Flirting with Models

🧪 Research Library of Newfound Research

Tag: model risk

Estimating from Historical Data

Estimating from historical data requires many assumptions about similarity. Reducing the number of estimated parameters can control model risk.

Jumpy Models Part II: What we can do with jumps once we find them

If detecting jumps is not hard enough, we have to deal with them afterwards. Models must handle jumps in a way that does not introduce excess whipsaw.

Jumpy Models Part I: Why detecting jumps is important for asset allocation models

Detecting jumps in asset prices is important for robust parameter estimation, especially when estimating volatility.

Pricing for Model Risk

Even a well-constructed model is open to model risk. By including estimates of errors in a model, we can aim to reduce the probability of model failure.
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