A prescription for the new PRIIPS RTSSeptember 29, 2016 - 08:41
The Commission is now looking to fix the RTS,
and there are suggestions that implementation may be delayed. We thought that
the aims of the Commission when they were developing RTS were completely
reasonable and think that the RTS can be fixed very easily. The RTS we propose
will be simpler, easier and will provide a useful guide for investors when
choosing one investment over another.
THE PROBLEM WITH THE OLD RTS
Parliament rejected the RTS primarily because they thought that it failed to
adequately describe the risk of an investment. Specifically, they were
concerned that the actual outcome of an investment could be significantly less
than the “what you may get back” in the unfavourable scenario. Implicit in this
criticism was the fact that the return in the unfavourable scenario was
positive too often. The EU parliament also criticised the lack of any sort of
that we have done supports the concerns of the EP. In over 60% of the
capital-at-risk PRIIPs we looked at the RTS unfavourable scenario would have
showed a gain when in fact there was an appreciable chance of loss:
While it is
naïve to think that the realised performance of a product should never be worse than the unfavourable
scenario result, we think the return in an unfavourable scenario should reflect
the entire bottom end of the returns that an investor may get, rather than the
best of that bottom end. We are advocates of a worst case based on a measure of
“Average Shortfall” rather than a line-in-the-sand measure like Value at Risk.
The aim of
the primary legislation is to create a KID that investors actually use to help
select products. We agree with the EP concerns and think the RTS was flawed in other
ways that rendered it almost useless as a tool for investors:
risk bands are so wide that they don’t usefully separate one investment from
are obvious problems having two different risk scales: those from the KIID
regulations for old funds, and the new PRIIPS scale.
PRIIPS volatility calculation is very insensitive to product features for products
with knock-in barriers; the volatility of a product with an 80% barrier will in
most cases be the same as the volatility of a product with a 50% barrier. Our
analysis shows that calculating volatility using the 97.5% VaR causes products
to fall into one of two groups: products where the chance of breaching the
barrier is very small, and all other products. For most products the 97.5% Var
is a scenario where even a very low barrier will been breached, so the
volatility for a product with a higher barrier will be the same as the
volatility of a product with a lower barrier. As a result, the volatility of
the product is in effect the risk of the underlying assets.
was not clear how to calculate the “what you may get back” values for products
that may mature early. In fact, it was not clear how the scenario calculations
should be carried out for PRIIPs with non-linear payoffs.
was no estimate of the expected return of a product. The 50th
percentile VAR is particularly misleading as a guide to the returns from
structured products: in many cases because of the asymmetry of returns it is
too flattering as a measure of the average return.
estimate of costs requires the calculation of the fair value of each product,
or for the issuer to publish an Issuer Estimated Value (IEV). There are obvious
problems with both: the IEV is a fudge, and the calculation of fair values with
any degree of accuracy requires significant investment and access to derivative
pricing that is not widely available.
that fixing the RTS is relatively simple. We support the use of a bootstrap
(sampling with replacement) to test products. All we suggest is that different
values are extracted from the test results:
- The 5yr historic base for
the data used to test products is too short, and gives unreliable results
(in the sense that a reanalysis a few months later will change the results
materially). A 10-year or even a 15-year base would be much better for structured
products and funds
- We would include a decimal
place in the MRM risk rating. There are significant differences between
the top and bottom limits of the volatility buckets. A decimal place would
offer much greater, and much needed granularity
- Rather than expanding the
volatility range for each risk category, it would be simpler to introduce
new categories. Category 7 could be capped at 40% volatility. Category 8
could be for products where volatility is between 40% and 80%, category 9
would be for products with more than 80% volatility. This would avoid the
problems that will occur if existing funds that benefit from the five year
exemption from PRIIPS are ranked using the KIID scale, and new PRIIPS use the
- We would show the market
risk and credit risk separately.
- For products based on new underlying
assets and where there is insufficient price history available the testing
can use an appropriate benchmark or proxy asset, although
the RTS needs to specify a standard methodology for choosing one
- Volatility should be based on average
shortfall not Value at Risk
- The illustration of what
you get back should be based on the distribution of annualised returns. It
would be simple to show the chances of the annualised return falling into
certain set buckets, say 5% wide.
- We would specifically show
the chance and average return from scenarios where the investor either
makes or loses money.
- The “worst case” value
should be the average of the worst 10% of the returns from the stress
- For many investors risk is
based on losing money. It would be easy to show the chance of a negative
return, and the average of all negative returns
think that there should be a measure of the average CAGR or IRR of each product
from the stress test
are two ways to approach the estimation of costs.
Issuers are required to publish their gross
margin or fair value as they are in the USA and Germany, or
The fair value is calculated from publically
available data and from derivative prices and data that are provided by each
issuer and collated centrally.
complexity issue can be resolved through a simple additive scoring system. The
FCA proposed a way that structured deposits can be scored. This type of features
based score can be extended to all products.
RTS can be produced using the same process that providers will have developed
for the rejected RTS. It will offer investors a simple way to compare products
and answers three important questions:
risks do I face?
volatile are the returns?
is the expected “worst case” return?
creditworthy is the issuer?
return might I get?
is the average return, and how does this compare to the benchmark assets?
likely am I to make money, and if I make money how much might I make?
likely am I to lose money, and if I lose money what is the average return I
costs, fees and other charges am I paying?
David has been involved in equity derivatives, equity structuring and the structured product market for over 25 years. Before setting up CUBE in 2013 David worked at J.P. Morgan, Barclays and RBS. David has worked with and for retail product providers, discretionary managers and institutional investors.