← 返回
数据分析 Key 中文

Polymarket Science Milestones Trader

Trades Polymarket prediction markets on scientific breakthroughs, Nobel Prizes, physics discoveries, and research milestones. Corrects for systematic retail...
在Polymarket预测市场交易科学突破、诺贝尔奖、物理发现及研究里程碑等事件。纠正系统性散户偏差...
diagnostikon
数据分析 clawhub v0.0.3 3 版本 100000 Key: 需要
★ 0
Stars
📥 629
下载
💾 27
安装
3
版本
#latest

概述

Science Milestones & Research Trader

> This is a template.

> The default signal is keyword-based market discovery combined with conviction-based sizing and science_bias() — remix it with the data sources listed below.

> The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Science markets are priced by non-experts following journalist headlines. Journalists systematically amplify the most optimistic interpretation of scientific results. The research community knows the replication rates, timeline track records, and definitional ambiguities behind each claim type. Retail doesn't. This creates large, consistent mispricings — and two of the most exploitable edges anywhere on Polymarket: hype-claim dampening and Nobel calendar timing.

Signal Logic

Default Signal: Conviction-Based Sizing with Science Hype Correction

  1. Discover active science and research markets on Polymarket
  2. Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
  3. Apply science_bias() — combines science claim type with Nobel calendar timing
  4. Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAX_POSITION
  5. Skip markets with spread > MAX_SPREAD or fewer than MIN_DAYS to resolution

Science Bias (built-in, no API required)

Factor 1 — Science Claim Type: Hype Cycle vs Replication Reality

Claim typeMultiplierThe real signal
---------
CRISPR / gene therapy clinical1.15xclinicaltrials.gov tracks endpoints; regulatory path is public — retail treats as sci-fi
Alzheimer / neurodegeneration drug1.10xPost-Lecanemab/Donanemab, Phase 3 approval path established; calendar trackable
Nobel Prize (any field)1.15x (+ timing)Clarivate Citation Laureates ~40% hit rate; committee rewards 10–30yr replicated work
Dark matter / particle physics0.85xBinary rare events; sensitivity curves published but genuine detections are rare
Quantum computing milestone0.85xRoadmaps exist but corporate "supremacy" claims are marketing-contaminated
AGI / AI consciousness by date0.70xNo agreed definition; every AGI timeline since 1956 has been wrong
Longevity / aging reversal0.70xMouse→human gap is 10–15 years minimum; conference culture creates retail overcrowding
Cancer "cure" / universal treatment0.65xFundamental category error — cancer is 200+ distinct diseases; premise is incoherent
Commercial / grid-connected fusion0.65xITER delayed 2016→2020→2025→2035; every commercial fusion timeline has slipped >50%
Room temperature superconductor0.55xNear-100% replication failure rate; LK-99 (2023) is the definitive template

The RT Superconductor Rule — 0.55x is the lowest multiplier in the entire project across all traders. The reason is historical: every significant "room temperature superconductor" claim since 1987 has either failed replication or been retracted. The 2023 LK-99 episode — global excitement, total replication failure within two weeks — is not an outlier. It is the pattern. When a RT superconductor market appears on Polymarket, the YES side is being priced by media excitement, not physics consensus. The NO edge is structural.

The Fusion Rule — "Fusion is always 5 years away" is not a joke; it's a documented pricing pattern. NIF's December 2022 ignition (Q>1) was genuinely historic. But commercial fusion — grid-connected, cost-competitive electricity — requires solving plasma engineering, materials science, and economic problems that are decades away. Every market asking "will fusion power X by Y" where Y is within 10 years is systematically overpriced.

