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Implied Volatility vs Beta: What Each Tells You
NVDA beta against SPY, re-estimated monthly over a rolling twelve-month windowseries · 2026-08-28 · 48×4Preview: a 16-point series, ending lower. Average absolute daily move on sessions when SPY moved less than 0.25 percentranking · 2026-08-28 · 10×4Preview: 10 ranked values, largest first. Near-the-money implied volatility, 20 to 45 days to expiry, three weeks to Aug 21 2026table · 2026-08-28 · 11×5 Beta and R-squared against SPY: daily returns versus weekly, twelve months to Aug 21 2026table · 2026-08-28 · 10×5
NVDA beta against SPY, re-estimated monthly over a rolling twelve-month window

NVDA beta against SPY, re-estimated monthly over a rolling twelve-month window

most recentas of series 48×4read in context →
NVDA beta against SPY, re-estimated monthly over a rolling twelve-month window — 48 rows by 4 columns, computed from US exchange, SIP and OPRA data.
monthmonth_labelrolling_beta_1yr_squared
2022-09Sep 20222.320.65
2022-10Oct 20222.260.64
2022-11Nov 20222.210.65
2022-12Dec 20222.220.71
2023-01Jan 20232.190.71
2023-02Feb 20232.190.7
2023-03Mar 20232.170.65
2023-04Apr 20232.080.63
2023-05May 20232.040.62
2023-06Jun 20232.060.51
2023-07Jul 20232.050.47
2023-08Aug 20232.080.46
2023-09Sep 20232.030.43
2023-10Oct 20232.110.43
2023-11Nov 20232.180.4
2023-12Dec 20232.050.33
2024-01Jan 202420.3
2024-02Feb 20241.950.28
2024-03Mar 20242.020.29
2024-04Apr 20242.220.29
2024-05May 20242.360.31
2024-06Jun 20242.160.32
2024-07Jul 20242.280.32
2024-08Aug 20242.450.35
2024-09Sep 20242.530.39
2024-10Oct 20242.680.42
2024-11Nov 20242.730.42
2024-12Dec 20242.760.42
2025-01Jan 20252.660.41
2025-02Feb 20252.870.42
2025-03Mar 20252.820.43
2025-04Apr 20252.690.44
2025-05May 20252.10.49
2025-06Jun 20252.090.53
2025-07Jul 20252.060.54
2025-08Aug 20251.980.54
2025-09Sep 20251.90.53
2025-10Oct 20251.850.52
2025-11Nov 20251.830.53
2025-12Dec 20251.840.53
2026-01Jan 20261.870.54
2026-02Feb 20261.760.59
2026-03Mar 20261.730.58
2026-04Apr 20261.70.61
2026-05May 20261.740.41
2026-06Jun 20261.780.4
2026-07Jul 20261.850.43
2026-08Aug 20261.870.44
the exact SQL behind every number
WITH
    px AS
    (
        SELECT
            ticker,
            date,
            toFloat64(close) AS close_px
        FROM global_markets.stocks_daily_aggs
        WHERE ticker IN ('SPY','NVDA')
          AND date >= '2021-08-01'
          AND date <= '2026-08-21'
    ),
    daily_ret AS
    (
        SELECT
            ticker,
            date,
            close_px / lagInFrame(close_px) OVER (PARTITION BY ticker ORDER BY date ROWS BETWEEN 1 PRECEDING AND CURRENT ROW) - 1 AS ret
        FROM px
    ),
    paired AS
    (
        SELECT
            s.date AS d,
            s.ret  AS stock_ret,
            i.ret  AS index_ret
        FROM daily_ret AS s
        INNER JOIN
        (
            SELECT date, ret FROM daily_ret WHERE ticker = 'SPY' AND isFinite(ret)
        ) AS i ON i.date = s.date
        WHERE s.ticker = 'NVDA' AND isFinite(s.ret)
    ),
    anchors AS
    (
        SELECT DISTINCT toStartOfMonth(d) AS anchor
        FROM paired
        WHERE d >= '2022-09-01'
    )
SELECT
    formatDateTime(a.anchor, '%Y-%m')                                    AS month,
    formatDateTime(a.anchor, '%b %Y')                                    AS month_label,
    round(covarSamp(p.stock_ret, p.index_ret) / varSamp(p.index_ret), 2) AS rolling_beta_1y,
    round(pow(corr(p.stock_ret, p.index_ret), 2), 2)                     AS r_squared
FROM anchors AS a, paired AS p
WHERE p.d < a.anchor
  AND p.d >= subtractYears(a.anchor, 1)
GROUP BY a.anchor
ORDER BY a.anchor
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