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What does the optimisation replication method do?

It uses a sophisticated computer modelling technique to find a representative sample that mimics the broad characteristics of the tracked index.

It costs more to implement than full replication

Optimization replication builds a tracking portfolio by solving a mathematical model to approximate the index, usually using a smaller set of securities with carefully chosen weights to match the index’s risk and return characteristics while meeting practical constraints like liquidity and turnover. The reason this statement is the best answer is that the method relies on sophisticated modelling, data inputs, and ongoing re-optimization to maintain a close track to the index. Those added requirements—developing and running the model, validating its assumptions, and rebalancing as markets move—tend to push implementation costs higher than simply buying all index constituents in their exact weights, which is full replication. It’s not about using swaps (that would be a synthetic approach) and it doesn’t require tracking every constituent; the aim is to reproduce exposure efficiently with a subset, even if that comes with higher modelling costs.

It relies on swaps with a counterparty

It requires tracking every constituent

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