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Market, alternative, and other data are available directly in Alpha Central. Technical and market data, fundamental data, consensus estimates & multiples, earnings distortion scores, factors, risk data, and more are integrated to view and manipulate external data alongside your assets.

There are several ways to make inputs to Alpha Central. Our Client Experience team can help you find which method works best for your team.  

1. Input data directly into Alpha Theory’s application.
2. Use our integration with Microsoft Excel, Excel Connect, to establish a bi-directional sync between your spreadsheets and our platform.
3. Use a flat-file to integrate with our API processes to push data to the platform.

We connect with your internal systems and vendors, pull data from Excel, and also maintain direct relationships with a wide variety of market and alternative data providers, including fund administrators, custodians, prime brokers, order management and execution management systems, trading, research, and accounting platforms,and technology providers. We consolidate data from these sources and, in some cases, perform calculations tomake the information more useful to our customers.

Yes. Alpha Central becomes your historical data store. While Alpha Theory performs analytics, clients also use our historical data to perform their own analytics.

Alpha Engine is designed to capture complexity. Users can build fully customizable confidence checklists that account for factors outside of expected return in their sizing process. The checklist can be made up of other qualitative measures like management team strength, research stage, or economic moat, and quantitative measures like ESG score or historical ROIC. The position-sizing logic is fully customized and configured by your team.

Unlike black box optimizers, Alpha Engine captures the complexities of how your fund invests with custom fund-level and tag-level parameters. Tags are fully customizable, but common tags include sectors, geographic regions, or themes. Leverage constraints on position size, liquidity, gross and net exposure, return hurdles, and more for optimal position sizes customized to your rules.

Our data science team provides clients with detailed historical analysis across a broad range of topics, including (but not limited to):  

• Ticker-level performance attribution
• Forecast accuracy
  
• Actual versus optimal sizing analysis
• Ticker correlation matrices
• Actual versus optimal performance

Our data science experts provide insights that are part of the feedback loop that helps you refine your investment
process to create better outcomes. Our team is dedicated to delivering analysis that helps managers improve and
generate more alpha.

Absolutely. Our Data Science team can perform a multitude of analyses on live position data, separate from the optimal position sizing framework. You can work directly with the data science team to collaborate on custom reporting and analytics that suit your specific needs.