Automated prediction market trading on Kalshi. Scans every 15 minutes, researches before every trade, reports daily via Telegram.
pip install cryptography requests --break-system-packages
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
cp scripts/kalshi_bot.py ~/kalshi_bot.py
chmod 600 ~/kalshi_bot.py
python3 ~/kalshi_bot.py test
15-minute scan (silent unless trade placed or exited):
/15 *Daily summary (9am your timezone):
0 9 * with your timezonepython3 ~/kalshi_bot.py summary and send daily trading report with balance, open positions, recent trades, P&L, and fees paid."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%)
kelly_fraction = (edge / market_price) × 0.5
max_position = min(kelly_fraction × balance, 0.20 × balance)
contracts = floor(max_position / market_price)
Exit ONLY if current bid ≥ fair value estimate (net of exit fee).
Use web_fetch as primary research tool (no quota limits). Known data sources:
https://gasprices.aaa.com/https://www.whitehouse.gov/presidential-actions/https://home.treasury.gov/resource-center/data-chart-center/interest-rates/https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usdhttps://wttr.in/CityName?format=3https://www.congress.govOnly use web_search for open-ended research where the URL isn't known upfront.
python3 ~/kalshi_bot.py # scan for opportunities
python3 ~/kalshi_bot.py summary # print P&L summary
python3 ~/kalshi_bot.py test # verify API connection
See references/api.md for Kalshi authentication and endpoints.
See references/trade-research.md for finding and evaluating opportunities.
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