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Structured Products: Performance, Costs and Investments


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This paper analyzes structured products with a focus on the Swiss market. Empirical results for these products’ five major categories are presented, along with case studies and a general discussion. The paper addresses three main questions: How did structured products perform in the period starting in the Great Financial Crisis 2008 until 2014? The study shows that 80% of all issued products have a positive performance. What are the costs for investors at issuance? How can structured products be used? Several case studies distinguish investments in normal market conditions from event-driven investments made when markets are under stress. A main focus is on the SNB and ECB decisions of January 2015: the removal of the EUR/CHF cap and the introduction of negative CHF interest rates, and the decision to apply a program of quantitative easing in the eurozone, respectively.
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White Paper Structured Products: Performance, Costs, and Investments
SFI White Papers
Structured Products
Performance, Costs and Investments
Dietmar Maringer, University of Basel
Walter Pohl, University of Zurich
Paolo Vanini, Zürcher Kantonalbank
June 2015
JEL classification: G10, G13, G14, G19, D24
Keywords: Structured Products, Costs, Performance, Investor Behaviour, Event Driven Investments
This paper analyzes structured products with a focus on the Swiss market. Empirical results for
these products’ five major categories are presented, along with case studies and a general
discussion. The paper addresses three main questions: How did structured products perform in
the period starting in the Great Financial Crisis 2008 until 2014? The study shows that 80% of
all issued products have a positive performance. What are the costs for investors at issuance?
How can structured products be used? Several case studies distinguish investments in normal
market conditions from event-driven investments made when markets are under stress. A main
focus is on the SNB and ECB decisions of January 2015: the removal of the EUR/CHF cap and the
introduction of negative CHF interest rates, and the decision to apply a program of quantitative
easing in the eurozone, respectively.
White Paper Structured Products: Performance, Costs, and Investments
The editorial board thanks Dietmar Maringer, Walter Pohl, and Paolo Vanini for researching and
writing this White Paper and the peer reviewers for their helpful comments. The authors would
like to thank Derivative Partners AG and SIX Swiss Exchange & SIX Structured Products
Exchange for providing access to the relevant data for this study and the representatives of the
various banks for sharing background information for the investment case studies. Financial
support from the Swiss Structured Products Association is gratefully acknowledged.
Editorial Board
Claudio Loderer, Managing Director, SFI
Karl Schmedders, Head of Knowledge Center, SFI
Paolo Vanini, Head of Knowledge Transfer, SFI
Jean-Charles Rochet, Head of Research, SFI
Production Editor
Désirée Spörndli, Program & Relations Manager Knowledge Center, SFI
SFI White Papers
The SFI Knowledge Center publishes White Papers that give new stimulus to relevant topics, raise knowledge
standards, and contribute to ongoing discussions or initiate debate on matters of particular relevance to the Swiss
financial services industry.
Any opinions and views expressed in this document are those of the authors, and the authors alone are responsible
for the document’s content. The authors are responsible for the statistical methods selected and for the accuracy of
their data and calculations. The findings and conclusions presented do not necessarily represent the views of Swiss
Finance Institute, the institute’s staff, or the Swiss Structured Products Association. Swiss Finance Institute grants its
researchers unrestricted academic freedom and preserves the scientific independence of research and the
researchers' freedom of publication.
White Paper Structured Products: Performance, Costs, and Investments
Although structured products have attracted considerable attention over recent years, only few
empirical studies exist. This paper provides the first comprehensive and representative analysis
for Switzerland, based on more than 20,000 individual products and studying the period 2008
2014. The category warrants has been excluded from the study. Structured products come in
many different flavors: depending on their type, their payoff profiles can vary substantially.
Barrier reverse convertibles are by far the largest category in this study’s sample, followed by
tracker certificates, discount certificates, bonus certificates, and capital protection certificates.
Within each class, the products themselves are highly heterogeneous. First, their life-spans
range from just a few months to several years. Next, they trade in different currencies: slightly
more than half of the products studied here trade in CHF, another quarter in euros, and the
remainder in US dollars or other major currencies. Finally, the vast majority have either single
stocks or baskets of stocks as underlyings, but some have indices. The main conclusions are as
In most of the years considered, structured products performed well. In the period 2012
2014 some 80% or more of structured products generated positive returns. Depending on
the category and year, these products generated median returns of between 5% and 15%,
per annum implying that half of the products achieved this return or exceeded it. A
particularly successful year was 2009 in which most medians were in the range of 19% to
31%. In all of these years, equity markets also performed well. The years 2008, which saw
the onset of the most recent global financial crisis, and 2011the year of the European debt
crisissaw (large) drops in equity markets. These drops also affected the structured
products in this sample as they are mostly equity-based, and they too had negative medians.
A noticeable exception is capital protection products, where the impact of market
movements, on either side, is rather weak.
Estimating the costs of structured products is difficult as some cost components are difficult
to measure or are simply not known at issuance: Structured products are payment
promises, contrary to the performance promises of funds. The trader has to guarantee the
payment promise from issuance to the redemption date of the product. Therefore, the best
known value of the costs is at the termination of the product, and uncertainty about the
future value of risk parameters such as volatilities matters in terms of so-called risk
management costs.
Adding the risk management costs to the theoretical (model) price, which assumes that
there are no market imperfections (such as bid-ask spreads) and for which crucial price
parameters such as volatilities are constant, defines the fair price” for the product
components if they can be manufactured at zero production costs, if distribution is costless,
and if the issuer targets zero profit. Risk management cost figures are not available
publicly. An anonymous survey of major issuers in the Swiss market was used to estimate
these costs.
The authors refer to the difference between the issuance price and the fair price of
components as the total expense ratio (TER). The TER equals the sum of the net margin and
all production and distribution fees. A structured product’s TER mimics the TER of the fund
White Paper Structured Products: Performance, Costs, and Investments
industry, which provides a first step toward comparing these two different wrappings of
investment ideas. The empirical analysis for the period April 2012 to April 2015 finds the
following rounded median TERs (all figures are per annum): 0.3% for tracker certificates;
0.6% for capital protection certificates; 1% for bonus certificates; 1.4% for discount
certificates; and 1.7% for barrier reverse convertibles.
Swiss investors have an appetite for barrier reverse convertibles on stocks, and behavioral
motives appear to play a major role in investment decisions. A case study analyzes under
which conditions an investor will survivewith a high probabilitya full stock market
cycle without breaching the barriers.
Several additional case studies and illustrative examples distinguish investments in normal
market conditions from event-driven investments made when markets are under stress. A
main focus is on the SNB and ECB decisions of January 2015: the removal of the EUR/CHF
cap and the introduction of negative CHF interest rates, and the decision to apply a program
of quantitative easing in the eurozone, respectively. The case studies not only focus on
possible return expectations but stress how investors’ views are the key to investors
making a sound investment or non-investment decision. The studies show that investment
in structured products is based on a view of the markets contrary to that which prevails for
investments in funds, where a mixture between a model and market view often applies.
The events of January 2015 show that interventions can create many investment
opportunities in different asset classes: equity, fixed income, credit, and FX examples are
discussed in the setting of the aftermath of the SNB and ECB decisions. While some
opportunities can be persistent, others exist only for a short amount of time. To transform
such opportunities into investments two elements are necessary: structured products with
a short time-to-market and a precise mapping of the opportunity into liquid investments,
and investors who are fit to invest.
White Paper Structured Products: Performance, Costs, and Investments
Structured Products
Structured products are investments whose repayment value derives from the development of
one or more underlying assets. These underlyings are often combinations of traditional
securities such as equities, bonds, commodities, and one or more derivative components.
Derivative components are used to transform the risk-return characteristics of the traditional
products such that the specific needs of an investor are met. Structured product investments are
characterized by a short time-to-market, a payoff promise, liquid secondary markets, a short
value chain, and a well-defined investment objective. Structured products can, as any other
investment, be represented in the three dimensions of underlying, payoff or strategy, and
wrapping; see Figure 1.
Figure 1: The three dimensions of investment products.
Underlyings are classified according to their asset classes, such as equity or FICC (fixed income,
currency, and commodities) and by their number of constituent underlying valuesthat is to
say, single constituents, baskets, or indices. The last decade has shown that payoffs can be
classified, at the top level, into four types:
Linear payoffs, where arbitrary gains and losses are possible for investors. The payoff of the
products is tied to the price of an index or a basket of stocks. These products are called
“tracker certificates” (TCs).
The issuer of a capital protection payoff guarantees, at maturity of the product, a predefined
redemption value.
If markets are expected to move sideways, yield enhancement products are used. Barrier
reverse convertibles (BRCs) are the products preferred by Swiss investors.
For “warrants” the investor pays an option premium upfront. As previously stated, warrants
are not covered in this study.
Figure 2: Top-level payoffs.
Linear payoff
Capital protection payoff
Yield enhancement payoff
Warrant payoff
White Paper Structured Products: Performance, Costs, and Investments
The Swiss Derivative Map classifies all structured products using these categories at the top
level and also specifies a more detailed second level categorization.
