Learn to Build Algorithmic Prediction-Market Trading Bots
Prediction markets are the fastest-growing regulated trading venue in the US — and the algorithmic edge is wide open. Algo Traders Club trains developers to build Python trading bots on Kalshi, with cross-venue work on Polymarket for arbitrage. CFTC-regulated, USD settlement, deterministic binary YES-NO contracts — ideal for quantitative modeling.
Start free with Kalshi Agent — a ~200-line Python Kalshi bot you can clone, run, and read in a single sitting. Graduate through three tracks: Operator (run a Kalshi bot 24/7), Quant (backtested strategies running live), and Builder (multi-strategy portfolios and agent orchestration).
The full bot operator journey — enter at any point
Three Tracks. One Quant's Career Path.
Track A — The Operator
The on-ramp. Ship a production Kalshi bot.
Build, deploy, and run a Python Kalshi trading bot 24/7. Auth (RSA-PSS), REST + WebSocket order-book streaming, risk management, dry-run-first. Graduate with a public GitHub repo + 14 days of live (paper or small-stake) data.
Standard tier · See Track ATrack B — The Quant
Build real strategies running live.
Statistical arbitrage / cointegration on correlated Kalshi contracts, NLP news-sentiment signals, implied-probability benchmarking, the Safe Compounder EV edge on mispriced NO-side contracts. Graduate with a documented, backtested strategy running live.
Premium tier · See Track BTrack C — The Builder
Multi-strategy portfolios. Cross-venue arbitrage. Agent orchestration.
Multi-strategy portfolios, multi-model LLM ensembles, cross-venue (Kalshi ↔ Polymarket) arbitrage engines, MCP-native agent orchestration. Cohort-based, capped enrollment.
The Algorithmic Opportunity Is Wide Open
Kalshi is a fully CFTC-regulated US exchange with USD settlement and binary event contracts — a clean quantitative surface. Most participants trade manually. The bots that ship first will define the category. ATC trains developers to build, backtest, and operate those bots with Python, the Kalshi API, and AI-assisted coding workflows.
CFTC
regulated
Fully regulated US exchange — USD settlement, US-accessible
Binary
contracts
Deterministic YES-NO settlement — ideal for quantitative modeling
Wide
open edge
Stat arb, sentiment, market-making — most edges unautomated
Start with Kalshi Agent
Clone something tiny that works. Read every line. Then graduate through the three tracks.
Clone it
git clone the Kalshi Agent repo, uv sync, then configure your .env.
Run it
Execute uv run python kalshi_agent.py. Dry-run by default, places a test trade, logs to SQLite.
Read it
The codebase fits on one screen: Kalshi API calls, a SQLite logger, and a strategy function. No magic.
Become a Bot Operator and Quant
From minimal Kalshi bot to live strategies: Foundation plus three tracks that map to a quant / bot operator career on prediction markets.
Track A — Operator
- Kalshi REST + WebSocket API and dry-run discipline
- 24/7 DigitalOcean deployment with tmux/screen
Track B — Quant
- Statistical arbitrage and cointegration on correlated Kalshi contracts
- NLP sentiment signals and implied-probability benchmarking
- Graduate with a documented, backtested strategy running live
Track C — Builder
- Multi-strategy portfolio management
- Kalshi ↔ Polymarket cross-venue arbitrage engines
- MCP-native multi-model LLM agent orchestration
Is This Course For You?
This is an intermediate course designed for developers ready to level up. It's a perfect fit if you are...
You're a Fit If...
- A developer or quantitative builder with 2+ years of experience (Python preferred)
- Excited about Kalshi, prediction markets, and building algorithmic trading bots
- Someone with a "build-first" mentality who wants to operate real agents, not just backtest ideas
- Ready to pivot into quant / bot operator work on regulated prediction markets
This Might Not Be For You If...
- You are completely new to coding
- You are looking for a "get rich quick" scheme
- You are looking for specific financial advice
- You are uncomfortable with managing API keys and trading risk
Your Edge on Kalshi
Join the community defining algorithmic trading on regulated prediction markets.
High-Performance Trading
Explore automated strategies on Kalshi event contracts and cross-venue arbitrage with Polymarket. Our strategies leverage pykalshi and local order-book mirroring to maximize your edge.
Developer-First Toolkit
Our Kalshi API, pykalshi, and PMXT playbooks, Claude Code operator workflows and SQLite trade logging and observability patterns help you build, test, and operate sophisticated trading agents with ease.
Career Pivot to Trading x AI
Join a community at the forefront of the convergence of AI, prediction markets, and autonomous trading agents. Develop the skills to build a career as a bot operator who runs agents with Claude Code and scales them across Kalshi and beyond.
From Code to Capital
A simple, powerful workflow for deploying autonomous Kalshi trading bots and operating them with Claude Code or Cursor.
- 1
Develop Your Strategy
Use Python and the Kalshi API to define your trading logic:
- Authenticate with RSA-PSS keys — REST for orders, WebSocket for order-book streaming
- Implement market making, statistical arbitrage, and sentiment-driven strategies
- Instrument your strategy for observability — SQLite logs, health endpoints, and structured JSON output
- 2
Deploy Your Agent and Operate It with Claude Code
Securely run and manage your trading bots:
- Deploy to a DigitalOcean droplet (or any VPS) with SSH access and your repo checked out
- Give Claude Code
CLAUDE.md/SKILL.mdcontext, then use it to start, stop, and monitor your bot from the project directory - Trade and operate bots 24/7 on Kalshi with full autonomy
- 3
Monitor & Scale Your Agents
Observe and optimize your bots with production-grade discipline:
- Track trading performance and PnL from SQLite history and CLI JSON output
- Fine-tune strategy parameters using analytics, metrics, and anomaly detection
- Scale position sizes, Kelly sizing, and the number of agents you operate confidently
Strategy Archetypes for Prediction Markets
Statistical Arbitrage
Cointegration on correlated Kalshi event contracts.
NLP Sentiment
News-sentiment signals driving implied-probability trades.
Cross-Venue Arb
Kalshi ↔ Polymarket price discrepancies.
Market Making
Provide liquidity on binary YES-NO contracts.
Safe Compounder
EV edge on mispriced NO-side contracts.
Why Kalshi: CFTC-regulated, USD settlement, US-accessible, deterministic binary-contract settlement — ideal for quantitative modeling.
Meet Your Coach
Fodé Diop aka Bot Mechanic
I'm not just a teacher; I'm a builder and founder. As the founder of Nexwave.xyz and Algo Traders Club, I build and operate algorithmic prediction-market trading bots on Kalshi — from the minimal Kalshi Agent starter to production quant strategies running live. Operators in the community run the stack with Claude Code on their own servers: SSH in, give the agent your project context, and operate with a real permission model. I've codified what works into an open-source-first curriculum designed to accelerate your path from developer to quant / bot operator. My goal isn't just to teach you to code — it's to teach you how to build, operate, and scale real trading systems on regulated markets. Let's build together.
Join the Conversation
Connect with developers building Kalshi trading bots, share strategies, and get real-time support from the community and core team. Start free with Kalshi Agent, then pick your track in Skool.
Ready to Build Your First Bot?
Join the community training developers from a free Kalshi Agent bot to live algorithmic prediction-market strategies on Kalshi. Foundation plus Operator, Quant, and Builder tracks.
Start Trading