AI Tools for Trading
Practical tutorials applying LLMs and AI to trading, research automation, and data analysis.
AI Research Stack 2026: The LLM Tools Quant Developers Actually Run
Treat cloud LLMs, local models, RAG, agents, and GPU as one system. Route each job by data sensitivity, task shape, and how you will verify the output.
RunPod vs Vast.ai: Practical Comparison of Local LLM and GPU Rental for Backtesting
A hands-on comparison of RunPod and Vast.ai for GPU cloud use in local LLM development and backtesting infrastructure.
Automating Quant Research with Claude API: Practical Comparison with GPT-4
When integrating LLMs into a quant research workflow, which is more suitable: Claude API or GPT-4? This article compares both through real-world use cases and cost analysis.
Quant hardware from an RTX 4090 to a DGX Spark
An overview of environments for running local LLMs, backtests, and data pipelines across different budgets. Comparing GPU cards, Mac setups, AI supercomputers, and cloud options based on real-world usage.
Building a Market Data Pipeline Using Crypto Exchange APIs
This guide explains how to collect and automate market data such as OHLCV, funding rates, and order book data from Binance and Bybit APIs. The first step in quantitative research is data.
Local LLMs vs Cloud Models: Which Is More Advantageous in Quant Research Environments?
A comparison of model deployment strategies suitable for research and development environments from security, cost, inference speed, and workflow automation perspectives. The optimal choice varies depending on the situation.