Equity Markets & IPO Trader
This is a template.
The default signal is keyword-based market discovery combined with conviction-based sizing and equity_bias() — two structural edges that work without any external API.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.
Strategy Overview
Equity prediction markets are unique: they run alongside the deepest, most quantified financial markets in the world. The edge is not in predicting markets better than Wall Street — it is in the lag between professional data (earnings base rates, options implied volatility, futures moves) and what Polymarket retail knows. Two structural edges compound cleanly:
- 1. Earnings base rate correction — The most underknown stat in equity markets: S&P 500 companies beat analyst consensus EPS estimates approximately 73–75% of the time, sustained across multiple economic cycles. Large-cap tech (NVDA, AAPL, MSFT, META, GOOG, AMZN) beats ~80–85%. Retail prices earnings beat markets as roughly 50–50. That 20–30 percentage point gap is structural edge that replenishes every earnings season.
- 2. Macro calendar timing lag — S&P 500 futures trade 24/7. When CPI prints, payrolls drop, or FOMC speaks, futures reprice instantly. Polymarket index threshold markets take 20–60 minutes to catch up, especially during pre-market hours. Quarter-start months (Jan, Apr, Jul, Oct) have maximum macro catalyst density — GDP advance estimate, full earnings flood, FOMC decision, and NFP all land within weeks of each other.
Signal Logic
Default Signal: Conviction-Based Sizing with Equity Bias
- 1. Discover active equity and financial markets on Polymarket
- Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1)
- Apply
equity_bias() — market type correction × earnings calendar timing - Size =
max(MIN_TRADE, conviction × bias × MAX_POSITION) — capped at MAXPOSITION - Skip markets with spread > MAXSPREAD or fewer than MIN_DAYS to resolution
Equity Bias (built-in, no API required)
Factor 1 — Market Type / Earnings Base Rate
| Market type | Multiplier | The structural reality |
|---|
| Large-cap tech earnings (NVDA, AAPL, MSFT, META, GOOG, AMZN, TSLA) | 1.25x | ~80–85% beat rate sustained 2020–2024; retail prices as 50–60%; Nvidia beat consensus 7 consecutive quarters |
| General S&P 500 earnings beat |
1.15x | ~73–75% historical beat rate across multiple cycles; retail treats as coin flip; every "will X beat earnings?" is a structural YES lean |
| Index level milestone (S&P 500, Nasdaq, Dow reaching X) |
1.15x | Futures market is a 24-hour reference; Polymarket lags macro catalysts 20–60 min; pre-market hours especially exploitable |
| Dividend / buyback / stock split |
0.90x | Some insider buying signal but corporate decision timing is genuinely uncertain |
| IPO by date / IPO valuation milestone |
0.85x | Window-driven; S-1 filing to pricing gap is highly variable; banker incentives dominant |
| Market crash / correction / bear market by date |
0.75x | Most reliably overpriced category; crashes are vivid but rare in any specific window; VIX-spike retail anchors to worst case when mean reversion is likelier |
| Short squeeze / meme stock milestone |
0.65x | Pure social coordination; requires specific short float data, borrow rate spikes, coordinated buying — none predictable from question text |
The Crash Overpricing Rule — "Will the S&P fall 20% by [date]?" is almost always overpriced on Polymarket. Retail's fear-anchoring after every VIX spike causes these markets to trade at 15–30% when the actual base rate for a 20%+ drawdown in any specific 3-month window is far lower. The vivid availability of 2008, 2020, and 2022 makes retail systematically pessimistic on specific-window crash markets. Dampen every crash/bear market question to 0.75x regardless of current probability.
The Beat Rate Rule — Analyst estimates are deliberately set to be beatable. Companies guide conservatively; analysts shade their models to match guidance; management sandbagging is a documented, multi-decade practice. The 73–75% aggregate beat rate is not a fluke — it is structural. Every "will X beat earnings?" market that prices below 50% is almost certainly mispriced unless the company has a specific documented miss history (e.g., retail, biotech pre-approval).
