S&P 500 Index Prices CSV – FRED (Federal Reserve Bank of St. Louis) (Date)
- Rows
- 2,610
- Columns
- 2
Daily S&P 500 closing index value from FRED. Observations represent the daily index value at market close. Covers 10 years of daily history per current FRED/S&P Dow Jones Indices LLC agreement.
AI analysis
Analysis: S&P 500 Index Prices (FRED)
1. Dataset Overview & Value
This dataset provides daily closing values for the S&P 500 index, sourced directly from the Federal Reserve Bank of St. Louis's FRED API (fredgraph.csv?id=SP500). FRED is a highly authoritative, widely-used publisher for macroeconomic and financial time series, and its direct API sourcing suggests this data is refreshed on a regular basis (likely daily, consistent with market close reporting). The 10-year window (2016-05-23 to 2026-05-22) makes this a strong backbone series for correlation studies — the S&P 500 is one of the most common benchmark variables against which economists and analysts test relationships with interest rates, inflation, unemployment, commodity prices, and other equity/bond indices. Note the license constraint mentioned in the description ("per current FRED/S&P Dow Jones Indices LLC agreement") — this may affect redistribution or commercial use of the raw index values, which is worth flagging before downstream use.
2. Data Quality Observations
The dataset is small in column count (only 2 columns: Date and SP500) but reasonably deep in rows (2,610). The Date column is clean — zero nulls, 2,610 distinct values, meaning no duplicate dates and full continuity as a join key. The SP500 value column, however, has 95 nulls out of 2,610 rows (3.6%), which is disproportionate given it's the only substantive data column — these are almost certainly non-trading days (weekends/holidays) that were left as blank rather than dropped, a common artifact of FRED's calendar-day series construction. Duplicate-row detection is marked as pending Phase D recomputation, so that check should be completed before this dataset is used in production correlation work — if the source truly has 2,610 distinct dates with zero repeats, duplicates are unlikely, but this should be confirmed. Sample rows are also not yet available, which limits deeper eyeballing of formatting/type consistency at this stage.
3. Key Column Distributions
The SP500 column shows substantial dispersion consistent with a decade that included both the COVID-19 crash/recovery and multiple bull-market runs: min=2000.54, max=7501.24 — a 3.75x range. The mean (3,962.42) sitting above the median (3,861.59) combined with a positive skew of 0.625 indicates a right-skewed distribution, i.e., a longer tail toward higher index values, which is typical for a price series experiencing sustained long-term growth punctuated by sharp corrections. The interquartile range (Q1=2,779.71, Q3=4,697.74) spans nearly 2,000 points, reflecting the wide structural regime shifts over the 10-year window (multiple market cycles) rather than a single stationary distribution — a reminder that raw levels are non-stationary and should likely be transformed (e.g., log returns, % daily change) before correlation testing.
4. Recommended Join Key
The Date column is the clear and only sensible join key — it's complete (zero nulls), fully distinct (2,610 unique values, one per trading day), and standardized as a Date type. For cross-dataset work, ensure the join partner also uses daily granularity (or aggregate this to weekly/monthly if the partner dataset is lower-frequency, e.g., monthly CPI or quarterly GDP) and align on trading-day vs. calendar-day conventions, given the 95 nulls likely correspond to non-trading dates.
5. Suggested Pairings for Correlation Discovery
Strong candidates from FRED itself (for consistent methodology and licensing) include: 10-Year Treasury Yield (DGS10) and Federal Funds Rate (FEDFUNDS) for rate-sensitivity analysis; CPI/Inflation (CPIAUCSL) for real-return and inflation-hedge studies; VIX (VIXCLS) for volatility/risk-sentiment correlation; Unemployment Rate (UNRATE) for macro-cycle alignment; and Crude Oil (DCOILWTICO) or Dollar Index (DTWEXBGS) for cross-asset relationships. Outside FRED, pairing with sector-level equity indices (Nasdaq, Russell 2000), corporate earnings/valuation datasets (P/E ratios), or global indices (FTSE, Nikkei) would enable lead-lag and co-movement analysis — again converting to returns/percent-change first given the non-stationary, skewed nature of the raw level series identified above.
Columns
- Date (date)
- SP500 (decimal)