The logic of the map is very
successful, and was also used as the basic input to the product classification at the European
The investment strategy of most structured products is passive and generally does not change
during the lifetime of the products, with tracker certificates (TCs) being the sole exception. TCs
can be passively or actively managed. Active strategies can be based on a mathematical rule that
describes the investment strategy during the lifetime of the product, or investment managers
can discretionally manage the underlying basket. These different approaches to management are
the same as those used in the fund industry: TCs are the structured product counterpart of
investment funds and ETFs. The type of wrapping chosen depends on the size of the investment,
tax issues, the investment restrictions of the investors, market access, and time-to-market
requirements. Hence, it might be optimal to wrap an economic investment idea as a structured
product, a mutual fund, an ETF, etc.
Table 1: Some characteristics of mutual funds compared to structured products.
Structured products
Long- or short-term and opportunistic trading
approach. Market views only.
Mass or tailor-made products starting from CHF 20,000
in investment size, or less.
Issuer risk. It can be mitigated using COSI or TCM
Short time-to-market in most cases.
Payment promise (“Zahlungsversprechen”).
There is a fifth category in the map, which will not be considered here.
COSI are structured products with a minimal counterparty risk. This protection is provided by means of a collateral
pledge. Investors thus profit from increased protection on the invested capital. This unique service is offered by SIX
Group. With TCMTriparty Collateral ManagementSIX Securities Services assumes responsibility for administering
exposures (pledged assets) and collateralizing them using assets of the same value (securities and cash).
White Paper Structured Products: Performance, Costs, and Investments
Low setup costs.
Life-cycle management is less developed.
Weaker formal setup; high quality secondary markets;
on balance sheet.
Appropriate for small and large investment sizes.
Over CHF 250 billion in Swiss securities accounts (SNB
statistic, 2015).
White Paper Structured Products: Performance, Costs, and Investments
Apple announced, on 9 March 2015, that their smartwatch portfolio would be launched in spring
2015. Just three days later Swatch announced their new smartwatch models that would compete
against their rivals from Silicon Valley. The theme was covered by all media as the final market
adoption of new, “intelligent” watches. Investors were looking for opportunities to invest in
companies with exposure to this theme.
How should one construct such an investment vehicle? In this scenario, time-to-market was
short, the patience of investors was close to zero, and potential issuers feared others would
serve investors first, so the only solution was a TC. To set up a fund with FINMA approval would
have taken several months. The first TC had its initial fixing on 20 March 2015, less than two
weeks after the first press announcement. The investor had a 100% participation on the
performance of a basket that contained 20 shares, not only from producers from the smartwatch
theme but also from key suppliers in this upcoming industry. While there was no room for an
investment fund to profit from the investment opportunity, funds can be a useful wrapper of the
investment idea as follows: Suppose that the investment is successful and that the invested
amount is increasing. A fund issuer could then benefit from the same economic concept by
launching a mutual fund. What is the rationale? First, if the invested amount is large then a fund
wrapper can be profitableit does not make sense to start a fund if the invested amount is not
larger than at least CHF 10 million. Second, a fund does not carry issuer risk, which is one of the
main reasons why some investors are not allowedor willingto invest in structured products.
The example shows that, for linear products, structured products and funds are in principle only
different wrappers of the same economic investment idea. The main differences between the
two are the maturity of the investment, the investment size, and issuer risk. It should be noted,
while this paper uses the term structured products throughout, the expressions structured
products and certificates are used synonymously.
To date there have been no comprehensive studies on the performance of structured products in
Switzerland. One major reason for this is the lack of comparability. Structured products differ
substantially from each other in terms of their payment structure and risk profiles, catering for
different investors’ views and expectations on the one hand, and reacting differently to market
developments on the other. A cursory examination of BRCs, capital protection certificates
(CPCs), and TCs alone is enough to illustrate this diversity: the first have an upper cap, the
second a lower cap, and the third neither. Views on future developments and hedging
requirements will determine how attractive one type is compared to another. Expectations
about volatility, the direction of price movements, andin particularthe potential of prices
falling below certain thresholds are the main criteria for preferring one type of structured
product over another. This implies that direct comparison across categories is difficult if not
impossible. It also implies that a category’s popularity will be driven by general developments
and expectations.
White Paper Structured Products: Performance, Costs, and Investments
A serious performance study has to take all of the aforementioned points into account. The
investigation that follows focuses primarily on the yearly performance of classes of structured
products over the period 20082014, and few comparisons between classes will be offered
during the discussion. Likewise, there will be no benchmarking to the underlying: most products
have some features that put a cap on one side of the payoffs, often with some leverage or scaling
of participation. A direct comparison of annualized returns only would ignore these effects and
would therefore be misleading.
Data Pre-Processing
The following analysis considers the types of structured products that, respectively, enjoy the
largest shares of the marketnamely, BRCs, bonus certificates (BCs), CPCs with coupon, CPCs
with participation, discount certificates (DCs), and TCs. The study considers structured products
listed on the SIX Structured Products Exchange with equity and equity index underlyings. For a
detailed overview of the types of products considered in the sample, see the cost analysis
section. The majority of observations already made are relatively recent; hence the emphasis of
the analysis will be on the period 20122014, while results for the years prior to 2010 need to
be interpreted with extra caution. Returns are computed in terms of price changes in the
secondary market and of coupons. Both price and coupon data were provided by Derivative
Partners AG. The actual amounts of coupon payments are not available, so the value of the
coupons is derived from the product description of coupon size and frequency. The market data
are based on live quotations from the SIX Structured Products Exchange, and are of good quality.
The coupon data are purely informational, and are more likely to suffer from quality issues. For
example, coupon amounts and frequencies can be incorrectly specified, or missing.
Structured products typically have short maturities. For example, around three-quarters of the
BRCs considered have maturities of one year or less, and start and end dates virtually never
coincide with the beginnings or ends of calendar years. Consequently, structured products often
exist for only a few months in one calendar year and a few more in the previous or the next one.
For the calendar year in which the structured product is issued, the return is computed from the
date with the first available quote until year end; for the year within which the product matures,
from start of year until the last available quoted price. These returns are then annualized. In all
cases, mid-prices of market quotes were used to capture the investor’s perspective.
Annualizing returns based on short periodsfor example, a weekcan result in extreme and
unrealistic annual returns. This could heavily distort the overall results, irrespective of the fact
that such a short period can hardly reflect the yearly performance of a given product. Therefore,
the following procedure has been adopted to compute annualized returns and aggregate
If a product exists for less than two months in a given calendar year, it is not included in the
analysis for that year. Two months was found to be a reasonable thresholdthe aggregate
results do not differ substantially from longer cutoff thresholds (e.g., three months), but are
based on a noticeably larger set of observations.
White Paper Structured Products: Performance, Costs, and Investments
All aggregate statistics will be based on weighted observations. The longer a product exists
within a given calendar year, the more emphasis it receives when evaluating the
performance of a class in that calendar year. This reduces the exaggerations of short-term
effects while maintaining some relevant information about performance during that period.
Apart from TCs, all structured products considered have caps, limiting one side of their payoffs
and, consequently, their returns. Such asymmetries have undesirable effects on commonly used
summary statistics: averages become biased toward outliers and no longer reflect what typically
happens, and standard deviations and volatilities do not catch the fact that large deviations will
mainly occur only on one side and that upside risk and downside risk can differ substantially.
Figure 14 illustrates this effect. The following analysis therefore prefers quantile-based
To get a better idea of the “typical” outcome, the median observation provides a robust
measurement for which half of the observations are above, and the other half below. More
technically, the median represents the 50% quantile, with a 50:50 chance that a structured
product from that sample performs above or below the median.
Likewise, quantiles for other probabilities provide information about the range of
observations and typical deviations from the center. For example, one-quarter of the
products have a performance below the 25% quantile while three-quarters exceed it; while
for the 75% quantile, it is exactly the other way round.
The mean, on the other hand, can be biaseda small number of outliers can distort the
sample average, which then no longer reflects the performance of typical (or even the
majority of) products. For example, data errors are more likely to affect the mean, since they
are a source of outliers. For this reason, means will be reported in the table with summary
statistics for the sake of completeness; but for the main analysis, medians and quantiles
provide more insights.
These measurements allow a clearer picture of the performance characteristics of an entire
class. Also, they are more robust to outliers and measurement errors than the usual average and
standard deviation, which also helps with the previously discussed issues of short maturities
and annualization, in particular in their weighted versions.
General Findings
For most of the years considered in this study, the majority of structured products yielded a
positive performance. In particular, for the years 20122014 all of the categories considered had
positive median returns (see Figure 3) implying that the majority of products generated positive
returns (see also Figure 4). By contrast, 2011 andabove all2008 were particularly difficult
years, in which a large proportion of products generated negative returns. This reflects the
general developments for those years. The Swiss market index (SMI) lost approximately 33% in
2008 due to the most recent global financial crisis (GFC), and in 2011which was affected by
the European debt crisisthe SMI was down by approximately 9%. Likewise, the positive
performance during 20122014 was paralleled by the positive performance of the SMI.