Factor 2 — Earnings Calendar Timing
| Condition | Multiplier | Why |
|---|
| Earnings-type question + peak season (Jan, Feb, Apr, May, Jul, Aug, Oct, Nov) | 1.20x | Maximum signal density: fresh analyst estimates, current management guidance, live options implied volatility |
| Earnings-type question + off-season (Mar, Jun, Sep, Dec) |
0.85x | Sparse pre-announcements; stale estimates; options vol compressed; base rate edge noisier |
| Index/macro question + quarter-start month (Jan, Apr, Jul, Oct) |
1.10x | GDP advance estimate + full earnings flood + FOMC + NFP all land; maximum macro catalyst density |
Combined Examples
| Market | Type mult | Calendar mult | Final bias |
|---|
| "Will Nvidia beat Q3 earnings?" — October | 1.25x | 1.20x (peak season) | 1.40x cap |
| "Will S&P 500 reach 6,000 by year end?" — January |
1.15x | 1.10x (quarter-start) |
1.27x |
| "Will Apple beat Q1 earnings?" — March | 1.25x | 0.85x (off-season) |
1.06x |
| "Will there be a market crash by December?" | 0.75x | 1.0x |
0.75x — always skeptical |
| "GameStop short squeeze to $100?" | 0.65x | 1.0x |
0.65x — near floor |
| "Will Amazon IPO a subsidiary this year?" | 0.85x | 1.0x |
0.85x |
Keywords Monitored
CODEBLOCK0
Remix Signal Ideas
- - Yahoo Finance options chain: Free unofficial API gives implied volatility and options-implied earnings move — compare the options-implied probability band to Polymarket price for earnings beat/miss markets; the gap is consistently 15–25% for mid-cap companies
- CBOE VIX data feed: VIX level and futures term structure — when VIX spikes, crash markets overprice; when VIX term structure inverts, macro catalyst timing signal for index threshold markets
- SEC EDGAR 8-K filings: Real-time earnings releases hit EDGAR before press coverage — earnings results are public on EDGAR minutes before Polymarket reprices
- CME FedWatch: Fed rate probability from federal funds futures — direct input for "will the Fed cut/hike?" markets; far more precise than Polymarket retail pricing
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 |
15000 | Min market volume filter (USD) — equity markets need liquidity |
|
SIMMER_MAX_SPREAD |
0.07 | Max bid-ask spread (7%) |
|
SIMMER_MIN_DAYS |
3 | Min days until resolution |
|
SIMMER_MAX_POSITIONS |
8 | 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
股票市场与IPO交易员
这是一个模板。
默认信号是基于关键词的市场发现,结合基于信念的仓位规模和equity_bias()——两种无需任何外部API即可运作的结构性优势。
该技能处理所有底层工作(市场发现、交易执行、安全防护)。您的智能体提供阿尔法收益。
策略概述
股票预测市场是独特的:它们与世界上最深入、最量化的金融市场并行运作。优势不在于比华尔街更好地预测市场——而在于专业数据(盈利基准率、期权隐含波动率、期货走势)与Polymarket散户之间存在滞后。两种结构性优势可以干净地叠加:
- 1. 盈利基准率修正——股票市场中最不为人知的统计数据:标普500公司在大约73-75%的情况下超出分析师一致预期的每股收益,这一比例跨越多个经济周期持续存在。大型科技股(NVDA、AAPL、MSFT、META、GOOG、AMZN)超出预期的比例约为80-85%。散户将盈利超出预期的市场定价为大约50-50。这20-30个百分点的差距是每个财报季都会重新出现的结构性优势。
