Project: CILA
CILA (Computational Intelligence for Low-Frequency Assets) is an agentic AI model specialized in financial trading.
We are making CILA a solid Desk Quant:
- Backtest: Conducting a wide range of accurate backtests, primarily at a daily frequency.
- Portfolio Analytics: Performing portfolio construction, stress testing, and portfolio simulation tasks.
- Risk Management: Calculating risk measures on positions and portfolios.
- Fundamental Research: Gather market information from trusted news channels and sources to provide market updates and in-depth research.
- Economic Analysis: Monitor economic data releases and major economic events to support informed trading decisions.
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
- Robust portfolio optimization