  The profitability of various investment styles in investment funds depends on
macroeconomic conditions. Market ecology, which views financial markets as
ecosystems of diverse, interacting and evolving trading strategies, has shown
that endogenous interactions between strategies determine market behaviour and
styles' performance. We present Evology: a heterogeneous, empirically
calibrated multi-agent market ecology agent-based model to quantify endogenous
interactions between US equity mutual funds, particularly Value and Growth
investment styles. We outline the model design, validation and calibration
approach and its potential for optimising investment strategies using machine
learning algorithms.
