Trading Strategies
4 articles
AI Paper Trading: How to Test Any Strategy with Virtual Money
Paper trading runs your strategy with virtual money on live market prices, so you see how it behaves before real funds are involved. With AI agents the stakes changed: you are no longer rehearsing your own clicks, you are auditing an automated strategy end to end. Here is how to do it properly.
AI Stock Trading: How to Automate US Equities with an Agent on Alpaca
AI stock trading in 2026 means an agent that watches the market and executes your strategy through a brokerage API, not a chatbot giving picks. This guide shows how to build one for US equities on Alpaca with NickAI: describe the strategy in plain English, prove it on a paper exchange, then go live.
Mean Reversion in Crypto: An AI-Native Approach (2026)
Mean reversion, the idea that prices stretched too far from a moving average snap back, works better in crypto than in equities, but only inside specific regimes. The classical Bollinger / z-score implementations miss the regime question entirely. An AI-native version uses an LLM to classify the regime and swaps strategy accordingly. This is the architecture and the working code.
Market Making Bots in Crypto: A 2026 Guide
A market making bot quotes both sides of an order book, capturing the spread between bid and ask while managing inventory risk. In 2026 it is the most boring, well-understood strategy in crypto: outperformed in raw return by directional trading, but with a far better Sharpe ratio. This is the architecture, the math, and the working Python.