FRED – US Dollar Index (Trade Weighted Broad)
- Rows
- 5,320
- Columns
- 2
Daily nominal broad US dollar index against major trading partners from 2006 to present. Key FX benchmark.
AI analysis
Analysis: FRED US Dollar Index (Trade Weighted Broad)
1. Dataset Overview & Value for Correlation Studies This dataset captures the nominal broad US dollar index (DTWEXBGS) — a trade-weighted measure of the dollar's value against a basket of major trading partner currencies — sourced directly from the Federal Reserve Bank of St. Louis (FRED) API at https://fred.stlouisfed.org/graph/fredgraph.csv?id=DTWEXBGS. The FRED provenance is significant: it signals institutional reliability, regular updates, and alignment with official Federal Reserve methodology. Spanning daily observations from 2006 to the present across 5,320 rows, this series covers multiple high-volatility macro cycles — the 2008 financial crisis, the 2014–2015 dollar bull run, COVID-era disruptions, and the aggressive Fed tightening of 2022–2023 — making it an exceptionally rich benchmark for studying how dollar strength propagates through global financial markets.
2. Data Quality Observations Overall quality is good but requires targeted attention. The Date column is clean with zero nulls and 5,320 distinct values, confirming no duplicate dates in the time series — an important structural integrity check for any time-series join. The primary concern is DTWEXBGS, which carries 208 null values (~3.9% of rows). This is the dataset's only data quality issue, but it is disproportionate given that there are only two columns and the index value is the sole measurement. These gaps likely correspond to U.S. federal holidays and weekend non-trading days that FRED includes as date entries without index readings — a common pattern in daily financial series. Duplicate row counts are noted as pending Phase D recomputation, so deduplication validation should be confirmed before production use. No type mismatches are flagged, and the decimal type for DTWEXBGS is appropriate.
3. Distribution & Statistical Highlights The DTWEXBGS index ranges from a minimum of 85.47 to a maximum of 130.04, reflecting substantial dollar volatility over the 18+ year window. The mean (106.24) sits noticeably below the median (109.88), and the interquartile range spans Q1=93.72 to Q3=116.74 — a spread of ~23 index points suggesting prolonged regime shifts rather than mean-reverting noise. The skewness of -0.059 is essentially zero, indicating a near-symmetric distribution with no strong directional bias across the full sample, though this masks regime-specific directionality within sub-periods. The standard deviation of 12.33 (~11.6% of the mean) reflects meaningful macro-cycle variance. With 5,077 distinct values out of 5,112 non-null rows, the data is highly granular with virtually no repeated readings, which is expected for a continuously quoted FX index.
4. Recommended Join Key The Date column is the clear and only recommended join key — it is fully populated (0 nulls), entirely distinct (5,320 unique values), and typed correctly as Date. For cross-dataset joins, care should be taken to align on business-day calendars, since the 208 null DTWEXBGS rows likely represent non-trading days that other financial datasets may simply omit entirely. A left-join strategy from this dataset — or pre-filtering to non-null DTWEXBGS rows — will minimize spurious null propagation. For higher-frequency or international datasets, a date normalization step (e.g., ISO 8601 formatting) should be validated before joining.
5. Suggested Companion Datasets for Correlation Analysis Several dataset categories would pair powerfully with this series:
- Commodity Prices (crude oil/WTI, gold, copper via FRED or EIA): Dollar strength is classically inversely correlated with dollar-denominated commodity prices — a well-documented macro relationship worth quantifying across cycles. - US Trade Balance / Current Account (BEA/FRED): The index is explicitly trade-weighted, making it a natural pair for testing whether dollar appreciation leads or lags deterioration in export competitiveness. - Emerging Market Equity Indices or EM Currency Baskets (e.g., MSCI EM, DXY): EM assets are highly sensitive to dollar cycles; correlation analysis here could reveal lead-lag dynamics. - Federal Funds Rate / US Treasury Yields (FRED): Interest rate differentials are a primary driver of dollar moves — pairing these series enables interest rate parity testing. - US CPI or Inflation Expectations (FRED, BLS): A stronger dollar suppresses import prices; this pairing supports purchasing power and pass-through inflation analysis.
Columns
- Date (date)
- DTWEXBGS (decimal)
