Citi Guide to Structured Product Terminology
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Transcript of Citi Guide to Structured Product Terminology
The Guide to Structured Product Terminology
Originally published in Structured Products magazine
p. 2 Autocallable
p. 4 Lookback
p. 6 Outperformance
p. 8 Individual Cap
p. 10 Total Return vs. Price Return
p. 12 Quanto-style Options
p. 14 Rainbow
p. 16 Custom Indexes
p. 18 Tailored Protection
p. 20 Secondary Market
p. 22 Range Accrual
p.2 Autocallable
p.4 Lookback
p.6 Outperformance
p.8 Individual Cap
p.10 Total Return v.s Price Return
p.12 Quanto-style Options
p.14 Rainbow
p.16 Custom Indexes
p.18 Tailored Protection
p.20 Secondary Market
p.22 Range Accrual
The Guide to Structured Product Terminology
Times are changing. Retail and high-net-worth investors are
increasingly seeking investments that offer interesting ways to
generate attractive yield. They are also willing to consider products that
offer alternatives to traditional equity investments and, therefore, are not
necessarily looking for full principal protection. And, as a result, yield-
enhancing products, such as the auto-callable structure, have been winning
fans across Europe. Here we examine how such products work.
The definitionAn auto-callable (or ‘auto-call’) product is essentially a market-linked
investment, which can automatically mature prior to the scheduled maturity
date if certain predetermined market conditions are achieved.
The criterion for deciding whether the product is automatically matured
(‘auto-called’) is whether the underlying reference index is above a
predetermined trigger level (the ’auto-call barrier’). This auto-call test is
usually carried out on a set of predetermined dates (for example, annually,
quarterly, etc.) specific to that particular investment product, so that the
product can only mature on one of these ‘auto-call dates’. The underlying
reference index will typically be an equity index, but it can also be linked to
stocks, basket of stocks, funds, etc.
If a product is auto-called, the investor normally receives a predetermined
coupon along with the capital redemption on that auto-call date. That
coupon is typically proportional to the length of time from the start date to
the auto-call date.
Most auto-call products incorporate a protection feature so that, if the
auto-call trigger has not occurred before the scheduled maturity date,
capital is fully protected provided the underlying has not fallen below a
certain level (‘the protection level’) during the term of the investment. Only
if the underlying has fallen below that protection level, and the product
has not been auto-called prior to maturity, will investors be exposed fully to
the downside of the underlying market at maturity.
Behind the scenesFigure 1 demonstrates how a plain vanilla auto-callable product linked to
an index operates.
In this example of a five-year auto-call investment, the auto-call barrier is
100%. Therefore the product will auto-call if the underlying index is above
its original start level on any of the five annual auto-call dates.
The coupon payable is X% if the product is auto-called on the first auto-
call date, two times X% if the product is auto-called on the second date and
so on up to and including the maturity date. Its important to note that the
auto-call barrier condition is also tested on the maturity date.
At maturity, if conditions for an auto-call have not already been met,
then the investor is long the underlying index but with the benefit of full
capital protection, provided the underlying index has not fallen below the
protection level during the term of the investment.
If the underlying index ever traded below the protection level during
the term of the investment, then the capital protection no longer applies
and the redemption will be equal to the index performance over the life of
the investment.
Product rationaleAuto-call investment products offer investors the opportunity for a high
coupon linked to the performance of the underlying index. The coupon
is usually higher than the auto-call barrier, so that investors can achieve
Citi believes that product education is vital for the continued success of the structured investment product market. Kicking off its new column, which will
discuss a wide range of structures, Citi explores what are commonly referred to as ‘autocallable’ investment products
1. Example of vanilla auto-callable structure
Example : coupon = X% maturity(T) = 5 years
t= 1 t=2 t= 3 t=4 T= 5t= 0
1
2
3
100% capital + 4
100% capital + 5 x coupon X%
Maturity
Auto-calllevel 100%
Protectionlevel P%
100% capital +
no coupon
Long underlying+
no coupon
100% capital +
(n) x coupon
-
100% capital + x coupon X%
100% capital + x coupon X%
100% capital + x coupon X%
x coupon X%
the investment proceeds and the potential coupon are accrued for the next auto-call date
call date (t),When underlying < auto-call level at each auto-No early redemption, No coupon payment :
>
The Guide to Structured Product Terminology
Autocallable
Autocallable
The Guide To Structured Products Terminology
2
attractive returns for small movements in the underlying index.