Nonetheless, a direct comparison of equity and structured products is difficult given these
White Paper Structured Products: Performance, Costs, and Investments
products’ payoff structures and features such as capital protection or coupon: almost all of the
structured products considered in this study have limits on the positive side of returns, but not
on the negative. This, however, is offset with a much lower probability of negative than positive
returns. This manifests itself in the fact that, under normal” market conditions, these products
are very likely to generate a positive return with relatively little volatility. Because of these
fundamental differences in payoff structures and likelihoods of outcomes, this paper abstains
from benchmarking.
The second main reason why benchmarking would prove difficult is the rather short time-to-
maturity of most structured products. The reported median performances are based on
annualized values as many of the constituents of a yearly sample only existed for some months
but not for the entire year; they therefore reflect the outcome of a buy-and-hold investment for
start to end of a calendar year (if the product did exist for the entire year), or a repeated
investment in comparable products.
Looking at median performances over the years also shows that some classes of product are
more reactive to market developments than others: not surprisingly, TCs closely follow overall
movements in equity markets, while products with capital protection typically fluctuate within a
rather narrow band; and depending on their design and conditioned payments at maturity,
deviations from the typical outcome can be asymmetric. The following discussion highlights
some of these category-specific findings; the summary statistics can be found in Table 2.
Investors in BRCs, TCs, DCs, and BCs fail in the aggregate to have a forecast view of the evolution
of financial markets. They, again on average, did not foresee the most recent GFC or the
European debt crisis in 2011. The losses from these products show that investors overestimated
return expectations and underestimated risks.
Figure 3: Median performance.
Figure 4: Fractions of products with positive returns.
White Paper Structured Products: Performance, Costs, and Investments
Barrier Reverse Convertibles
With more than 20,000 individual products considered, BRCs constitute by far the largest group
in this study. From 2012 to 2014, BRCs typically generated returns of 10%, 7%, and 4% per
year, respectively (weighted median returns), with deviations of individual products growing
smaller over time. This can be seen in Figure 5: the red line depicts the medianthat is, it splits
the products in half, with 50% having higher, and the rest having lower returns. The gray area
gives the 25%75% quantiles, and the two gray lines the range for the 15%85% quantiles
that is, the bandwidths covering 50% and 70%, respectively, of the sample. Note that for BRCs
and similar products the median, representing “typical” product performance, is closer to the
upper than to the lower bounds. The payoff structure limits the positive performance. Effectively
this leads to a high probability of positive performance, while negative performance is less
likely, but is not capped. This skewness in the returns will be discussed in more detail in the
“investmentssection of this study.
In 2014, three out of four BRCs performed positively; in the two preceding years it was even
nine out of ten. Comparing results over time also reveals that performance can change
noticeably from year to year: in 2009, for example, another nine out of ten products again had
positive returns, yet with a median of 30%. Over these five years, this class attracted huge
interest from investors, with twenty times the number of included products for 2014 compared
to 2008. By design, BRCs are affected by large drops in the prices of underlyings; this explains
the poor performance in the years 2008 and 2011.
Figure 5: Median (red line), 25%75% quantile band (gray area), and 15%85% quantiles (gray
White Paper Structured Products: Performance, Costs, and Investments
Bonus Certificates
Similar to BRCs, the profit and loss of a BC depends on whether a barrier has been hit; however,
they do not have a cap on the profit. Accordingly, their performance is similar to that of BRCs in
years with sharp falls in the markets, yet more positive in bearish markets. The median BC
generated a return of 15% or more during 20122013, and 9% in 2014, with typically four out
of five performing positively. More popular than BRCs in the years following the most recent
GFC, their number stagnated and eventually dropped over recent years.
White Paper Structured Products: Performance, Costs, and Investments
Figure 6: Median (red line), 25%75% quantile band (gray area), and 15%85% quantiles (gray
Discount Certificates
DCs have a cap on profits, but lack the barrier that characterizes BRCs. Payments at maturity can
be lower even without sharp drops in the underlying’s price; this, however, is also reflected in
the pricing of this product. The typical DC has had, over the last three years, a return of 12%,
10%, and 5%, respectively, with approximately four out of five having a positive return. Due to
the cap on profits, negative deviations from the typical outcome can be bigger than positive
ones. This can be seen for 2011, for which the confidence band is asymmetric around the median
with larger negative, than positive, deviations. The median was still close to zero, implying that
almost half of the products had a positive return. DCs share this asymmetric behavior with BRCs
and BCs; consequently, under (strongly) negative market developments they all have mean
returns noticeably below their medians.
Figure 7: Median (red line), 25%75% quantile band (gray area), and 15%85% quantiles (gray
Tracker Certificates
Unlike the other product categories considered here, TCs have no conditional payoffs at
maturity. Consequently, they do not exhibit the asymmetries found in all the other categories,
White Paper Structured Products: Performance, Costs, and Investments
and their values directly reflect general market developments. Not surprisingly, TCs were hit
hard by market turmoil in 2008 and 2011, and have the lowest proportion of positively
performing products of all categories considered.
Figure 8: Median (red line), 25%75% quantile band (gray area), and 15%85% quantiles (gray
Capital Protection Certificates
CPCs exhibit the most stable performance of all classes investigated. For CPCs with participation,
the median performance is always in single digits. The bandwidths within which the majority of
these products perform are narrower than those of other categories, indicating their low level of
risk. Losses are possible due to price fluctuations during CPCs’, comparatively long, time to
maturity and because capital protection levels are often below 100%. Apart from CPCs with
participation, CPCs also exist with coupons. Preliminary results show that the performance of
the latter variety is very similar to that of their “participation” counterparts; however, due to
missing data for several years, a detailed discussion is not possible here and these results are
therefore not reported.
Figure 9: Median (red line), 25%75% quantile band (gray area), and 15%85% quantiles (gray
White Paper Structured Products: Performance, Costs, and Investments
Table 2: Summary statistics for the annualized performance of the five main categories.
Barrier reverse convertibles
25% quantile
75% quantile
Fraction positive
Bonus certificates
25% quantile
75% quantile
Fraction positive
Capital protection certificates with participation
25% quantile
75% quantile
Fraction positive
Discount certificates
25% quantile
White Paper Structured Products: Performance, Costs, and Investments
75% quantile
Fraction positive
Tracker certificates
25% quantile
75% quantile
Fraction positive
Swiss market index
Annual performance
Cost Analysis
The logic of fees for structured products will now be considered and will be compared to the
fees and costs for funds. A structured product has, in general, three fee categories:
Distribution fees;
Production fees;
Risk management costs.
The first two categories are based on feesthat is to say, costs plus a possible net margin.
Distribution and production fees are both known at the issuance date of the structured product.
Distribution and production fees are borne by the investor. The lower the fees, the better the
terms and conditions for the investorso, for example, a higher participation rate, coupon
payments, or a capital protection level follow. Risk management costs are not known with
certainty at the issuance datethe numerical value is known best at the redemption date but
even then the exact value is not known if one takes into consideration the portfolio issues of the
trading books. Figure 10 shows the various fee components of a structured product. Beside the
three categories, the net margin is the residual component between the issuance price (assumed
to be 100%) and the theoretical price (assumed to be 97.5%).
Figure 10: The different fee and cost components of a structured product (the authors).
White Paper Structured Products: Performance, Costs, and Investments
Issuance price
Fair price of
components (IEV)
Theoretical (model)
price (97.5%)
Production issuer
3rd party
3rd party
Risk management
The theoretical price, which is also called the model price, is the price of the product if all
components of the product such as options, stock, funds, etc. are priced using a theoretical
modelthat is to say, as if there were
1. No market frictions such as bid-ask spreads;
2. No uncertainty premium for changing price-sensitive parameters such as dividends,
volatilities, and correlations;
3. No capital-at-risk chargesfor example the shareholder of the issuing firm does not charge
a return for the risk capital, but risk capital is charged and this charge depends not only on
the individual products in the trading book but also on the risk profile of the whole
4. No gains from risk-free investments at early redemptions;
5. No risk costs for the leverage in some products.
Therefore, without taking risk management costs into account, nobody can buy a structured
product at the theoretical price. The uncertainty premium alone will be commented upon since
the other elements do not require further explanation. Why do traders need to consider an
uncertainty premium? The structured product is a payoff promiseat any future date the issuer
has to serve the payoff liability. If a trader does not consider these uncertainties, the issuer is
likely to lose money through its structured product business.
Consider the Australian dollar / Swiss franc (AUD/CHF) correlation, which matters for the value
of derivatives with AUD/CHF as their underlying value. Figure 11 shows the historical
development of this correlation value. The historical values are by no means constant. The value
of the derivative changes over time. This also leads to varying liability value. The traders have
therefore to adjust their position, which guarantees the liability value (dynamic hedging). At the
issuance date of the structured product, the future value of correlation is not known. But the
trader has to fix a value in order to price the product. A different marking of the correlation
leads to a different price of the derivative. Which value should the trader choose? The average
value could be chosen, or the historical maximum or minimum, or any other value. Whatever
value ex ante is chosen, ex post the chosen value can turn out to be too optimistic (the trader
loses money) or too conservative (the trader makes money).
IEV = Issuer estimated value
White Paper Structured Products: Performance, Costs, and Investments
Figure 11: Historical 1-year correlation AUD/CHF from Jan 2012 to Jan 2013. Green areas denote
a positive correlation and red areas a negative correlation (Bloomberg).
