Background to Beige Book Nowcast by Tellusant
Description
We provide a snapshot of current economic activity. It is easy to past data and future projections. We provide the here and now to bridge the gap.
The Fed’s Beige Book, Summary of Commentary on Current Economic Conditions, covers current economic activity for the 12 Federal Reserve Districts. It is published sesqui-monthly (every 1½ months). Tellusant converts it into a quantitative nowcast.
The Beige Book is useful for, among others, CEOs and management teams who want to quickly assess where the economy is at present.
We compute a composite score for each of the twelve districts based on a semantic analysis of the report, then sum the scores weighted by the GDP of each district.
We have published these nowcasts since June 2015 on LinkedIn. The new series published here starts in October 2025. The LinkedIn series can still be found there.
Ther analysis is now entirely performed by our Fedora AI agent (v1.1.4). It consists of five parts:
- ChatGPT = runtime environment
- YAML = analytical serialization
- Excel = model + parameters
- Mermaid v11 = workflow graphing
In the next cycle, we will implemenent a scheduler such as cron in GitHub Action to make the updating instant upon report release.
Workflow
How can a previously manual workflow be automated with AI and other components? We use our Fed Beige Book analysis agent called Fedora as a case study to show the new automated workflow in GPT. No human needs to be involved in the process any more, except for the occasional quality control.
Just like the workflow is automated, the workflow graph generation is also automated using Mermaid v11.
HTML / PDF`"]:::base C["`**Store Source & Metadata**`"]:::base end subgraph S2["`*2. Extraction*`"] D["`**Parse District Sections**`"]:::base E["`**Extract First Sentences**`"]:::base F["`**Extract Full District Text**`"]:::base end subgraph S3["`*3. Scoring*`"] G["`**Apply Growth LUT**
First Sentence`"]:::base H["`**Apply Semantic LUT**
Full Text`"]:::base I["`**Generate District Scores**`"]:::base end subgraph S4["`*4. Aggregation*`"] J["`**Apply GDP Weights
from Workbook**`"]:::base K["`**Compute Metrics: Weighted Mean, DI, WDI**`"]:::base L["`**Compute Semantic Indices**`"]:::base M["`**Compute Composite Macro Index**`"]:::base end subgraph S5["`⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀*5. Output*`"] N["`**Write to Workbook**
Main, Semantic, History`"]:::base O["`**Generate Tellusant Summary**`"]:::base P["`**Generate Charts (Python)**`"]:::base Q["`**Store Audit Trail**`"]:::base end subgraph S6["`*0. Automation*`"] R["`**Scheduled Trigger**
GitHub Actions`"]:::base S["`**Check for New Release**`"]:::base end subgraph S7["`⠀⠀⠀⠀⠀⠀⠀*6. Feedback Loop*`"] T["`**Human Review**`"]:::green U["`**Update in Workbook**`"]:::base end V["`**Final Output**`"]:::red R --> S --> A A --> B --> C --> D --> E D --> F E --> G --> I F --> H --> I I --> J --> K I --> L --> M K --> N M --> N N --> O N --> P N --> Q O --> T P --> T Q --> T -->|⠀if error⠀| U --> G T -->|⠀if correct⠀| V O --> V linkStyle 24 stroke:blue,stroke-width:1; linkStyle 26 stroke:transparent,stroke-width:0; %% ========= STYLES ========= classDef green fill:#E8F5E9,stroke:#1B5E20,stroke-width:2px,color:#111; classDef blue fill:#E3F2FD,stroke:#0D47A1,stroke-width:2px,color:#111; classDef orange fill:#FFF8E1,stroke:#FF6F00,stroke-width:2px,color:#111; classDef red fill:#FDECEA,stroke:#B71C1C,stroke-width:2px,color:#111; classDef grey fill:#F5F5F5,stroke:#424242,stroke-width:2px,color:#111; classDef base fill:#ECECFF,stroke:#9370DB,stroke-width:2px,color:#111; classDef clear fill:transparent,stroke:transparent;
The details of the workflow is best understand by studying the graph.