- 2. 宏观日历时机滞后——标普500期货24/7交易。当CPI公布、非农数据发布或FOMC讲话时,期货会立即重新定价。Polymarket指数阈值市场需要20-60分钟才能跟上,尤其是在盘前时段。季度初月份(1月、4月、7月、10月)具有最大的宏观催化剂密度——GDP初值预估、全面财报潮、FOMC决策和非农数据都在几周内相继落地。
信号逻辑
默认信号:基于信念的仓位规模与股票偏向
- 1. 发现Polymarket上的活跃股票和金融市场
- 根据与阈值的距离计算基础信念(边界处为0% → p=0/p=1时为100%)
- 应用equitybias()——市场类型修正 × 财报日历时机
- 仓位规模 = max(MINTRADE, 信念 × 偏向 × MAXPOSITION)——上限为MAXPOSITION
- 跳过价差大于MAXSPREAD或距离结算少于MINDAYS的市场
股票偏向(内置,无需API)
因素1 — 市场类型/盈利基准率
| 市场类型 | 乘数 | 结构性现实 |
|---|
| 大型科技股财报(NVDA、AAPL、MSFT、META、GOOG、AMZN、TSLA) | 1.25倍 | 2020-2024年持续约80-85%的超出率;散户定价为50-60%;英伟达连续7个季度超出预期 |
| 一般标普500盈利超出 |
1.15倍 | 跨越多个周期约73-75%的历史超出率;散户视为抛硬币;每个X会超出盈利预期吗?都是结构性的YES倾向 |
| 指数里程碑(标普500、纳斯达克、道琼斯达到X) |
1.15倍 | 期货市场是24小时参考;Polymarket滞后宏观催化剂20-60分钟;盘前时段尤其可利用 |
| 股息/回购/股票拆分 |
0.90倍 | 存在一些内幕买入信号,但公司决策时机确实不确定 |
| 按日期IPO/IPO估值里程碑 |
0.85倍 | 窗口驱动;S-1文件到定价的间隔高度可变;银行家激励占主导 |
| 按日期市场崩盘/回调/熊市 |
0.75倍 | 最可靠的高估类别;崩盘虽引人注目但在任何特定窗口中很少见;VIX飙升时散户锚定最坏情况,而均值回归更可能发生 |
| 轧空/模因股里程碑 |
0.65倍 | 纯粹的社会协调;需要特定的空头流通数据、借券利率飙升、协调买入——这些都无法从问题文本中预测 |
崩盘高估规则——标普会在[日期]前下跌20%吗?在Polymarket上几乎总是被高估。每次VIX飙升后散户的恐惧锚定导致这些市场以15-30%的价格交易,而任何特定3个月窗口内20%以上回撤的实际基准率要低得多。2008年、2020年和2022年的生动可得性使散户在特定窗口的崩盘市场上系统性地悲观。无论当前概率如何,将所有崩盘/熊市问题降低至0.75倍。
超出率规则——分析师预估被故意设定为可被超出。公司保守地引导预期;分析师调整模型以匹配指引;管理层压低预期是经过记录、跨越数十年的做法。73-75%的总体超出率并非偶然——它是结构性的。每个定价低于50%的X会超出盈利预期吗?市场几乎肯定被错误定价,除非该公司有特定的记录在案的未达预期历史(例如,零售、生物技术审批前)。
因素2 — 财报日历时机
| 条件 | 乘数 | 原因 |
|---|
| 盈利类问题 + 旺季(1月、2月、4月、5月、7月、8月、10月、11月) | 1.20倍 | 最大信号密度:最新的分析师预估、当前的公司指引、实时期权隐含波动率 |
| 盈利类问题 + 淡季(3月、6月、9月、12月) |
0.85倍 | 稀疏的预公告;过时的预估;期权波动率压缩;基准率优势噪音更大 |
| 指数/宏观问题 + 季度初月份(1月、4月、7月、10月) |
1.10倍 | GDP初值预估 + 全面财报潮 + FOMC + 非农数据全部落地;最大宏观催化剂密度 |
组合示例
| 市场 | 类型乘数 | 日历乘数 | 最终偏向 |
|---|
| 英伟达会超出第三季度盈利预期吗?——10月 | 1.25倍 | 1.20倍(旺季) | 1.40倍上限 |
| 标普500会在年底前达到6,000点吗?——1月 |
1.15倍 | 1.10倍(季度初) |
1.27倍 |
| 苹果会超出第一季度盈利预期吗?——3月 | 1.25倍 | 0.85倍(淡季) |
1.06倍 |
| 到12月会发生市场崩盘吗? | 0.75倍 | 1.0倍 |
0.75倍——始终持怀疑态度 |
| GameStop轧空到100美元? | 0.65倍 | 1.0倍 |
0.65倍——接近底线 |
| 亚马逊今年会IPO一个子公司吗? | 0.85倍 | 1.0倍 |
0.85倍 |
监控关键词
标普500、道琼斯、纳斯达克、股票市场、牛市、熊市、
市场崩盘、回调、IPO、盈利、营收未达预期、超出预期、
伯克希尔、沃伦·巴菲特、苹果盈利、特斯拉盈利、
英伟达盈利、股票拆分、回购、股息、轧空、
历史新高、市值万亿、指数再平衡、每股收益超出预期、
盈利惊喜、指引上调、营收超出预期、超出预估、
CPI、通胀、非农就业、NFP、美联储利率、FOMC、
衰退、VIX、波动率、熔断机制
混音信号思路
- - 雅虎财经期权链:免费非官方API提供隐含波动率和期权隐含的盈利波动——将期权隐含的概率区间与Polymarket上盈利超出/未达预期市场的价格进行比较;对于中型公司,差距始终在15-25%
- CBOE VIX数据流:VIX水平和期货期限结构——当VIX飙升时,崩盘市场被高估;当VIX期限结构倒挂时,指数阈值市场的宏观催化剂时机信号
- SEC EDGAR 8-K文件:实时盈利发布在媒体报道之前到达EDGAR——盈利结果在Polymarket重新定价前几分钟就在EDGAR上公开
- CME FedWatch:来自联邦基金期货的美联储利率概率——直接输入美联储会降息/加息吗?市场;比Polymarket散户定价精确得多
安全与执行模式
该技能默认为模拟交易(venue=sim)。仅使用--live标志进行真实交易。
| 场景 | 模式 | 财务风险 |
|---|
| python trader.py | 模拟(sim) | 无 |
| 定时任务/自动化 |
模拟(sim) | 无 |
| python trader.py --live | 实盘(polymarket) | 真实USDC |
autostart: false和cron: null——在您在Simmer UI中配置之前,没有任何内容会自动运行。
所需凭证
| 变量 | 必需 | 备注 |
|---|---|---|
| SIMMERAPIKEY