Adding all these real imperfections to the theoretical price defines the fair price. The difference
is the risk management component. Whether or not the uncertainty premium was sufficient to
cover the final payoff is only known to the trader at the redemption date.
In a mutual fund, the risk management component is not fully borne by the issuer of the fund.
The tracking error of the fundthat is to say, the deviations of the fund investments from the
underlying benchmarkis charged to the investor. This is possible since the fund does not make
a payoff promise to the investor and hence the fund manager does not need to hedge the
tracking error. It should be noted that the tracking error is not included in the TER of funds.
The difference between the issuance price and the fair price of the components in Figure 10 is
defined by several Swiss issuers as the TER, in order to mimic the TER of the fund industry.
Production fees include index fees for underlying values, issuance costs such as fees for the stock
exchange listing, structuring costs, life-cycle management costs such as for the reporting or
management of corporate actions, and all personnel and non-personnel costs for the employees
involved in the structured product value chain. Since 1 March 2015, issuers of structured
products in Switzerland have had to disclose all distribution fees.
The costs referred to in the next section were computed as follows:
The issuance price of the structured product based on the first ask price was used.
The theoretical (model) price was received from an independent price provider.
Risk management costs were estimated anonymously by several issuers.
The TER, as defined above, was calculated as shown in Figure 10.
The decomposition of the different fee and cost components in Figure 10 suggests that the issue
of cost transparency for structured products is well defined and easy to establish. But it is not. At
least three issues matter.
1. The decomposition is time dependent since the risk management costs vary over time.
2. Which information is publicly known and verifiable; which information is private to the
White Paper Structured Products: Performance, Costs, and Investments
3. Is there a potential for moral hazard from the issuer’s side?
These issues are addressed in the sequel as follows: Due to its importance, the focus lies on the
primary market; specifically, what the costs are for an investor who buys the product in the
primary market. The costs in the secondary market are different. A study of the German market
by Döhrer et al. (2013) shows that the expected issuer margin decreases monotonically over
time for all product categories except for capital protection products. This is also expected to
hold for the Swiss market and indicates that the costs for the investor are not increasing in the
secondary market.
Unlike the Döhrer et al. study of the German market (op cit), which estimates the expected issuer
margin, the present analysis concerns the costs that an investor faces. A first reason for this is
that, for almost all financial products, the issuer’s profit is private information. Second, risk
management costs are issuer specific: two traders that price the same product might differ in
their risk management costs since, for example, the risks of the product diversify the risks of the
trading book of trader 1 (positive impact on capital at risk) while trader 2 does not seek the
risks of the product and therefore has a different willingness to pay for them.
Most information from the cost and fee decomposition is also private, with only the issuance
price and the distribution fee figures being publicly available. This appears to suggest serious
risks of moral hazard. But the analysis thus far has not considered several institutional aspects
that counteract such behavior from the issuer’s side.
1. Standardization: Structured products are mass products. They are generated and managed
over the life cycle with a high degree of automatization. Therefore, there is no opportunity
(in case of automatized platforms) or only a small one (in case of products with a
subscription period) to manipulate the cost and fee structure of single products.
2. Structured product units are part of the trading units of banks. Thus they are subject to
strict control processes, including risk control under which they are accountable to their
bank’s compliance unit. These controls are not applied on a broad superficial level but
rather to individual products on a day-to-day basis.
3. The price of structured products is mark-to-market. There is no room to add arbitrary, non-
qualified components from the trader’s side.
4. The Swiss structured product market is a competitive market. Professional buyers of
products ask several issuers to quote a price (i.e., to state terms and conditions). The quality
of the secondary market is tracked by Derivative Partners AG using the Payoff Market
Making Index, which is published on a monthly basis. Although competition cannot prevent
any undesirable shift between the different cost components, it does make it impossible to
transform the whole cost structure without affecting the terms and conditions of the
product. This is true since structured products are liabilities for the issuer with a payoff
To summarize, the calculation of costs for a structured product is a complicated task. The main
reason for this is that financial products are forward looking in time contrary to most physical
products: The calculation of the costs or margins of a bottle of wine does not face any
uncertainty about the future value of price-sensitive parameters.
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Data Pre-Processing and Sample Construction
The following analysis largely considers the same types of structured products as does the
performance analysisnamely, BRCs, BCs, CPCs with coupon, and DCs. The analysis is
performed over the three years prior to the point at which the study was conducted: from April
2012 to April 2015. For comparability purposes, only those TCs with limited life-spans were
included. (TCs with unlimited life-spans must be sold in the secondary market and must be held
to maturity, which makes them unlike the other classes of structured products). In the sample,
there were only very few capital protection products with participation, so that category was
also dropped. All data for the cost study were obtained from Derivative Partners AG.
The cost calculation for this analysis builds on the fee and cost components of a structured
product as illustrated in Figure 10. In order to compute the costs of structured products, the
difference between the earliest available ask price and the corresponding theoretical price has
been calculated. This is an approximation of the difference between the issuance price and the
theoretical price. But the authors of the present paper lacked reliable data for the issuance price
and the theoretical price at the issuance date. The assumption is that the error is small since this
study considers many products and price fluctuations are likely to cancel each other out to some
degree. As explained in the previous section, the theoretical price in this analysis is the price of a
product if all components of the product are priced using a theoretical model. This price does
not include risk management costs, which are borne by the issuer and which can be significant
for the kinds of complex products available in Switzerland, such as BRCs. The computation of
theoretical prices is beset with considerable difficulties. The products themselves are
heterogeneous, and even products within the same class can have different features, such as
callability. The terms of the products are laid out in individual term sheets, and while databases
of terms have been assembled, these suffer from data omissions and data entry errors.
To solve these problems, theoretical prices were also obtained from Derivative Partners AGa
vendor that provides model prices for structured products in the Swiss marketand calculated
by using this company’s internal model. Derivative Partners AG uses a local volatility model to
price all options. Implied volatilities are provided by Morningstar Inc. and are computed from
Eurex equity-option volatility surfaces. Derivative Partners AG model prices provide a standard
benchmark for the market, and are already used as an independent source of product valuation
for collateralized secured instruments (COSI). The sample consists of all products available from
April 2012 until April 2015 for which Derivative Partners AG had model prices. Derivative
Partners AG provided a time series of theoretical model prices corresponding to ask prices. The
goal of this study is to measure the costs borne by the investor at issuance, so for each product
the earliest ask price has been used as the relevant price for comparison. As some of the
products may have been issued well before the sample period began, products were included in
the sample only if they were issued after the Derivative Partners AG data start date. In addition,
the data for products with shorter maturities seems particularly full of outliers. So to ensure
data accuracy the sample has also been restricted to products with a product life-span of at least
51 weeks (a product’s life-span is the period between its issue and its maturity). One additional
source of outliers is products with missing price data, so the sample only includes products that
White Paper Structured Products: Performance, Costs, and Investments
have ask prices available for at least 181 days to maturity. Altogether, the sample of this study is
very large, containing 7,275 products. Model prices are particularly susceptible to errors in the
product descriptions. So to control for outliers this study concentrates on medians.
Within each product class, the observed products themselves are heterogeneous. The products
trade in a range of currencies: 54% trade in Swiss Francs, while 26% trade in euros, 17% in US
dollars, and the remainder in other major currencies. A total of 95% of the observed products
have equities as underlyings, while 5% have indices. Regarding the underlyings, 52% are Swiss,
while 15% are American, 12% are German, 7% are French, and the remaining 14% are other
As explained in the previous section, risk management costs need to be added to the theoretical
price in order to obtain the fair component price of a structured product. However, risk
management costs are not known with certainty at the issuance date, are not publicly available,
and vary among issuers and also in the market situation as volatility changes. In order to
consider a representative value for these costs, estimates of risk management costs for the
various product types in the current market environment were obtained from four major issuers
of structured products in Switzerland. For each estimate, product features such as the
underlyings, currency, strike prices, and barriers were predefined and the issuers provided their
estimates independently for the products with these features to SFI. In order to avoid moral
hazard, the highest estimate figure was not considered when calculating the average estimate
figure for each product and the final figures were reported anonymously to the authors of this
study. The average annualized value has been used to proxy for these costs. Table 3 shows the
interval for the risk management cost estimates. As can be seen, the estimates are similar to each
other, but can vary up to 25 basis points from the mean. It must be stated that these estimates
only represent such costs in the current market environment and that these costs vary as
market parameters, such as volatility, change. Risk management costs can also vary within a
product class, which is another potential source of error. TCs do not normally face the same
kinds of risk management costs, so the study uses a risk management cost of zero.
White Paper Structured Products: Performance, Costs, and Investments
Table 3: Average annualized risk management cost estimates, for which the highest reported
figures were deleted (four major issuers of structured products in Switzerland).
