What It Is
Mimicking Portfolio is an allocation method that replicates the performance and characteristics of a chosen benchmark or reference portfolio. The goal is to construct a model or portfolio that behaves similarly to the target index in terms of return, risk, and composition.
What It Does in Fincanva
Logic: Allocates capital in a way that minimizes the difference between the model’s performance and that of the benchmark
Simulation Behavior: During each rebalance, weights are adjusted to closely track the benchmark using optimization techniques
Computation: Solves a quadratic programming problem using a hybrid local search algorithm to match benchmark characteristics as closely as possible
Benchmark Selection: Users implicitly define the benchmark by choosing the investable universe or target index to mimic
Pros
Allows tracking of well-known indices or custom benchmarks
Useful for passive investing or performance comparisons
Helps build educational strategies to understand index behavior
Enables customization of benchmark-like strategies with additional controls (e.g. constraints)
Cons
Computationally intensive during rebalance
May not perfectly replicate the benchmark, especially if the investable universe differs
Does not necessarily optimize for alpha or returns
Requires good data on benchmark constituents and characteristics
Where You Can Use It
Portfolios: Not available
Models: Yes
When to Use It
Best for replicating the performance of an index or ETF
Useful for passive investment strategies with customized rules
Suitable when benchmarking custom model strategies against a market standard
Ideal for educational simulations to understand tracking error and benchmark design
Example If you want your model to replicate the S&P 500 index but only include a subset of large-cap stocks, the mimicking method will allocate weights across the selected assets to approximate the return and risk profile of the S&P 500.
Plan Access
Models: Available on Ultimate and Professional plans
Portfolios: Not available
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