Non-linear mixture of asset return models

Sandrine Tobelem-Foldvari and Pauline Barrieu present a non-linear methodology that combines different asset return models in order to define the preferable portfolio allocation when the investor is averse to model ambiguity. This method offers robustness, tractability and simplicity to investors requiring flexible and easy-to-implement blending of different ambiguous models

market volatility

When quantitatively determining a portfolio’s asset allocation, a blend of different models’ outputs can be used. Traditional subjective expected utility (SEU) methods do so linearly, and as such cannot capture non-linear strategies used to guard against the uncertainty over how accurately a model reflects the  real-world distribution. For instance, it may be desirable to cap possible allocations to guard against models excessively overweighting a given asset, or to penalise the outliers when

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact or view our subscription options here:

You are currently unable to copy this content. Please contact to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

Most read articles loading...

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here