什么是 Kalshi Econ Bin Sum Trader？

Kalshi Econ Bin Sum Trader 是为 Openclaw Skills 设计的专业代理，旨在利用预测市场中的结构性低效。在诸如 CPI、GDP 或失业率等区间 bin 市场中，结果是互斥的，这意味着总概率在数学上必须等于 100%。该技能坚控这些市场中偏离该总和的情况，识别定价最错误的 bin，并执行交易以捕捉套利边缘。它为开发者提供了一个强大的模板，用于实施复杂的经济策略，而该技能则负责处理底层的市场发现和执行工作。

下载入口:https://github.com/openclaw/skills/tree/main/skills/diagnostikon/kalshi-econ-bin-sum-trader

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

Kalshi Econ Bin Sum Trader 应用场景

• 当总市场价格偏离 100% 的数学约束时，对通货膨胀 (CPI) 区间 bin 市场进行套利。
• 在 Kalshi 上自动对定价错误的经济数据 bin 进行高频检查。
• 实施一种依赖于纯套利数学而非主观预测的无模型交易策略。
• 利用 Openclaw Skills 管理各种互斥结果集（如 GDP 或失业率报告）的风险。

1. 该技能发现并分组属于同一经济事件的特定 CPI bin 市场。
2. 它计算组内所有市场价格的总和，以检查是否偏离 100% 的基准线。
3. 如果偏差超过配置的总和容差，该技能将归一化价格以确定每个结果的公平概率。
4. 它通过寻找归一化公平概率与当前市场价格之间的差异来计算每个 bin 的边缘（edge）。
5. 代理根据相对于总偏差的信心度定价来确定最佳交易规模。
6. 它通过 Simmer SDK 执行交易，在敲定交易前对滑点和流动性进行安全检查。

Kalshi Econ Bin Sum Trader 配置指南

要安装此技能，请使用以下命令：

clawhub install kalshi-econ-bin-sum-trader

您必须在环境或 .env 文件中设置以下环境变量：

• SIMMER_API_KEY：您的交易授权凭据。
• SOLANA_PRIVATE_KEY：用于实时交易的 Base58 编码 Solana 私钥。

默认情况下，该技能在 dry-run 模式下运行。要执行实时交易，请使用 live 标志：

python trader.py --live

Kalshi Econ Bin Sum Trader 数据架构与分类体系

该技能通过环境变量和特定于市场的元数据的组合来管理数据。数据组织包括：

name: kalshi-econ-bin-sum-trader description: Trades CPI range bin markets on Kalshi using the constraint that mutually exclusive bins must sum to ~100%. Normalizes and trades the most mispriced bin when deviation exceeds tolerance. Requires SIMMER_API_KEY and simmer-sdk. metadata: author: Diagnostikon owner: Diagnostikon version: "1.0.0" displayName: Kalshi Econ Bin Sum Trader difficulty: intermediate homepage: "https://simmer.markets/skills" repository: "https://github.com/SpartanLabsXyz/simmer-sdk" requires_env: "SIMMER_API_KEY" requires_pip: "simmer-sdk" default_mode: "paper" live_flag: "--live"

Kalshi Econ Bin Sum Trader

This is a template.
The default signal uses the fundamental constraint that mutually exclusive outcome bins must sum to 100% -- remix it with Bayesian priors, consensus forecasts, or cross-event correlation models.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

CPI range bin markets on Kalshi price each outcome bin independently. Since exactly one bin must resolve YES, the probabilities must sum to 100%. When the market sum deviates beyond tolerance, at least one bin is mispriced. This skill normalizes the distribution and trades the most mispriced bin.

Key advantages:

• Mathematical certainty -- bins MUST sum to 100%, any deviation is a guaranteed mispricing
• No forecasting needed -- the strategy is model-free, relying purely on arbitrage math
• Self-correcting -- as the sum approaches 100%, signals disappear (no stale trades)
• Works across any bin-style market -- CPI, GDP, unemployment, any mutually exclusive set

Signal Logic

Bin Sum Normalization

1. Group CPI bin markets by event (e.g., "March 2026 CPI")
2. Sum all bin prices in the group
3. If |sum - 1.0| > sum_tolerance, normalize: fair_prob = price / sum
4. Compute edge per bin: edge = fair_prob - market_price
5. Trade the bin with the largest absolute edge

Example

Conviction-Based Sizing

• conviction = min(|edge| / deviation, 2.0) / 2.0
• size = max($1.00, conviction * MAX_POSITION_USD)
• Larger edge relative to total deviation = larger position

Remix Ideas

• Cross-event sum: Apply same logic to GDP, unemployment, or Fed rate bins
• Consensus prior: Weight normalization toward consensus CPI forecasts
• Multi-bin arbitrage: Trade multiple bins simultaneously for hedged positions
• Rolling rebalance: Re-run as market moves to capture dynamic mispricing

Risk Parameters

Installation & Setup

clawhub install kalshi-econ-bin-sum-trader

Requires: SIMMER_API_KEY and SOLANA_PRIVATE_KEY environment variables.

Cron Schedule

Cron is set to null -- the skill does not run on a schedule until you configure it in the Simmer UI.

Safety & Execution Mode

The skill defaults to dry-run mode. Real trades only execute when --live is passed explicitly.

The automaton cron is set to null -- it does not run on a schedule until you configure it in the Simmer UI. autostart: false means it won't start automatically on install.

Required Credentials

Tunables (Risk Parameters)

All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes.

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

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

Review the source before providing live credentials if you require full auditability.