Project: CILA

CILA (Computational Intelligence for Low-Frequency Assets) is the first generative AI model specialized in computational tasks for trading.

For our initial version, we aim to make CILA a solid Desk Quant:

• Backtest: Conducting a wide range of accurate backtests, primarily at a daily frequency, while also offering some intraday capabilities.
• Portfolio Analytics: Performing portfolio construction, stress testing, and portfolio simulation tasks.
• Risk Management: Calculating risk measures on positions and portfolios.

Our ultimate goal is to develop CILA into a Quantitative Researcher with advanced quantitative skills, including:

• Full-scale human-AI interaction for building quantitative signals
• Complex trading signal construction
• Grid search in signal parameter space
• Transaction cost analysis
• Portfolio optimization