If a coupon is not paid, because the auto-call barrier has not been
achieved by the underlying index on an auto-call date, then the investor gets
the opportunity to recoup the missed coupon on the next auto-call date.
In addition, the protection level ensures that the investment is
conditionally protected. If the underlying does not fall below the protection
level, investors will receive at least the full principal amount back at maturity.
Scenario simulationsWith each structure we examine in this monthly column, we will also
provide some simulations designed to show how the product can behave
in certain assumed market conditions. The following simulations are based
on a Monte Carlo approach. The Monte Carlo simulation involves generating
thousands of possible price paths for the underlying index, based on preset
volatility and trend assumptions. The simulation calculates how the product
would have performed using each of those simulated price paths and then
summarises the results. We assume that returns on the underlying single
index follow a process with constant growth rate and volatility.
The example we use here is for a five-year auto-call investment linked
to the Dow Jones EURO STOXX 50® with an auto-call barrier at 100%, a
potential coupon of 9% per annum and a protection level of 60%.
Three hypothetical scenarios are analysed below. Flat market: the growth rate is zero per annum, representing a scenario
with no trend.
Moderate growth market: the underlying has a positive drift of 2.50%
per annum, the trend is positive but weak.
Bullish market: the growth rate for this scenario is equal to 7.50% per
annum, a clear uptrend is assumed.
For each scenario we have assumed a volatility level of 18% per annum,
which is similar to the current implied volatility of the Dow Jones
EURO STOXX 50®.
Parameters of the simulation
In all scenarios, the most likely outcome is that it is auto-called in year one
with a coupon of 9% (the dark-blue segment). If it is not auto-called in
year one, then figure 2 demonstrates the likelihood of it being called in
subsequent years (the remaining lighter-blue segments). The likelihood of
the product lasting until maturity is equivalent to the size of the red and pink
sectors combined in each scenario, with the size of the red sector showing
the probability of losing some portion of capital and the size of the pink
sector representing the probability of the product redeeming 100% capital.
VariationsAs with any popular structure, a number of variations on the original idea
exist. Some of the more commonly seen variations are:
Performance auto-call: The auto-call coupon is not fixed at a specific level
but pays the greater of X% and the actual underlying performance in case
of an auto-call event.
Crescendo auto-call: The auto-call event depends on two underlyings
being above the auto-call barrier. The additional condition on the second
underlying provides additional financing for higher auto-call coupons.
Escalator auto-call: The auto-call barrier decreases each year – increasing
the likelihood of an auto-call event and reducing the probability of capital
at risk.
Bonus plus auto-call: Besides the auto-call coupon, investors receive a
bonus coupon if auto-called early in the life of the product. The effective
per annum coupon is high in early years compared with a standard auto-
call note and reduces towards maturity.
Premium express: The auto-call barrier is below 100% of the initial strike
level aiming to provide a high auto-call probability with full capital protection.
0
10
20
30
40
50
60
70
80
90
100
Flat market Moderate growthmarket
Bullish market
Not auto-called with capital loss atmaturity
Not auto-called with capital protectionat maturity
Auto-called year 5 with 45% coupon
Auto-called year 4 with 36% coupon
Auto-called year 3 with 27% coupon
Auto-called year 2 with 18% coupon
Auto-called year 1 with 9% coupon
%
Financial terms of the hypothetical auto-callable structure
Underlying Dow Jones EURO STOXX 50 ®
Tenor, currency Five years, EUR
Auto-call barrier 100%
Protection level 60%
Auto-call coupon 9%
Flat market Moderate market Bullish market
0% growth rate pa 2.5% growth rate pa 7.5% growth rate pa
3
3
The lookback structures are investment products with a payoff linked
to the maximum or minimum price registered by the underlying asset
during the observed period.
These structures enable the investors to “look back” at the behaviour
of the underlying and to benefit from the most favourable level reached
during the investment period. The embedded lookback options can be
structured in the form of lookback call and lookback put, in order to offer a
bullish or bearish exposure to the market.
The peaks registered by the underlying are considered to define the
level of strike price or to fix the relevant underlying’s price to compare with
the fixed strike price.
On the basis of these criteria, two major categories of lookback options
can be considered: the lookback structures with fixed strike, where the
underlying’s price is the level that will be fixed ex-post, and the lookback
structures with floating strike, where the level of strike price will be fixed at
the end of the investment period.
