Economic Data Releases — Trading Context

When to load

When analyzing PM contracts about: CPI, inflation, jobs numbers, GDP, unemployment rate, economic data releases.

Instructions

Inject silently. Use to inform analysis and construct distribution-based reasoning.

CPI (Consumer Price Index)

What it is: BLS measures price changes in a basket of consumer goods/services. Released monthly, usually second week, 8:30 AM ET.

Two versions:

Headline CPI: Everything including food and energy

Core CPI: Excludes food and energy. This is what markets and the Fed primarily watch.

Key components by weight:

Shelter (~36%) — LARGEST. Lags real rents by 6-12 months due to BLS methodology (Owners' Equivalent Rent)

Food (~13%)

Energy (~7%) — Most volatile

Used cars, medical, airfares — volatile swing components

Normal ranges for Core CPI MoM:

≤0.2% = cool (dovish for Fed, bullish for rate cuts)

0.3% = inline (neutral)

≥0.4% = hot (hawkish, rate cuts pushed out)

Kalshi CPI contracts: Range buckets (e.g., "Core CPI MoM 0.2-0.3%"). These form an implied probability distribution.

NFP (Non-Farm Payrolls)

What it is: BLS measures monthly job creation. Released first Friday of the month, 8:30 AM ET.

Three numbers that matter:

1. Headline jobs added: Normal range ~100K-250K

2. Unemployment rate: Currently near 4%

3. Average Hourly Earnings (AHE): Wage growth, Fed watches this closely

Key quirk: Revisions are HUGE. A +200K print can be revised to +150K next month. The initial number moves markets most.

Kalshi NFP contracts: Also range buckets, same distribution logic as CPI.

GDP

What it is: Total economic output, reported quarterly by BEA.

Three releases per quarter:

1. Advance (1 month after quarter ends) — most market-moving

2. Second estimate (2 months) — modest revision

3. Third estimate (3 months) — usually ignored

Normal range: 1.5-3.0% annualized. Below 0% for two consecutive quarters = common recession definition (but not official).

Distribution Trading Strategy

The core idea: Most PM traders think in point estimates. You think in distributions.

Process:

1. Get the Cleveland Fed Inflation Nowcast (for CPI) or Atlanta Fed GDPNow (for GDP) — these provide PROBABILITY DISTRIBUTIONS, not just point estimates

2. Map Kalshi bucket prices to an implied probability distribution

3. Compare the two distributions

4. Any bucket where Kalshi implied probability diverges >5pp from the nowcast → potential trade

Example:

Nowcast says P(CPI MoM < 0.2%) = 18%

Kalshi "CPI MoM < 0.2%" trading at 8c (implied 8%)

→ Bucket is underpriced by 10pp. Buy.

You don't need to predict the exact CPI print. You need to find mispriced buckets in the distribution.

Seasonal Traps

January Effect (CPI): January CPI almost always prints hotter than expected. BLS updates seasonal adjustment factors in January. The "hot" bucket is systematically underpriced in January.

Birth-Death Model (NFP): BLS estimates new business creation/destruction using a model. This model overshoots in turning points (adds phantom jobs when economy is actually slowing).

Holiday hiring (NFP): October-December numbers are inflated by seasonal hiring. January often shows a "payback" drop.

Key Data Sources

| Source | What | Update frequency | |--------|------|-----------------| | Cleveland Fed Inflation Nowcast | CPI probability distribution | Daily | | Atlanta Fed GDPNow | GDP point estimate + model details | ~Weekly after component data | | BLS Release Calendar | Exact date/time of CPI, NFP | Fixed schedule | | AAA Gas Prices | Energy component lead indicator | Daily | | Manheim Used Vehicle Index | Used car component lead | Mid-month | | Zillow/Apartment List Rent Index | Shelter component lead (6-12mo) | Monthly |

Trading Rules

1. ALWAYS check nowcast distribution vs Kalshi bucket prices before trading economic data contracts

2. January CPI: bias toward the "hot" bucket (0.3%+ for core MoM)

3. NFP: the initial print matters most for PM resolution; revisions are irrelevant for contract settlement

4. GDP Advance estimate: check GDPNow on the day before release — it's usually within 0.5pp

5. Don't trade the consensus point estimate — trade the distribution tails where Kalshi misprices

6. Use get_forecast tool for Kalshi numeric events (CPI, GDP, unemployment) to see market-implied distributions