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Kalshi Trader

Automated Kalshi prediction market trading bot. Sets up a fully automated trading system that scans markets every 15 minutes, researches opportunities using...
bobthemom987
未分类 clawhub v1.0.0 100000 Key: 需要
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概述

Kalshi Trader

Automated prediction market trading on Kalshi. Scans every 15 minutes, researches before every trade, reports daily via Telegram.

Setup (run once)

1. Install dependencies

pip install cryptography requests --break-system-packages

2. Store Kalshi credentials

mkdir -p ~/.kalshi && chmod 700 ~/.kalshi
nano ~/.kalshi/private_key.pem   # paste -----BEGIN RSA PRIVATE KEY----- block
chmod 600 ~/.kalshi/private_key.pem
echo "YOUR-API-KEY-ID-HERE" > ~/.kalshi/key_id.txt
chmod 600 ~/.kalshi/key_id.txt

Get your API key at: kalshi.com → Settings → API → Create Key

3. Deploy the bot

cp scripts/kalshi_bot.py ~/kalshi_bot.py
chmod 600 ~/kalshi_bot.py

4. Test connection

python3 ~/kalshi_bot.py test

5. Set up cron jobs (via OpenClaw cron tool)

15-minute scan (silent unless trade placed or exited):

  • Schedule: /15 *
  • Message: see references/cron-prompt.md

Daily summary (9am your timezone):

  • Schedule: 0 9 * with your timezone
  • Message: "Run python3 ~/kalshi_bot.py summary and send daily trading report with balance, open positions, recent trades, P&L, and fees paid."

Trading Rules

Entry criteria

Only place a trade if EV IRR ≥ 50% (post-fee):

edge = fair_value - (market_price + entry_fee)
EV IRR = (edge / (market_price + entry_fee)) × (365 / days_to_close)

Minimum: EV IRR ≥ 0.50 (50%)

Position sizing — Half Kelly

kelly_fraction = (edge / market_price) × 0.5
max_position = min(kelly_fraction × balance, 0.20 × balance)
contracts = floor(max_position / market_price)

Exit rule

Exit ONLY if current bid ≥ fair value estimate (net of exit fee).

  • Never use price-based stop losses — prediction markets resolve on facts, not on what other traders think
  • If price drops, research whether the underlying facts changed
  • Only exit early if: (a) price reached fair value, or (b) new evidence shows the outcome is unlikely

Research approach

Use web_fetch as primary research tool (no quota limits). Known data sources:

  • Gas prices: https://gasprices.aaa.com/
  • Trump actions: https://www.whitehouse.gov/presidential-actions/
  • Treasury yields: https://home.treasury.gov/resource-center/data-chart-center/interest-rates/
  • Bitcoin/crypto: https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd
  • Weather: https://wttr.in/CityName?format=3
  • Congress bills: https://www.congress.gov

Only use web_search for open-ended research where the URL isn't known upfront.

Bot Commands

python3 ~/kalshi_bot.py          # scan for opportunities
python3 ~/kalshi_bot.py summary  # print P&L summary  
python3 ~/kalshi_bot.py test     # verify API connection

Reporting format (include in every update)

  • 💰 Cash balance
  • 📦 Total position cost
  • 📈 Current market value of positions
  • 💹 Unrealized P&L
  • 💸 Total Kalshi fees paid
  • 🏦 Total portfolio value

API reference

See references/api.md for Kalshi authentication and endpoints.

Trade research workflow

See references/trade-research.md for finding and evaluating opportunities.

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-05-07 05:28 安全 安全

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