Acadian employees in conference room


The mandate of Acadian’s research group is the continuous enhancement of our forecast models and our clients’ investment results through rigorous idea generation and ongoing refinement of existing frameworks.

  • We believe in a diversified and scientific approach to innovation.
  • We consider a wide range of possibilities in an effort to uncover, refine, and integrate enhancements to our investment process. 
  • We focus on optimal portfolio implementation, a function which includes a dedicated portfolio analytics team whose mandate is to more effectively transform alpha forecasts into portfolio holdings that maximize realized information ratios. 

Four Research Categories

Strategy Focus

Some research relates to the exploration of alternative investment strategies. These efforts have led our team into areas of interest differing from, but often related to, our investment model. Examples include Managed Volatility, Long Short, and Multi-Asset Class strategies.

Signal Generation

We devote much of our research to signal generation – identifying characteristics and attributes that seek to predict returns for individual companies, segments, and markets. These research initiatives are categorized according to bottom-up and top-down elements. In addition to looking for new signals, we also devote a great deal of time and resources to enhancing our existing signals.

Signal Consumption

The process of utilizing signals to construct portfolios is a critical area of research.  Given the importance of the optimization process and the impact of real-world frictions, it is critical that these two areas work closely together to ensure that we capture the optimal blend of exposures after accounting for risk, costs, and portfolio restraints.

Process Enhancements

In addition to research related to factors and portfolio construction, we also seek to constantly improve the manner in which we conduct research. These efforts have led to the development of an open architecture supported by a robust data infrastructure, uniform programming languages, expanded backtest environment, dynamic analytical tools, and multiple forms of attribution. 

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