Product type
Risk management cost estimates per
Worst of barrier reverse convertibles (barrier at 75%)
1-year maturity: 1.28%1.50%
3-year maturity: 0.51%0.87%
Bonus certificates (barrier at 75%)
2-year maturity: 0.84%1.25%
Capital protection certificates (95% cap. protection)
5-year maturity: 0.06%0.13%
Discount certificates
1-year maturity: 0.10%0.25%
As can be seen from the table, the risk management costs for products with barriers and several
dependent underlyingssuch as the worst of BRCscan be sizeable. The costs are not a source
of income for the issuer; they are simply a cost the issuer bears to hedge the complex product
features that are not known at issuance. For simpler products, these costs are much lower. For
TCs, for example, the costs are close to zero
since there are no complex structures to hedge.
The following example, which was sent to the authors by an anonymous issuer, discloses the fine
structure of the risk management costs for a BRC with a Nestlé, Novartis, and Roche underlying,
1-year maturity, and a barrier at 80%. The pricing holds for the market conditions in March
Spread of volatilities 0.55%.
Uncertainty premium 0.38%
Dividend risk 0.23%
Funding spread 0.30%
This results in risk management costs of 1.46%.
General Findings
Table 4 reports the cost results for each product class. The costs are the difference between the
ask price and fair price, expressed as a percentage of the theoretical price. The count column
reports the number of products in the sample for each class, while the other three columns
represent the 25%, 50%, and 75% quantiles for each class. All figures are annualized.
Such costs can arise if the investor does not bear the bid-ask spreads in rebalancings and are difficult to imagine in
secondary markets. Illiquid underlying values such as some funds or the minimum trading unit in bond trading could
generate this type of cost.
White Paper Structured Products: Performance, Costs, and Investments
Table 4: 25%, 50%, and 75% quantiles for the product sample for the period April 2012 to April
Product type
Number of products
Barrier reverse convertibles
Bonus certificates
Capital protection
Discount certificates
Tracker certificates
As mentioned above, TCs without expiration dates are excluded, since annualization is
meaningless for a product with an unlimited life-span. Since investors can only realize the gains
from such a TC by selling it, an alternative measurement would be the percentage difference
between the ask price and the mid-price. There are 88 TCs in the Derivative Partners AG sample.
For those 88 products, the 25%, 50%, and 75% quantiles are 0.26%, 0.36%, and 0.54%,
respectively. It is tempting to compare these figures with their counterparts from the fund
industry. To avoid a comparison of apples to oranges, some remarks should be considered. First,
of the 88 TCs 10 were dynamic and 78 static. Since dynamic strategies, either by a rule or
discretionary, are more complex than static ones the former are more expensive. Second, the
type of underlying in TCs is an important cost driver. If a TC consists of a basket of 20 liquid
stocks, much lower costs should follow than for a basket of 20 credit default swaps. Third, the
volume of TCs matters: the larger the volume, the lower the production costs per unit. Also, for
funds a number of disclaimers apply. Like the prices of most goods and services, the expenses of
funds differ considerably across the array of available products. First, does one consider actively
managed funds, index funds, or ETFs? Second, are the underlying values equities, bonds, or from
another asset class? Third, are large and small size funds considered? Fourth, how is the
investment objective defined? For equity funds, are growth, value, alternative strategies, or any
other investment objective considered? Taking these remarks into account, data from the
Investment Company Institute (2013), for mutual funds and index funds, and from DB Tracker
(2015,) for ETFs, provide the following mean figures
Mutual funds: 0.74% for equity funds, 0.61% for bond funds where the figures are volume
weighted. Since larger funds have lower fees, the corresponding figures are 1.37% and
1.16% for bond funds without volume weighting.
ETFs: 0.49% for equity and 0.25% for bonds.
ETF core: 0.09%.
Despite all these differences, it can be stated that:
Structured products are not cost competitive to ETF core.
Structured products face similar costs to ETFs.
If only actively managed TCs are considered, they seem to have a price advantage over
mutual funds.
White Paper Structured Products: Performance, Costs, and Investments
There are several previous studies that have considered the question of costs for derivatives and
structured products. Of these, Döhrer et al. (op cit) find the lowest costs of any study,
considering a cross-section of German structured products on a single day, and using a complex
estimation procedure to back out implied issuer margins. The authors’ estimation procedure
leads to exponentially decreasing estimates of the issuer margin over the lifetime of the product,
except for the case of CPCs. Most of the products in the study were evaluated in the middle of
their lifetimes, which biases the issuer margin estimates downward compared to the margin at
issuance. Since most products are bought at issuance, this is the relevant cost for the vast
majority of investors. The sample of products studied by Döhrer et al. (op cit) is also very
different from that of the present study, in that the vast majority of products in their sample are
CPCs, which are the least complex and therefore lowest cost product. One might wonder why the
costs differ within different types of product by a factor of 2 to 4 if one compares the quantiles.
Besides the different risk appetite of the traders other factors also have an impact. First,
distribution fees can be very different. If an investor uses the products in a mandate where no
distribution fees are allowed, a different price follows than follows for an investor that charges
its end customers a fee of 0.5%. Second, the production fees are different both for different
issuers and different underlyings. Since not all issuers have achieved the same standard of
automatization, production costs per unit are different. If an investor wants a product with
underlying Nikkei 225 and another investor asks for the same structure but on the SMI, the
former product will be more expensive since the index fees for the Nikkei 225 are higher than
for the SMI. Third, as for any product, volume matters: a pricing request for an issuance of CHF 1
million has a different pricing ticket than a CHF 40 million request. These differences need to be
considered if one decides to validate a third independent valuation party’s pricing of products.
If the results of this study are compared to the many prior academic or regulatory studies,
majority of the latter find much higher costs. The reason for this is simple, as Döhrer et al. (op
cit) already state in detail in their study: Academics need to focus on the theoretical value due to
lack of datathat is to say, they treat the risk management costs borne by the issuer as if they
were costs borne by the investor. Therefore, one has to be very careful when interpreting
academic studies in this field.
Investments When Markets are “Normal”
The statistics in the cost and performance section of this paper show that many Swiss investors
prefer to invest in BRCs, autocallables,
TCs, andif the time value of money is positivealso in
capital protection structured products. This White Paper will not discuss when and how such
investments are chosen since this is covered in detail in Meier and Sandmeier (2012), Rieger
ESMA Report (2014), Henderson and Pearson (2011), Jorgenson et al. (2011), and Szymanowska et al. (2009).
Autocallables are structured products that offer an opportunity both for early redemption at a predefined cash
amount and for coupon. Both opportunities are linked to the performance of the underlying.
White Paper Structured Products: Performance, Costs, and Investments
(2009), and Tolle et al. (2006). The focus here will be on the issues of technology and investor
White Paper Structured Products: Performance, Costs, and Investments
Structured products are today offered to investors on a tailor-made basis using platforms
starting from a minimum investment of CHF 20,000 or even lower. An investor can construct
and buy a tailor-made product without any delay. Comprehensive documentation of the
investment is also generated automatically before the trade is confirmed. The pricing of the
product is based on real-time data and products can be sold in the secondary market at any time
with tight bid-ask spreads. To the authors’ knowledge, there is no other banking unit that is able
to generate a customized security for such a low investment amount using a fully automatized
value chain.
The technological trends in the structured products industry are manifold. Some single-issuer
platforms are transformed into multi-issuer platforms that give investors the opportunity to
compare the offerings of different issuers; see, for example, the Vontobel deritrade platform.
Other issuers offer the functionality needed for running a structured products business to
smaller banks, which are not able to issue products on a stand-alone basis (“white labelling”; e.g.,
Leonteq). Other issuers are actually enlarging their offering such that investors can value an
investment decision in the portfolio context. Finally, issuers are finding out to what extent big
data” can be used to refine investor’s preferences and even to provide anticipatory offerings (i.e.,
investors’ preferences are known ex ante from their activities in the virtual world, which makes
questionnaires for determining investors’ preferences redundant). These activities show that
the Swiss structured products industry is not a mere follower of what today is called FinTech,
but is itself active as a first mover. This makes structured productsfrom a technological
perspectivefitter to face future challenges than many other banking functions.
Investor Behavior
Investors in Switzerland like to invest in BRCs on stocks. Investors in other countries have
different preferences about the underlying value and the payoff. A study by Hens et al. (2014)
proves that cultural background matters for the degree of risk aversion although these
differences are diminishing due to globalization. Investments in such products occur more often
when markets are calm than in periods in which markets are under stress. This is remarkable
since analysis reveals that in Swiss structured products equity markets a period of falling share
prices is paralleled by increasing volatility. But an investment in a BRC means that the investor,
among others, sells a put option. If volatility is high this put option is worth more than it is in
calm markets. Therefore, in turbulent markets the BRC investor receives a higher coupon and/or
can choose a lower barrier for the same coupon than in normal markets. But Figure 12 shows
that investors refrain from BRC investments when volatility is high. The volatility of SMI spiked
in summer 2011 when the European debt crisis led to an increase in uncertainty about the
future of the eurozone. The data for the figure were taken from a platform via which investors
can create their own BRCs.
White Paper Structured Products: Performance, Costs, and Investments
Figure 12: Number of transactions (bars) and SMI volatility (line) for the 1,900 investors who
used a selected tailor-made structured-product platform. Since more than 90% of the
underlyings were Swiss stocks, SMI volatility is a good proxy (ZKB).
