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Quant Trading Post-Trade Analysis with Snowflake

Accelerate the search for alpha by unifying traditional and alternative (e.g., crypto/blockchain) data to backtest systematic strategies, capture market arbitrage, optimize execution algos, and manage risk. 

The Financial Services Data Cloud enables quant trading teams to focus on trade execution quality and generating alpha, instead of maintaining data pipelines across multiple silos. 
Seamless data onboarding, aggregation and sharing capabilities enable quant traders to quickly leverage real-time and historic pricing and execution data, along with other first-party and third-party data sets, to run queries, build algorithms, backtest, and power analytics and rules-based automation.

Why Snowflake?

Data Access and Sharing

Bring together significant volumes of data – from new alternative datasets to internal proprietary data – to power quant research & trading workloads.

Consistency Across Workloads & Teams

Build models to backtest systematic strategies, capture market arbitrage, and optimize execution algorithms without workload contention.

Scale and Performance

Lower data management TCO by removing the need for expensive, large and unscalable on-prem (e.g., tick) database technology.

Quant Trading

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