Behind the scenesFigure 1 shows the mechanism of a lookback call with fixed strike. In this
example of a five-year product, the index drops at the beginning of the
investment period, registers a positive peak at year three and then enters a
bearish trend.
At the end of the investment, the option offers participation in the per-
formance calculated on the maximum value of the underlying. A standard
European call option would have offered a lower performance, considering
only the level registered by the underlying at year five.
Figure 2 shows the mechanism of a lookback call with floating strike. The
index has the same behaviour presented in the previous example. At the
end of the investment, the structure offers participation to the perform-
ance calculated on a strike price equal to the lowest level of the underlying.
A standard European call option would have offered a lower performance,
considering a strike price equal to the initial level of the underlying.
Product rationaleThe powerful concept behind a lookback option is that the investor
has the privilege of benefitting from a favourable market timing for his
synthetic operations of buying or selling the underlying. In the case
of a lookback call option, for example, the investor knows from the
beginning the price at which he is synthetically buying the underlying
(strike price) but he will choose at the end of the option’s life the price at
Market timing can be critical for the success of an investment strategy. What about having a product that will choose the best timing in an automatic way? In this
column, which discusses a wide range of structures, Citi examines how lookbackinvestment products can achieve this objective.
70
80
90
100
110
120
130
140
150
160
0 1 2 3 4 5
Inde
x va
lue
(%)
Year
Level of the index considered
Fixed strike
Performance
70
80
90
100
110
120
130
140
150
160
0 1 2 3 4 5
Inde
x va
lue
(%)
Year
Level of the indexconsidered
Performance
Floating strike
>
The Guide to Structured Product Terminology
Lookback
4
Lookback
The Guide To Structured Products Terminology
4
which he will synthetically sell the underlying. This selling price will be
the highest registered at the observation periods, in order to realise the
maximum profit. The best market timing is automatic selected ex-post,
by observing the underlying behaviour. The “path-dependent” aspect of
the lookback structures provides the investor with protection from the
market’s uncertainties.
Scenario simulationsThe scenario analysis conducted here present the results of simulations
based on a Monte Carlo approach. The process is based on thousands of
simulations, each one generating a specific path for the underlying index,
on the basis of volatility and growth rate assumptions. For each simulation,
the relative payoff is calculated and then results are summarised in order to
obtain the expected behaviour of the structure.
The product considered in this example is a five-year lookback option
with fixed strike, linked to the Dow Jones EURO STOXX 50® and with a
participation rate equal to 70%.
Investors benefit from full capital protection and have an exposure to
70% of the maximum performance of the index based on 10 semi-annual
observations over the five year investment period.
Different hypothetical scenarios are analysed, each one with a specific
combination of volatility and annual growth rate. In terms of growth trend,
three main scenarios are analysed:
Flat market: zero growth rate, no clear trend in the market
Moderate growth market: the underlying has a positive drift of 5%
per annum
Bullish market: a growth rate of 7.5% per annum is assumed
On the volatility side, three scenarios are considered:
Low vol market: the volatility level is equal to 15%
Moderate vol market: the volatility is equal to 20%, in line with the current
implied volatility of the underlying
High vol market: a volatility level of 25% is assumed
The following table summarises the assumptions for the simulation and
shows the average time to market peak for each combination of volatility
and growth rate.
Automatic market timing selection
Distribution of the automatic market timing selection
In a flat growth scenario, the impact of the volatility is less relevant and
the timing of the maximum peak of the underlying performance is around
2.7 years.
Considering higher growth rate equal to 5% per annum, the impact of
the volatility is more evident. In a low volatility scenario, the peak is
registered on average after 3.6 years, while in the highest volatility scenario
the maximum level is achieved a few months before.
In a bullish market scenario, with a growth rate of 7.5% per annum,
the average period that investors need to wait in order to record the
maximum performance of the underlying oscillates between the 3.4
years of the high volatility environment and the 3.9 years of the lowest
volatility scenario.
Average time to observation of market peak
2.5
2.7
2.9
3.1
3.3
3.5
3.7
3.9
0.0% 2.5% 5.0% 7.5%
Volatility at 15%Volatility at 20%Volatility at 25%
Tim
e
Growth rate p.a.
Financial terms of the hypothetical lookback structure
Maturity Five years
Underlying Dow Jones EURO STOXX 50 ®
Currency EUR
Capital protection 100% of the initial invested capital
Participation level 70%
Observation frequency Semi-annual
Growth rate
0.0% 5.0% 7.5%
Positive peak registered after
Volatility
15% 2.7 years 3.6 years 3.9 years
20% 2.7 years 3.3 years 3.6 years
25% 2.7 years 3.2 years 3.4 years
5
5
The definitionOutperformance is an investment product that presents a payout linked to
the differential between the performance of two or more underlyings.