In periods of increasing volatility, many BRCs breached their barriers. As a result, many
investors were disappointed but others simply accepted that the risk of breaching the barrier
materialized. This leads us to consider two types of investors in BRCs: through-the-cycle
investors and point-in-time investors. The first require an investment that should be
independent of the stock market cycle. The second type of investor wants to exploit the current
market opportunity; thus the investment depends on the stock market cycle. For the latter, the
interplay between the barrier (the risk level of the product) and the actual volatility in the
market matters. Through-the-cycle investors by definition accept a lower return and lower risk
compared to their point-in-time counterparts.
Is it possible to quantify the risk and return boundaries for BRCs on stocks for through-the-cycle
investorsthat is, to derive barrier levels that are independent of the stock market cycle? To
answer this question, a three-year investment in the S&P 500, with a 50% barrier, starting in
1957, repeated 1958, and so on up to 2011for the last timewill be considered. Figure 13
shows the lowest value of the index for each three-year investment (blue area). The red bar
shows the period in which an investment in the BRC would have led to a breach of the barrier:
this only happened during the most recent GFC. In all other investments in the 55-year period, a
50% barrier level would have led to capital protection.
White Paper Structured Products: Performance, Costs, and Investments
Figure 13: Lowest value of the S&P 500 for annual 3y investments (S&P).
It is also evident from Figure 13 that a barrier level of, say, 80% or 70% cannot be considered to
be appropriate for a through-the-cycle investor. The above findings will next be applied to a
portfolio of 1,900 tailor-made products, using the fully automatized platform of a large Swiss
issuer in the period January 2011 to March 2013. This period has been chosen as it covers a full
stock market cycle: market turbulences in August 2011 due to the European debt crisis, followed
by a stock market recovery. Figure 14 showsin the left panelthe returns of all BRCs. One
observes that there were many barrier hits in August 2011 and for products maturing shortly
after this market turmoil there was not enough time to recover. Is this data set representative?
The large number of barrier hits due to the market turmoil of August 2011 can also be observed
in the following table (Derivative Partners AG) regarding all listed BRCs in the Swiss market (see
Table 5). This shows that the choice of the data from the issuer can be seen as representative.
Table 5: Barrier events of active BRCs, 20082014 (Derivative Partners AG).
Number of
active BRCs
Number of active BRCs (less BRCs with
barrier event in the previous year)
Number of
barrier events
White Paper Structured Products: Performance, Costs, and Investments
Figure 14: Returns of tailor-made BRCs. On the horizontal axis the products are ordered in
increasing order of their maturity date, starting in January 2011 and ending in March 2013 (fully
automatized platform of a Swiss structured products issuer).
Note to the two previous figures. First figure: one observes a cluster of negative returns for
products that were issued before August 2011. This is only possible if they breached their
barrier in August 2011. Second figure with barriers below or at 60%: the cluster of negative
returns due to the barrier hits in August 2011 vanishes if the barrier is not larger than 60%. The
few large negative returns left were due to investments in the underlying values of firms that
The average return of the products in the stock cycle was 2.2% and the proportion of products
with a positive return was 77%. The second panel shows the same analysis but only for products
with a barrier not higher than 60%. One observes that much fewer barrier hits follow. The
average return of the portfolio jumps to 7.7% and the proportion of products with a positive
return to maturity is 97.9%. There are only a few products with heavy losses left. These
products cannot be related to the above discussion of through-the-cycle vs point-in-time
White Paper Structured Products: Performance, Costs, and Investments
investors, but can be to investors who have chosen an underlying value that defaults or that is
close to default.
Investment Opportunities Driven by Events
While some events are isolated and affect only a single corporate, events at the political or
market level often lead to more interesting investment opportunities for structured products.
Policy interventions can trigger market reactions that in turn can lead to new policy
interventions. The SNB decision, in January 2015, to remove the euro cap and to introduce
negative interest rates had an effect on Swiss stock markets, EUR/CHF rates, and fixed income
markets. Next, investment opportunities caused by political or market eventsbut not firm-
specific eventswill be discussed.
The BRC analysis in the last section showed that investors prefer to invest in times when
markets are not under stress. This is remarkable since events create investment opportunities
due to higher volatility. In addition, gaining an investment view and evaluating it personally is
easier if an event has happened and markets are under stress than it is in normal times. Once an
event has occurred, an investor no longer needs to guess whether any event could happen in the
future that would affect the investment. However, an investor does have to consider the
possibility that markets will return to the pre-event state or to a new state that will become the
new normal, or if the changes in market values are just a beginning. Analyzing these possibilities
is not a simple task, but it is simpler than the situation in normal markets, where the likelihood
of the occurrence of events has to be considered. It should be stressed that a general
requirement for investments based on events is fitness of all parties involvedinvestors,
advisory, and the issuer. In order to benefit from such investments, the active involvement of all
parties is necessary.
Political Events
The SNB announced, on 15 January 2015, the removal of the euro cap and the introduction of
negative CHF short-term interest rates. This decision caused the SMI to lose about 15% of its
value within 12 days, and the FX rate EUR/CHF dropped from 1.2 to near parity. Similar
changes occurred for USD/CHF. Swiss stocks from export oriented companies or companies with
a high cost base in Swiss francs were most affected. The drop in stock prices led to a sudden and
large increase in Swiss stock market volatility. Swiss interest rates became negative for
maturities of up to thirteen years.
It was also known at the time that the ECB would make public its stance on quantitative easing
(QE) one week later. The market participants’ consensus was that Mario Draghipresident of
the ECBwould announce a QE program. The events in Switzerlandwhich came as a
surpriseand the ECB QE measures subsequently announced paved the way for the following
investment opportunities:
1. A CHF investor could invest in high quality or high dividend paying EUR shares at a discount
of 15%. EUR shares were expected to rise due to the forthcoming ECB announcement.
White Paper Structured Products: Performance, Costs, and Investments
2. All Swiss stocks, independent of their market capitalization, faced heavy losses
independently of their exposure to the Swiss franc.
3. The increase in volatility made BRCs with very low barriers feasible.
4. The strengthening of the Swiss franc versus the US dollar, and the negative CHF interest
rates, led to a USD/CHF FX swap opportunity that only qualified investors could benefit
5. The negative interest rates in CHF and rates of almost zero in the eurozone made
investments in newly issued bonds very unattractive. Conversely, the low credit risk of
corporates brought about by the ECB’s decision offered opportunities to invest in the credit
risk premia of large European corporates via structured products.
Before certain investment opportunities are discussed in more detail, it should be noted that by
the time this paper was written (about five months after the events described above took place),
all investments were profitable and some even had two-digit returns. This certainly does not
mean that the investments were risk free, as such investments are not risk free. But it shows that
many investment opportunities are created by policy interventions. This contrasts with the
often voiced complaints about negative interest rates and the absence of investment
opportunities for firms, pension funds, and even private investors. Some investment ideas will
now be considered in more detail.
Opportunities to invest in high dividend paying EU stocks
The idea was to buy such stocks at a discount due to the gain in value of the Swiss franc against
the euro. The first issuer of a TC offered such products on Monday, 19 January 2015that is to
say, two business days after the SNB’s decision was announced. With all products, investors
participated in the performance of a basket of European shares with a high dividend forecast.
The baskets’ constituents were selected following suggestions from the issuing banks research
units. Investors could choose between a structured product denominated in Swiss francs or in
euros depending on their willingness to facebesides the market risk of the stock basketalso
the EUR/CHF FX risk.
This investment had two main risk sources. If it was denominated in euros, the EUR/CHF risk
held and one faced the market risk of the large European companies whose shares comprised
the basket. Most investors classified the FX risk as acceptable since a significant further
strengthening of the Swiss franc against the euro would meet with counter measures from the
SNB. More specifically, a TC on a basket of fourteen European stocks was issued. The issuance
price was fixed at EUR 98.75. As of 1 April 2015 the product was trading at EUR 111.10 (mid-
price)equivalent to a performance of 12.51% pro rata. Similar products were launched by all
the large issuers.
Other issuers launched a TC on Swiss stocks, putting all large Swiss stocks in a basket that had
only a little exposure to the Swiss franc, but which also faced a heavy price correction after the
SNB decision in January. Again, the input of each issuing bank’s research unit in identifying these
firms was key. The underlying investment idea for this product can be seen as a typical
White Paper Structured Products: Performance, Costs, and Investments
application of behavioral finance: an overreaction of market participants to events is expected to
vanish over time.
The risk in this investment was twofold. First, one could not know with certainty whether the
SNB would consider further measures, such as lowering interest rates further, which would have
led to a second drop in the value of Swiss equity shares. Second, international investors with
euros or US dollars as their reference currency could realize profits since the drop in Swiss share
valuesaround 15%was more than offset by the gain from the currency, which lost around
20% in “value”; roughly, an institutional investor could earn 5% by selling Swiss stocks. Since
large investors exploit such opportunities rapidly, it became clear three days after the SNB’s
decision was announced that the avalanche of selling orders from international investors was
Low-barrier BRCs
Investors and private bankers searched for cash alternatives with a 100% capital guarantee. The
negative CHF interest rates made this impossible: if 1 Swiss franc today is worth less than 1
Swiss franc will be worth tomorrow, one has to invest more than 100% today to get a 100%
capital guarantee in the future.
