Alpha Engine

A Disciplined Process to Sizing Positions Improves Returns

Play By Your Rules

Alpha Engine is a customizable rules engine built to increase discipline around position sizing. We help investment managers translate sizing criteria into custom rules to generate optimal position sizes aligned with the firm’s investment strategy.

  • Make your intuition and implicit rules explicit with custom criteria
  • Customize liquidity, drawdown, sector exposure, risk, and other rules
  • Create a consistent and repeatable sizing process to remove bias

Put Your Research to Work

Alpha Engine is powered by critical inputs like price targets and conviction levels combined with investment manager custom rules to produce optimal position sizes. Plus, users get insight into the freshness and coverage of their data.

  • Leverage fundamental research and external data to size positions
  • Update optimal position sizes automatically as data changes
  • Choose from dozens of custom fields to leverage inputs most important to the firm

Maximize Your Return Potential

Alpha Engine compares optimal position sizes against the actual portfolio data in real time and identifies discrepancies to maximize expected return. These actionable insights help capture alpha already hidden in the portfolio.

  • Compare optimal position sizes against the portfolio in real time
  • Take action to correct position size discrepancies to maintain an optimized portfolio
  • Capture alpha already in the portfolio with position sizing that maximizes expected return
"Alpha Theory provides me with the platform I need to make better timing and sizing decisions that have yielded better performance. As a result, Alpha Theory is now an integral part of my daily investment process.

— Long/Short Hedge Fund Portfolio Manager/Founder

Frequently Asked Questions

How do we account for items outside of our expected return forecasts that impact sizing decisions?

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.

Sizing based purely on our fundamental research is great, but how do we account for other sizing constraints in our portfolio?

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.