This tool performs a simple seasonality study on the selected symbol. It measures historical returns and summarizes them in two horizontal heatmaps:
Hours table (top) — Columns 00–23 show the average return of each clock hour, plus sample size, win rate, volatility (SD), and a t-score.
Days table (middle) — Columns 1–7 correspond to Mon–Sun with the same metrics.
Summary (bottom) — Shows the most profitable day and hour in the history loaded on your chart.
Green cells indicate higher average returns; red cells indicate lower/negative averages. The layout is centered on the screen, with the hours table above the days table for quick scanning.
How it works (methodology)
Returns: by default the indicator uses log returns ln(Ct/Ct-1) (you can switch to simple % if you prefer).
Daily aggregation (no look-ahead): day statistics are computed from completed daily closes via a higher timeframe request. Yesterday’s daily close vs. the prior day is added to the appropriate weekday bucket, preventing repaint/forward bias.
Hourly aggregation (intraday only): hour statistics are computed bar-to-bar on the current intraday timeframe and accumulated by clock hour (00–23) of the symbol’s exchange timezone.
Metrics per bucket:
Mean: average return in that bucket.
n: number of observations.
Win%: share of positive returns.
SD: standard deviation of returns (volatility proxy).
t-score: mean / SD * sqrt(n) — a quick stability signal (not a hypothesis test).
The indicator does not rely on future data and does not repaint past values.
Reading the tables
Start with the Mean row in each table: it’s color-mapped (red → yellow → green).
Check n (sample size). A bright green cell with very low n is less meaningful than a mild green cell with large n.
Use Win% and SD to judge consistency and noise.
t-score is a compact “signal-to-noise × sample size” measure; higher absolute values suggest more stable effects.
Typical observations traders look for (purely illustrative): for some equity indices, the first hour after the cash open can dominate; for FX/crypto, certain late-US or early-Asia hours sometimes stand out. Always verify on your symbol and timeframe.
Skrip open-source
Dengan semangat TradingView yang sesungguhnya, penulis skrip ini telah menjadikannya sumber terbuka, sehingga para trader dapat meninjau dan memverifikasi fungsinya. Hormat untuk penulisnya! Meskipun anda dapat menggunakannya secara gratis, ingatlah bahwa penerbitan ulang kode tersebut tunduk pada Tata Tertib kami.
Pernyataan Penyangkalan
Informasi dan publikasi tidak dimaksudkan untuk menjadi, dan bukan merupakan saran keuangan, investasi, perdagangan, atau rekomendasi lainnya yang diberikan atau didukung oleh TradingView. Baca selengkapnya di Persyaratan Penggunaan.
Skrip open-source
Dengan semangat TradingView yang sesungguhnya, penulis skrip ini telah menjadikannya sumber terbuka, sehingga para trader dapat meninjau dan memverifikasi fungsinya. Hormat untuk penulisnya! Meskipun anda dapat menggunakannya secara gratis, ingatlah bahwa penerbitan ulang kode tersebut tunduk pada Tata Tertib kami.
Pernyataan Penyangkalan
Informasi dan publikasi tidak dimaksudkan untuk menjadi, dan bukan merupakan saran keuangan, investasi, perdagangan, atau rekomendasi lainnya yang diberikan atau didukung oleh TradingView. Baca selengkapnya di Persyaratan Penggunaan.