Low-barrier BRCssay with a barrier at 39%could be issued with a coupon of 1%2%
depending on the issuer’s credit worthiness and risk appetite for a maturity of 1 to 2 years.
S&P500, Eurostoxx 50, SMI, NIKKEI 225, and other broadly diversified stock indices were used
in combination as underlying values for the BRCs. The low fixed coupon of 1%2% takes into
account that the product is considered as a cash alternative with 0%, or even a negative, return.
Therefore, investors received, at maturity, the coupon paymentin any caseand also 100% of
the investment back if no equity index lost more than 61% during the life-span of the product. If
at least one index lost more than 61%, the investor received the worst performing index at
maturity, together with the coupon. The risks of such an investment differ clearly from those of a
deposit. For a deposit in Switzerland, there is a deposit guarantee of up to CHF 100,000.
Furthermore, almost all banks in Switzerland did not charge their clients the negative interest
rate costs. Hence, at present, a deposit is seen by many customers as “less risky”, albeit also with
zero performance before costs.
A low-barrier BRC, apart from issuer risk, has market risk. Can one estimate the probability that
one of the indices in a basket will lose more than 61% in one year? One could simulate the
basket and simply count the frequency of events leading to a breach. Such a simulation has the
drawback that one needs to assume parameters for the indices. Another method would be to
consider the historical lowest level of such a basketthat is to say, what was the maximum loss
in the past if one invested in a low-barrier BRC? Using data going back to the initiation of the
indices, no index lostin one yearmore than 60% (see also Figure 13). This was the rational
to set the barrier at 39%. This is obviously not a guarantee that this statement will apply also in
the future, but it helps investors to decide whether they accept the risk or not.
Although this discussion has concerned a BRC on equity, a similar discussion applies to such
convertibles that have currencies and commodities as underlyings. Relevant political and market
White Paper Structured Products: Performance, Costs, and Investments
events in the recent pastand to which the above discussion also appliesoccurred in October
2014 and, due to the European debt crisis, in August 2011. With regards to the former set of
events, the pressure on equity markets was due to uncertainty regarding Russia and what would
happen next in Ukraine; and on 15 October 2015 liquidity evaporated in treasury futures and
prices skyrocketed—an event known as the “flash crash in the treasury market”.
Japan: Abenomics
As expected, the Liberal Democratic Party of Japan gained a substantial parliamentary majority
in the 2012 elections. The economic program introduced by the newly elected PM Shinzo Abe
was built on three pillars: 1) fiscal stimulus, 2) monetary easing, and 3) structural reforms
(“Abenomics"). Subsequently, the Yen (JPY) plunged versus its main trading currencies,
providing a hefty stimulus to the Japanese export industry. The issuer of one product offered an
outperformance structured product on the Nikkei 225 in quanto Australian dollars, meaning
that the structured product in question is denominated in AUD and not in JPY, which would be
the natural currency given the underlying Nikkei 225. This means that investors did not face
JPY/AUD currency risk but if they were Swiss investors who think in Swiss francs, they still faced
AUD/CHF risk. The acronym “quanto” means “quantity adjusting option”.
Outperformance certificates enable investors to participate disproportionately in price advances
in the underlying instrument if it trades higher than a specified threshold value. Below the
threshold value the performance of the structured product is the same as the underlying value.
How can investors invest in an index in such a way as to gain more when markets outperform a
single market index investment, but still not lose more if the index drops? The issuer uses the
anticipated dividends of the stocks in the index to buy call options. These options lead to the
leveraged position on the upside (see Figure 15).
Figure 15: Payoff of an outperformance structured product.
The reason for using quanto AUD is the higher AUD interest rates compared to JPY interest rates.
Higher interest rates lead to higher participation and the participation in the quanto product
was 130%. The risk of the investment lay in whether Abenomics would work as expected; and
White Paper Structured Products: Performance, Costs, and Investments
possibly FX AUD/CHF. The economic program in Japan worked out well with redemption of
198% after two years. This redemption contains a loss of 16.35% due to the weakness of the
Australian dollar against the Swiss franc.
Market Events
The focus here will be on the credit risk of structured products. Although the examples are
presented under the heading of market events, the status of the market in the most recent GFC
and in 2014/2015 was the result of a complicated catenation of business activities, policy
interventions, and market participants’ reactions.
The discussion below shows that structured products with underlying “credit risk” offer, under
specific circumstances, valuable investment opportunities to some investors. But the number of
such products issued is much smaller than the number of equity products. One reason for this is
that not all issuers are equally experienced or satisfy the requirements for issuing credit-risky
structured products (necessary FI trading desk, balance sheet, and risk capital constraints).
Another reason is the lack of acceptance of such products among investors, regulators, portfolio
managers, and relationship managers, all of whom often do not have the same experience and
know-how as they do regarding equity products.
Negative Credit Basis after the Most Recent GFC
Negative credit basis is a measurement of the difference in the same risk in different markets.
The basis measures the difference in credit riskmeasuring once in the derivatives markets and
once fixed in the bond markets. Theoretically, one would expect that the credit risk of ABB has
the same value independent of whether an ABB bond or a credit derivative defined on ABB’s
credit risk is being considered.
This is indeed true if markets are not under stressat which point the credit basis is close to
zero. But if liquidity is an issue, the basis becomes either negative or positive. In the most recent
GFC, liquidity was a scarce resource. The basis became negative since investing in bonds
required funding the notional while for credit derivatives only the option premium needs to be
financed. For large corporates, the basis became strongly negative by up to -7%. The following
table shows how the positive basis in May 2003 changed to a negative one in November 2008
(bps are basis points: 1 bps is 1% of 1%).
Table 6: Credit basis for a sample of corporates in 2003 and their negative basis in the most
recent GFC.
Credit basis in May 2003 (bps)
Credit basis in November 2008 (bps)
Merrill Lynch
General Motors
White Paper Structured Products: Performance, Costs, and Investments
JPMorgan Chase
To invest in a negative basis product, the issuer of a structured product locks in the negative
basis for an investor by forming a portfolio of bonds and credit derivatives of those firms with a
negative basis. For each day on which the negative basis exists a cash flow follows, which defines
the participation of the investor. When the negative basis vanishes, the product is terminated.
Example: Investing in the negative credit basis of General Motors (see Table 6) leads to a return,
on an annual basis, of 5.04% if the basis remains constant for one year. If the product has a
leverage of 3, the gross return is 15.12%. To obtain the net return, one has to deduct the
financing costs of the leverage.
Structured products with this idea in mind were offered in spring 2009 to qualified investors.
The products offered an annual fixed coupon of around 12% and participation in the negative
basis. The high coupons were possible as some issuers leveraged investorscapital. This could
only be offered by those few issuers in the most recent GFC that were cash rich; typically AAA-
rated banks. The products paid one coupon and were then terminated after 14 months since the
negative basis approached its normal value. The product value led to a performance of around
70% for a 14-month investment period. Was this formidable performance realized ex ante a free
lunchthat is to say, a riskless investment? No. If the financial system had fallen apart, investors
would have lost all the invested capital. But the investors basically only needed to answer the
following question: Will the financial system and real economy return to normality? If yes, the
investment was reduced to the AAA issuer risk of the structured product.
Many lessons can be drawn from these products. A very turbulent time for markets can offer
extraordinary investment opportunities. The valuation of these opportunities by investors must
follow different patterns than in times of normal markets: There is for example no history and
no extensive back-testing, and hence an impossibility of calculating any risk and return figures.
But there is a lot of uncertainty. Making an investment decision when uncertainty is the main
market characteristic is an entirely different proposition to doing so when markets are normal
and the usual risk machinery can be used to support decision-making with a range of forward-
looking risk and return figures. If uncertainty matters, investors who are cold-blooded,
courageous, or gamblers, and analytically strong, will invest, while others will prefer to keep
their money in a safe haven.
Positive Credit Basis 2014
The monetary interventions of the ECB and other central banks led to excess liquidity, which
was mirrored in a positive basis for several large firms. Monetary policy also implied low or
even negative interest rates. This made investment in newly issued bonds unattractive. To
summarize, investors were searching for an alternative to their bond investments, but an
alternative that was similar to a bond.
A credit linked note (CLN) is a structured product. Its payoff profile corresponds to a bond’s
payoff in many respects. A CLN payssimilarly to a bonda regular coupon. The size of the
coupon and the amount of the nominal value repaid at maturity both depend on the credit
White Paper Structured Products: Performance, Costs, and Investments
worthiness of a third party, the so-called reference entity (the issuer of the comparable bond).
