Welcome to the home of the CAATS Project

 CAATS = Credit Arbitrage Algorithmic Trading System.

CAATS is:

• A developmental algorithmic trading system that drives relative value strategies involving securities from across the traded capital structure.
• Underpinned by Augmented Risk Analytics: a fusion of quantitative risk analytics and deep learning data science technologies, optimized for tactical risk decision making.

The CAATS Project has soundly achieved its two main objectives:

1. Create a trading algorithm to systematically identify and exploit valuation inconsistencies across a firms' traded capital structure - reflected in the prices of its' traded equity and credit derivatives - and consistently generate positive P&L with attractive returns across the market cycle.
2. Successfully demonstrate an application of Augmented Risk Analytics, creating an augmented, predictive risk-management environment with potential applications extending well beyond algorithmic trading.

CAATS employs neural-network based, unsupervised deep learning powered by outputs from Seven Streets’ C2E Risk and Valuation Engine: a proprietary analytics platform that generates consistent risk views across a firm’s traded capital structure, providing relative value insights across credit and equity capital markets.

On this website we discuss the CAATS algorithmic trading system and the C2E platform that supports it. We also document back testing results from the first generation of CAATS algorithm development, which span over a decade and clearly show CAATS performing favorably against the industry benchmark.