kalshi-trader

# 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 ```bash pip install cryptography requests --break-system-packages ``` ### 2. Store Kalshi credentials ```bash 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 ```bash cp scripts/kalshi_bot.py ~/kalshi_bot.py chmod 600 ~/kalshi_bot.py ``` ### 4. Test connection ```bash 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 ```bash 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.