The PRIIPs, ‘Packaged Retail and Insurance-based Investment Products’ regulation discussed handled in this blog relates to Category 2 PRIIPs. Category 2 PRIIPs is defined as ‘unit-linked insurance-based investment product’ e.g., pension funds and investment funds.
The purpose of PRIIPs, is to provide the bespoke funds with a Key Information Document (KID) as additional information to clients. KIDs basis data consists of performance return and costs.
One of the challenges with PRIIPs is how to interpret the legislation. It is crucial for a UCITs provider to be competitive compared to other similar providers. Hence it is important to set up groups across vendors, where SMEs can discuss and align the interpretation and definition of key figures and methods.
Another key consideration is in which system to develop the report, and how the final and or intermediate data should be stored e.g., in a data warehouse. It is an advantage to integrate the solution to an existing platform, since you will not have to reconcile to an external system, in addition, there will be in-house knowledge of the system and database.
In September 2021, the EU amended the regulation, which had an impact on performance scenarios. This meant that the performance scenarios changed from using one principle, Cornish Fisher distribution, to operate with two different principles.
The new principle uses performance returns more directly and consists of two batches of performance returns:
The first batch consists of 5 years rolling average, for recommended holding period (RHP) of 5 years, which requires 10 years of prices. This can be a challenge, as not all funds will have historic market data for 10 years. In this case prices can, if possible, be estimated using a similar fund with 10 years of historic data.
The second batch consists of backwards accumulating performance return from execution date to minus 5 years (RHP = 5). It is not straight forward to obtain backwards accumulating return from a regular performance calculation. This batch can advantageously be calculated in code / SQL, using daily returns from a performance calculation.
The second principle, Cornish Fisher distribution (CF) transforms a normal distribution to a distribution that takes skewness and excess kurtosis into account. The CF for PRIIPs calculates a stress scenario using daily performance return as input.
Figure 1. Skewness = 0 and kurtosis 0 corresponds to normal distribution (Bonyár, 2015).
The CF is an approximation of the quantiles of a probability distribution, using 3rd and 4th derived. Since CF is an approximation from a Gaussian (normal) distribution towards a non-Gaussian distribution, the skewness and kurtosis parameters will only coincide with actual kurtosis and skewness for small values of the CF skewness and kurtosis parameters (Maillard, 2012).
Maillard (2012) shows that output is valid for skewness parameters less than the absolute value of 2,5, the dependency of skewness- and kurtosis parameter leads to a kurtosis parameter value between 0 and 12. For outliers of the bespoke values, results might be misleading. This is a potential root cause; for EU to change the method for favourable, moderate, and unfavourable scenarios to a method with less complexity.
Cost Reporting & Definitions
Costs are reported separately in PRIIPs regulation, there are 3 years of data for Transaction cost and Ongoing cost and 5 years of data for incidental costs (e.g., performance fee). It is again advisable to agree definitions of cost with similar PRIIPs issuers in the market.
Historic costs, produced at the upstart of PRIIPs, should not be underestimated. Transaction costs consist of explicit cost and implicit cost. Explicit cost is direct transaction cost or other costs related to transactions. Implicit cost refers to the difference between the issued price and the market value of underlying securities. This cost can be obtained from vendors, or it can be estimated using spreads supplied by AFG. The spreads are defined for underlying asset classes. Calculation of the weighted average to reflect the underlying holdings is required.
We have extensive knowledge and experience of implementing PRIIPs regulation across investment managers and if you would like to speak to one of our experts, please contact us at firstname.lastname@example.org.
Blog author: Elise Christiansen, Senior Manager, Axxsys Consulting
Bonyár, Attila. (2015). Application of localization factor for the detection of tin oxidation with AFM. 10.1109/SIITME.2015.7342289.
Maillard, D. (2012) ‘A User’s Guide to the Cornish Fisher Expansion’, SSRN Electronic Journal [Preprint]. Available at: https://doi.org/10.2139/ssrn.1997178.