Truflation’s U.S. CPI-like index is designed as a daily-updated inflation measure built from a basket of consumer-spending categories broadly inspired by CPI structure, but implemented with alternative/high-frequency data feeds and a distinct housing treatment. Truflation documents a 7-step process (household expenditure weights → data sources → ingestion → transformations → indexing → weighting/roll-up → publication) and publishes a category-weight appendix for its U.S. index.
At the top level, Truflation publishes a 12-category basket (e.g., Food & non-alcoholic beverages; Housing; Transportation; Utilities; Health; etc.) with category weights such as Housing 23.2%, Transportation 19.8%, Food 15.3%, Health 8.5%, and others. Truflation states that relative importance is updated annually and implemented in February, using the previous year’s data, which is more frequent/less lagged than the BLS CPI’s current annual-weight regime (weights reflecting spending from two years prior).
Methodologically, Truflation’s index differs from the official CPI in several high-impact ways. The most consequential, and most likely to generate persistent divergence, is housing: Truflation’s “Owned housing” component is built using a mixed approach that includes a mortgage-rate-based calculation (e.g., assumptions around down payments and fixed-rate mortgages using Freddie Mac rate series, and weighting new vs. existing mortgages). In contrast, the BLS CPI treats owner-occupied housing via owners’ equivalent rent (OER) derived from the rental market, and collects rent data from sampled units on a 6‑month schedule.
Truflation documents operational controls for missing data, frequency mismatches, and outliers: it flags unusually large moves (example threshold >5%) for review, carries forward monthly series between updates, and uses “interim” repeats when a red flag persists, and it also describes backcasting new provider series to the index base date via correlation splicing. These are practical necessities for a mixed-frequency, multi-provider index—but they also introduce specific risks (stepwise behavior from carry-forwards; dependence on correlation stability for backcasts) that users should understand.
On empirical alignment, Truflation’s own lag-correlation analysis (Jan 2020 to “present” as of the paper’s last update) reports a peak full-sample correlation around r≈0.974 when Truflation is shifted ~+72 days ahead of CPI, and regime-specific leads of about +41 days (Jan 2020–Jan 2021), +75 days (Jan 2021–Jul 2023), and +40–45 days (Jul 2023–present). Because Truflation’s CPI data access may require enterprise API access for full constituent history, a reproducible workflow is necessary to independently compute differences, correlations, and lag structures using Truflation-accessible feeds and BLS CPI series data.
Disclosure
This material is provided by Gryphon Financial Partners, LLC (“Gryphon”) for informational purposes only. It is not intended as a substitute for personalized investment advice or as a recommendation or solicitation of any particular security, strategy, or investment product. Facts presented have been obtained from sources believed to be reliable, though Gryphon cannot guarantee their accuracy or completeness. Gryphon does not provide tax, accounting, or legal advice. Individuals should seek such guidance from qualified professionals based on their specific circumstances.