Factor 2 — Nobel Calendar Timing

The Nobel Prize follows a known annual schedule. Two data sources are public every year:

ConditionMultiplierWhy
---------
Nobel market + October (announcement week)1.25xPhysics Mon, Chemistry Tue, Medicine Mon, Peace Fri — Polymarket takes 15–30 min to reprice each announcement
Nobel market + September (Clarivate month)1.15xClarivate Citation Laureates shortlist published — citation data retail doesn't read
Nobel market + all other months1.00xClarivate predictions still useful but no immediate timing catalyst

The skill prints nobel=ANNOUNCEMENT / CLARIVATE / off-season on startup.

Clarivate Citation Laureates — Clarivate analyzes citation impact across all scientific literature and publishes annual shortlists of researchers predicted to win Nobel Prizes. Their hit rate is ~40% correct in advance — far above the base rate. The key insight: Nobel committees reward longevity of impact, not recency. The Clarivate list reflects citation networks built over decades; retail chases last year's hottest paper. These systematically diverge.

Keywords Monitored

Nobel Prize, Nobel, physics, fusion energy, ITER, nuclear fusion, dark matter,
quantum computer, quantum computing, breakthrough, nature paper, CERN,
James Webb, room temperature superconductor, AGI, consciousness, cancer cure,
Alzheimer treatment, longevity, aging reversal, CRISPR, gene therapy,
clinical trial, phase 3, replication, preprint, arXiv, peer review,
superconductor, LK-99, qubit, quantum supremacy, drug approval

Remix Signal Ideas

  • Clarivate Citation Laureates: September shortlist — use to adjust YES_THRESHOLD per Nobel candidate market; candidates on the shortlist deserve lower YES_THRESHOLD than those off it
  • arXiv API: Monitor preprint velocity per keyword topic — spikes 3–7 days before mainstream coverage, before markets reprice
  • ClinicalTrials.gov: Gene therapy and Alzheimer drug trial completion dates — feed expected date into days-to-resolution analysis
  • Semantic Scholar API: Real-time citation graph — detect breakout papers early before journal publication drives Polymarket question creation

Safety & Execution Mode

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

ScenarioModeFinancial risk
---------
python trader.pyPaper (sim)None
Cron / automatonPaper (sim)None
python trader.py --liveLive (polymarket)Real USDC

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

Required Credentials

VariableRequiredNotes
---------
SIMMER_API_KEYYesTrading authority. Treat as high-value credential.

Tunables (Risk Parameters)

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

VariableDefaultPurpose
---------
SIMMER_MAX_POSITION25Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_VOLUME5000Min market volume filter (USD)
SIMMER_MAX_SPREAD0.12Max bid-ask spread (12%) — wider for low-volume science markets
SIMMER_MIN_DAYS14Min days until resolution — science markets need longer runway
SIMMER_MAX_POSITIONS6Max concurrent open positions
SIMMER_YES_THRESHOLD0.38Buy YES if market price ≤ this value
SIMMER_NO_THRESHOLD0.62Sell NO if market price ≥ this value
SIMMER_MIN_TRADE5Floor for any trade (min USDC regardless of conviction)

Dependency

simmer-sdk by Simmer Markets (SpartanLabsXyz)

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

版本历史

共 3 个版本

  • v0.0.3 当前
    2026-05-01 11:01 安全 安全
  • v1.0.1
    2026-03-30 04:57 安全 安全
  • v1.0.0
    2026-03-20 01:59

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

data-analysis

A股量化 AkShare

mbpz
A股量化数据分析工具,基于AkShare库获取A股行情、财务数据、板块信息等。用于回答关于A股股票查询、行情数据、财务分析、选股等问题。
★ 165 📥 60,008
data-analysis

Data Analysis

ivangdavila
{"answer":"数据分析与可视化。查询数据库、生成报告、自动化电子表格,将原始数据转化为清晰可行的见解。适用于:(1) 您……"}
★ 198 📥 65,118
data-analysis

Excel / XLSX

ivangdavila
创建、检查和编辑 Microsoft Excel 工作簿及 XLSX 文件,支持可靠的公式、日期、类型、格式、重算及模板保留功能。
★ 368 📥 140,456