r.Team assist with common quantitative strategies which include:

1. Statistical arbitrage: Exploiting pricing inefficiencies between related securities or markets.

2. Factor investing: Selecting securities based on specific characteristics or "factors," such as value, momentum, or quality.

3. Trend following: Identifying and following persistent price trends in markets.

4. High-frequency trading: Executing a large number of trades in fractions of a second to capture small price discrepancies.

5. Machine learning and artificial intelligence: Applying advanced computational techniques to uncover complex patterns and make predictions in financial markets.

Quantitative strategies are used by a wide range of market participants, including hedge funds, institutional investors, and trading desks at investment banks. While these strategies can be effective in generating returns, they also come with risks, such as model risk (when models fail to accurately predict market behavior), data quality issues, and the potential for significant losses during extreme market events.