This is also similar to the situation for bonds. But the size of the CLN coupon derives from credit
derivative markets. Hence, if the credit basis is positive, a larger CLN coupon follows, as
compared to the bond coupon of the same reference entity. CLNs are typically more liquid than
their corresponding bonds since credit derivative markets are liquid while many bonds, even
from large corporates often suffer from illiquidity. CLNs are flexible in their design of interest
payments, maturities, and currencies. CLNs also possess, compared to bonds, tax advantages; in
fact, the return after tax for bonds that were bought at a price above 100% isat presentoften
negative. The investor in a CLN faces two sources of credit risk: the reference entity risk as for
bonds, and the issuer risk of the structured product. As an example, Glencore issued a new
1.25% bond with coupon in Swiss francs. Due to the positive basis, the coupon of the CLN was
1.70%. Another product with, as the reference entity, Arcelor Mittal in EUR implied a higher CLN
effective yield compared to the bond of 1.02% in EUR.
Let us consider a more detailed example. Consider the reference entity Citigroup Inc. The bond
in CHF matures in April 2021 and its price is 102.5 with a coupon of 2.75%. The bond spread is
57 bps, which leads to a yield to maturity of -0.18%an investor should sell the bond. The CLN
has a spread of 75 bps, which proves the positive basis and an issuance price of 100. The coupon
of the CLN isthen0.71%, which leads to a yield to maturity of 0.57% if funding is subtracted.
Therefore, selling the bond and buying the CLN generates an additional return of 75 bps.
White Paper Structured Products: Performance, Costs, and Investments
Measuring the performance of structured products, the investment opportunities and caveats,
and, in particular, the costs investors have to bear, is not a straightforward task. Structured
products differ substantially from each other in their payoff structures and risk profiles; and
even within their various categories they are extremely heterogeneous. Any discussion of their
pros and cons needs to consider this diversity.
This study empirically investigates structured products in the Swiss market with a special
emphasis on barrier reverse convertibles, bonus certificates, capital protection certificates, and
similar products, mostly with Swiss stocks as underlying assets. The results show that these
products have a very low probability of generating a loss when markets are behaving in a
normal fashion, that their performance can become negative when the underlyings are under
pressure, and that their TERs, including distribution costs and net margins, are in the range of
half to about one and a half percent.
What these figures do not show, however, is that these products appeal to investors for different
reasons. They have very particular risk profiles, and they can cater for applications where
solutions are needed: for investors who have strong opinions about maximum shortfalls and
expectations about direction movements in the markets, for investment vehicles in the forefront
or the wake of special economic events, and so on. This makes it difficult to benchmark these
products and even to compare them to each other. Also, many of the traditional risk-adjusted
performance measures are not useful when the magnitude and likelihood of downside risks
differ so substantially from those of upside risks.
What these figures do show, however, is the increased attention these products have received,
and there is no reason to assume that this will change in the near future. This emphasizes all the
more that a careful analysis and understanding of the workings and potentials of structured
products is necessary, and perhaps even points to a need for special indicators and evaluation
White Paper Structured Products: Performance, Costs, and Investments
Bradbury, M., T. Hens, and S. Zeisberger. Improving Investment Decisions with Simulated Experience. Review of Finance,
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... They obtained an average overpricing of at least 3.4% and indicated that the overpricing is positively related to the coupon level; investors tend to overweight the sure coupon and underestimate the risk. Maringer, Pohl and Vanini (2015) ( [15]) empirically investigated structured products, particularly barrier reverse convertibles, bonus certificates, capital protection certificates, and similar products, mostly with Swiss stocks as underlying assets. Their results show that these products have a very low probability of generating a loss under normal market condition, but their performance can become negative when the underlying assets are under pressure. ...
Full-text available
Structured Products are popular financial products for retail investors in many financial markets including the United States and Europe; especially in the Swiss, German and Danish markets. A number of studies have appeared on the mispricing of these products, and a few studies on valuation methods and the performance of these products. The studies on mispricing have consistently demonstrated that structured products are significantly overpriced. In addition, there is some evidence indicating poor performances in the US market. This work contributes to the literature by investigating the pricing and performance of struc-tured products issued in the Australian market. We calculated the fair pricing and the actual returns of fifty eight (58) structured products issued on various dates ranging from 2002 to 2013 with various terms ranging from six months to six years. These products consist of eighteen (18) different payoffs, ranging from bonds to many complex exotic types. We compared the theoretical prices and the issue prices of the products and found significant overpricing of 4.74% on average. The actual annualized excess returns are only 1% on average. Furthermore, we find that the complexity and overpricing of the structured products are positively related, and the relative price differences of the products are negatively correlated by their returns.
... The literature considers that structured products are not all equal (see, for example Nicolaus, 2010;Kiriakopoulos and Mavralexakis, 2011;Maringer et al., 2015) and that demand is strongly influenced by product characteristics that should not matter to a rational investor (Nicolaus, 2010). In this section, we test whether different investors invest and trade in different types of SRP (CLN -Credit Linked Notes; CRT -Certificates; ETF -Exchange Traded Funds; CB -Convertible Bonds; WAR -Warrants). ...
Structured retail products (SRP) are one of the most visible faces of financial innovation and are becoming increasingly popular amongst retail investors. However, there is strong consensus that retail investors' preference for structured products is difficult to explain using the standard rational theory, those products being in general sold at a significant premium. Studying the actual trading behavior of individual investors we provide evidence consistent with the view that SRP likely offer value to some informed investors compared to other products, and that SRP allow investors to access segments otherwise not available to them. Nonetheless, our results also suggest that the increasing popularity of SRP is deeply related to investors' behavioral biases, particularly overconfidence and gambling.
Full-text available
We analyze the investment behavior of private clients with regard to retail structured products. To ascertain their stated and revealed preferences, we use a questionnaire and a field experiment. The real product issued in the field experiment is comparable to the hypothetical product in the questionnaire in terms of both payoff and communication. We find that a product described in simple words strongly motivates people to invest in structured products for the first time, and also eliminates gender differences. However, the real product attracts far fewer first-time buyers than we expected from the questionnaire results.
This paper studies the cost structure and pricing efficiency of principal protected notes (PPNs) from the Danish retail market. Our data set consists of detailed information on almost 400 Danish issues of PPNs during the period from 1998 to 2009. Comparing actual offer prices with theoretical fair values we find that on average PPNs are overpriced by about 6%. While overpricing of structured retail products is well-documented in the literature, our paper is the first to compare the level of overpricing with the product costs disclosed by sellers at issuance. We find that on average only about half of the overpricing can be explained by disclosed product costs. The finding of a significant hidden cost component in structured retail products is new to the literature. At the individual instrument level we find time to maturity and indicators of product complexity to be important determinants of costs and of the degree of overpricing, but other factors such as arranger and issuer size play a part as well. The degree of overpricing of PPNs has declined over time, but the unexplained cost component - hidden costs - has not.
The offering prices of 64 issues of a popular retail structured equity product were, on average, almost 8% greater than estimates of the products' fair market values obtained using option pricing methods. Under reasonable assumptions about the underlying stocks' expected returns, the mean expected return estimate on the structured products is slightly below zero. The products do not provide tax, liquidity, or other benefits, and it is difficult to rationalize their purchase by informed rational investors. Our findings are, however, consistent with the recent hypothesis that issuing firms might shroud some aspects of innovative securities or introduce complexity to exploit uninformed investors.
We study the pricing of reverse convertible (RC) bonds. These are bonds that carry high coupon payments. In exchange, the issuer has an option at the maturity date to either redeem the bonds in cash, or to deliver a pre-specified number of shares. We find that Dutch plain vanilla and knock-in reverse convertible bonds are, on average, overpriced by almost 6%. This overpricing is confirmed in a model-free analysis with respect to option- and bond- pricing models. We find that rational factors explain 23% of the documented overpricing. In addition, we find that the combination of financial marketing, framing, and the representativeness bias further increases our ability to explain the documented overpricing to more than 35%.
Risk and Return for Retail Investors
  • Structured Esma
  • Products
ESMA, Structured Products. Risk and Return for Retail Investors, Economic Report No. 1, Retailisation in the EU, European Securities and Markets Authority, Paris, 2014.
Die Welt der Strukturierten Produkte. Das Buch zur SVSP Swiss Derivative Map
  • M Meier
  • D Sandmeier
Meier, M. and D. Sandmeier, Die Welt der Strukturierten Produkte. Das Buch zur SVSP Swiss Derivative Map, 2012.
Visual Representation and Observational Learning in Asset Market Bubbles
  • T Cason
  • S Samek
Cason, T. and S. Samek., Visual Representation and Observational Learning in Asset Market Bubbles, Purdue University, 2014.
  • M O Rieger
  • M Wang
  • T Hens
Rieger, M. O., Wang, M. and T. Hens, Risk Preferences around the World, Management Science, 2014.
Improving Investment Decisions with Simulated Experience. Review of Finance
  • M Bradbury
  • T Hens
  • S Zeisberger
Bradbury, M., T. Hens, and S. Zeisberger. Improving Investment Decisions with Simulated Experience. Review of Finance, 2014.
Overpricing and Hidden Costs of Structured Bonds for Retail Investors, Evidence from the Danish Market for Principal Protected Notes, mimeo
  • P Jorgenson
  • H Norholm
  • D Skovmand
Jorgenson, P., Norholm, H. and D. Skovmand, Overpricing and Hidden Costs of Structured Bonds for Retail Investors, Evidence from the Danish Market for Principal Protected Notes, mimeo, 2011.