Build a Kalshi trading bot

How it works

1. 1
   Write or clone a strategy

   Implement the banger.Strategy interface in Python, or clone a public Kalshi strategy and configure it. Filter the universe by category (NFL, weather, economics) and time to resolution.

2. 2
   Paper-trade against live markets

   Run against real Kalshi market data with simulated fills, and watch orders, fills, logs, and P&L on the dashboard before risking capital.

3. 3
   Go live with hard limits

   Add your Kalshi API key and private key, set risk caps and a kill switch, and promote the same strategy to live trading.

A Kalshi strategy in ~25 lines

from decimal import Decimal
from banger import Strategy, signals
from banger.risk import RiskEnvelope
from banger.venues.kalshi import Kalshi


class UnderdogCatch(Strategy):
    name = "underdog_catch"
    venues = [Kalshi()]
    universe = signals.kalshi_markets(
        category="NFL", time_to_resolution_lt="6h"
    )
    risk = RiskEnvelope(
        max_position_usd=Decimal("75"), max_daily_loss_usd=Decimal("300")
    )

    async def on_market_tick(self, market, tick, ctx):
        if tick.yes_price and ctx.can_open_position():
            await ctx.place(self.venues[0], market, side="yes",
                            size=Decimal("50"))

Install with pip install bangertrades, then banger run strategy.py --paper.

FAQ

How do I build a Kalshi trading bot?

Install Banger with `pip install bangertrades`, write a strategy implementing the banger.Strategy interface (or clone one), then run `banger run strategy.py --paper` to test against live Kalshi markets. Add your Kalshi API key to go live.

Does Kalshi allow trading bots?

Yes. Kalshi offers a first-class trading API and supports automated trading. Banger connects with your own Kalshi API key and never custodies funds.

Is Kalshi legal in the US?

Yes. Kalshi is a CFTC-regulated US exchange and is legal for US persons, though some states restrict certain markets such as sports. Check current availability for your state.