Real Estate & Housing Trader

This is a template.
The default signal is keyword-based market discovery combined with probability-extreme detection — remix it with the data sources listed in the Edge Thesis below.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Housing and Fed rate markets are priced by retail traders following mainstream media narratives. This skill exploits two structural edges without any external API:

1. 1. FOMC calendar timing — Rate markets diverge most from CME FedWatch in the weeks before a meeting. Trading the pre-meeting window captures the professional vs retail pricing gap.
2. Market type confidence — Fed/rate decisions are professionally calibrated; crash/bubble markets are emotionally driven. Position sizing reflects this.

Signal Logic

Default Signal: Conviction-Based Sizing with Macro Cycle Bias

1. 1. Discover active housing and rate markets on Polymarket
2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
3. Apply macro_cycle_bias() — combines FOMC month timing with market type confidence
4. Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAXPOSITION
5. Skip markets with spread > MAXSPREAD or fewer than MIN_DAYS to resolution

Macro Cycle Bias (built-in, no API required)

Factor 1 — FOMC Calendar Timing

Fed rate decision markets have their highest edge in the 2–4 weeks BEFORE a meeting — when CME FedWatch (professional market) and Polymarket (retail) diverge most. After the decision, repricing happens within hours.

FOMC meets ~8x/year: Jan, Mar, May, Jun, Jul, Sep, Nov, Dec

Condition	Multiplier
Rate question in FOMC-active month	1.2x — pre-meeting window, edge at its peak
Rate question in gap month (Apr, Aug, Oct)

0.9x — fewer catalysts |

Factor 2 — Market Type Confidence

Market type	Multiplier	Why
Fed/FOMC rate decisions	1.25x	CME FedWatch = professional-grade calibration
Mortgage rate markets

1.15x | Mechanically tied to Fed funds — directionally predictable |
| Case-Shiller / price index | 1.10x | Data-driven index releases — trackable trajectory |
| Housing crash / bubble / collapse | 0.75x | Fear/narrative-driven — hard to time, high variance |
| Commercial RE / office vacancy | 0.80x | WFH narrative distorts rational pricing |

Combined capped at 1.40x. A Fed rate cut market in March → 1.2 × 1.25 = 1.40x (cap) — maximum edge. A "housing bubble crash" question → 1.0 × 0.75 = 0.75x — trade very conservatively.

Remix Signal Ideas

• - CME FedWatch: Replace market.current_probability with FedWatch implied probability — trade the divergence between professional futures and Polymarket retail pricing
• FRED API: Federal Reserve economic data releases as leading signal for rate trajectory
• Case-Shiller releases: Track monthly index trajectory to front-run known lagged data
• Zillow / Redfin Research: Regional data as leading indicator for national market questions

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.

Scenario	Mode	Financial risk
INLINECODE5	Paper (sim)	None
Cron / automaton

Paper (sim) | None |
| python trader.py --live | Live (polymarket) | Real USDC |

INLINECODE7 and cron: null — nothing runs automatically until you configure it in Simmer UI.

Required Credentials

Variable	Required	Notes
INLINECODE9	Yes	Trading authority. Treat as high-value credential.

Tunables (Risk Parameters)

All declared as tunables in clawhub.json and adjustable from the Simmer UI.

Variable	Default	Purpose
INLINECODE12	INLINECODE13	Max USDC per trade (reached at 100% conviction)
INLINECODE14

8000 | Min market volume filter (USD) |
| SIMMER_MAX_SPREAD | 0.08 | Max bid-ask spread (8%) |
| SIMMER_MIN_DAYS | 7 | Min days until resolution |
| SIMMER_MAX_POSITIONS | 6 | Max concurrent open positions |
| SIMMER_YES_THRESHOLD | 0.38 | Buy YES if market price ≤ this value |
| SIMMER_NO_THRESHOLD | 0.62 | Sell NO if market price ≥ this value |
| SIMMER_MIN_TRADE | 5 | Floor for any trade (min USDC regardless of conviction) |

Dependency

INLINECODE28 by Simmer Markets (SpartanLabsXyz)

• - PyPI: https://pypi.org/project/simmer-sdk/
• GitHub: https://github.com/SpartanLabsXyz/simmer-sdk