Our solution uses network science to quantify the complex connections, interactions, and influences in private markets, enabling us to identify patterns and dependencies not apparent from traditional benchmark analysis. We enable asset allocators to evaluate fund managers across multiple dimensions and the most relevant peer groups for new insights into manager behavior.
Approach to creation to be discussed. Similar to the “Automate” section, the graphic would use light animation and color to direct the eye of the viewer. In this case though, the graphic would show movement from a single dot (like a node on a graph), then the same dot on a vertical line of other dots in uneven distribution, then those dots going into a small network (still keeping the first dot highlighted), and then that small network going into a large network of multiple, loosely connected small networks (still highlighting our dot and the small network within the larger entity).
Our solution puts past investment decisions into context by aligning various market data sources around past events.
Our solution uses machine learning to place fund managers and their performance in the context of the most relevant peer communities and compare community attributes among all in the market
Our solution incorporates the market’s network features to deliver learned metrics across multiple dimensions of performance and manager behavior.
Our solution enhances our understanding of complex systems like private markets by analyzing the relationships among firms with external influences like economic and market environments.
Our solution puts past investment decisions into context by aligning various market data sources around past events.
Our solution uses machine learning to place fund managers and their performance in the context of the most relevant peer communities and compare community attributes among all in the market.
Our solution incorporates the market’s network features to deliver learned metrics across multiple dimensions of performance and manager behavior.
Our solution enhances our understanding of complex systems like private markets by analyzing the relationships among firms with external influences like economic and market environments.
Our solution puts past investment decisions into context by aligning various market data sources around past events.
Our solution uses machine learning to place fund managers and their performance in the context of the most relevant peer communities and compare community attributes among all in the market
Our solution incorporates the market’s network features to deliver learned metrics across multiple dimensions of performance and manager behavior.
Our solution enhances our understanding of complex systems like private markets by analyzing the relationships among firms with external influences like economic and market environments.
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