Advances in computational technology, introduction of new benchmarks and trading tools, and a decline in the cost of computing power have all driven changes in the techniques of portfolio management over the past decade.
All active portfolios can be decomposed into an active component and a passive (benchmark replicating) component.
Dynamic factor models are used to build portfolios based on tactical exposure to factors such as equity style, industry or geographic location, macroeconomic factors, or microeconomic factors.
Factor models have a close relationship with theoretical asset pricing models.
Dynamic factor strategies attempt to eliminate sources of security-specific risk.
Portfolio managers use a variety of methods for modeling the time series variation in factor exposure, including relative value spreads, momentum and trends, as well as other combinations.
Both value and momentum strategies have been shown to be effective for security selection within particular markets as well as selection across markets (e.g., sectors or countries).
Implementation of dynamic factor approaches to portfolio management has been facilitated by new developments in modeling, benchmarking, computing power, and trading technology.
Many dynamic factor models may be implemented at the macro level—via direct exposure to one or more factors—or at the micro level through factor-based security selection models.
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