{"slug":"why-rsi-differs-between-platforms","qid":"close_definitions","label":"Two definitions of one daily close, side by side","post_title":"Why Your RSI Differs Between Platforms","post_url":"/blog/why-rsi-differs-between-platforms#q-close_definitions","columns":["date","session_close","daily_bar_close","close_spread_bps"],"rows":[{"date":"2026-06-01","session_close":306.31,"daily_bar_close":306.31,"close_spread_bps":0},{"date":"2026-06-02","session_close":315.22,"daily_bar_close":315.2,"close_spread_bps":-0.6},{"date":"2026-06-03","session_close":310.39,"daily_bar_close":310.26,"close_spread_bps":-4.2},{"date":"2026-06-04","session_close":311.21,"daily_bar_close":311.23,"close_spread_bps":0.6},{"date":"2026-06-05","session_close":307.39,"daily_bar_close":307.34,"close_spread_bps":-1.6},{"date":"2026-06-08","session_close":301.58,"daily_bar_close":301.54,"close_spread_bps":-1.3},{"date":"2026-06-09","session_close":290.36,"daily_bar_close":290.55,"close_spread_bps":6.5},{"date":"2026-06-10","session_close":291.48,"daily_bar_close":291.58,"close_spread_bps":3.4},{"date":"2026-06-11","session_close":295.34,"daily_bar_close":295.63,"close_spread_bps":9.8},{"date":"2026-06-12","session_close":291.07,"daily_bar_close":291.13,"close_spread_bps":2.1},{"date":"2026-06-15","session_close":296.51,"daily_bar_close":296.42,"close_spread_bps":-3},{"date":"2026-06-16","session_close":299.26,"daily_bar_close":299.24,"close_spread_bps":-0.7},{"date":"2026-06-17","session_close":295.88,"daily_bar_close":295.95,"close_spread_bps":2.4},{"date":"2026-06-18","session_close":297.89,"daily_bar_close":298.01,"close_spread_bps":4},{"date":"2026-06-22","session_close":296.79,"daily_bar_close":297.01,"close_spread_bps":7.4},{"date":"2026-06-23","session_close":294.29,"daily_bar_close":294.3,"close_spread_bps":0.3},{"date":"2026-06-24","session_close":293.07,"daily_bar_close":293.08,"close_spread_bps":0.3},{"date":"2026-06-25","session_close":275.05,"daily_bar_close":275.15,"close_spread_bps":3.6},{"date":"2026-06-26","session_close":281.3,"daily_bar_close":283.78,"close_spread_bps":88.2},{"date":"2026-06-29","session_close":281.63,"daily_bar_close":281.74,"close_spread_bps":3.9},{"date":"2026-06-30","session_close":289.09,"daily_bar_close":289.36,"close_spread_bps":9.3}],"shape":"series","sql":"SELECT\n    toString(m.day)                                                    AS date,\n    round(m.session_close, 2)                                          AS session_close,\n    round(a.agg_close, 2)                                              AS daily_bar_close,\n    round(10000 * (a.agg_close - m.session_close) / m.session_close, 1) AS close_spread_bps\nFROM\n(\n    SELECT\n        toDate(toTimeZone(window_start, 'America/New_York')) AS day,\n        toFloat64(argMax(close, window_start))               AS session_close\n    FROM global_markets.delayed_stocks_minute_aggs\n    WHERE ticker = 'AAPL'\n      AND window_start >= '2026-06-01 04:00:00'\n      AND window_start <  '2026-07-01 04:00:00'\n      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60\n           + toMinute(toTimeZone(window_start, 'America/New_York'))) >= 570\n      AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60\n           + toMinute(toTimeZone(window_start, 'America/New_York'))) < 960\n    GROUP BY day\n) AS m\nINNER JOIN\n(\n    SELECT\n        date                  AS day,\n        toFloat64(max(close)) AS agg_close\n    FROM global_markets.stocks_daily_aggs\n    WHERE ticker = 'AAPL'\n      AND date >= '2026-06-01'\n      AND date <= '2026-06-30'\n    GROUP BY day\n) AS a ON a.day = m.day\nORDER BY date","computed_at":"2026-08-17T15:36:40.682122+00:00","elapsed":0.00338253}