The general market trend is not relevant due to the specific nature
of the derivative component; the option is able to immunise the gener-
ated over-performance from the directional movement of the markets.
Outperformance structured products allow implementing strategies based
on expectations on the growth differential between geographic markets,
asset classes or sectors, and are particularly interesting when uncertainties
regarding the trend of the markets are high.
Behind the scenesThe typical payout associated with an outperfomance investment
product consists of the payment of a fixed coupon or of the actual over-
performance if the target asset performs better than the reference asset at
the relevant observation date. The over-performance is not related to the
global bullish or bearish trend of the market, but depends on the relative
behaviour of the underlying assets.
In case of negative overall market conditions, the coupon is paid if the
target asset loses less than the reference asset.
Product rationaleLet’s consider a product that pays a fixed coupon equal to x% if the return
of the target asset is higher than that registered by the reference asset.
The behaviour of the two assets is observed every year in order to
calculate if the over-performance is realised; the observation is repeated
until maturity.
Thanks to the neutralisation of the market’s directional trend, the struc-
ture can generate positive returns even in bearish scenarios. For example,
in year one, both assets register a negative performance but the target has
a higher value than the reference asset and the investor receives the target
coupon in that year.
At the end of the second and fourth year, the target asset generates
over-performance and the structure pays the fixed coupons for these
years also.
At the end of the third year, the target asset doesn’t achieve its objective,
registering a performance lower than that realised by the second asset and
a similar situation is observed at maturity. The coupon is not paid on these
two coupon payment dates.
Scenario simulationsUsing a Monte Carlo simulation approach, we can estimate the probability of
the target asset beating the reference asset and thus generating positive cash
flows for investors.
We consider a five-year product that pays at the end of each year, a
coupon of x% if the over-performance is realised.
Investors will often have a view on the ability of one asset to perform better than another. Outperformance products can be an efficient way to execute such a view,
while neutralising risks to overall market direction
1. Example of outperformance structure
60708090
100110120130140150160170180
0 1 2 3 4 5
Target asset
Reference asset
Year
Und
erly
ing
valu
e (%
)
Financial terms of the hypothetical outperformance structure
Maturity Five years
Underlying Target and reference assets
Currency EUR
Capital protection 100% of the initial invested capital
Annual coupon Digital coupon, paid if outperformance is realised
The Guide to Structured Product Terminology
Outperformance
6
Outperformance
The Guide To Structured Products Terminology
6
Parameters of the simulations In the analysis presented here, different hypotheses on annual growth rate
and correlation are considered for the underlying assets. The expected
behaviour of the outperformance structure is simulated in order to observe
the average frequency of coupons paid. The annualised volatility level of the
two assets’ returns is assumed equal to 15% and the correlation between their
returns is set at 80%.
Figures 2 and 3 represent the average number of coupons paid during
the hypothetical life of a five-year investment associated with each growth
rate’s level.
For example, given a growth rate of 7.5% per annum for the target asset
and a growth rate of 5% for the reference asset, the investment offers, on
average, more than three coupons during the five years of investment.
By reducing the correlation between assets’ returns from 80% to 50%, it
is possible to observe how the average number of paid coupons is affected.
If the same growth rate is assumed for the target asset and the reference
asset, the change in correlation doesn’t have any effect.
The analysis shows that lower correlation between the two assets in-
creases the likelihood of coupons occurring by ‘chance’ in scenarios that are
typically negative for the structure, but decrease the likelihood of coupons
occurring in scenarios that are typically positive for the structure.
VariationsThe basic outperformance payout can be developed in order to create more
sophisticated structures that are able to offer a linear participation to the
over-performance registered by the target index. There are also variations that
are based on the behaviour of three or more underlying assets. Here are some
of the most common variations.
Variation 1
The digital coupon’s amount paid when the over-performance occurs is not
fixed, but linearly reflects the realised over-performance.
Variation 2
The investor receives, at relevant payment date, the highest amount between
a conditional fixed coupon and a participation in the over-performance
realised during the observed period.
Variation 3
The coupon’s amount is linked to the number of underlying assets that
perform better than the reference asset.
2. Correlation equal to 80%
0.0
0.51.0
1.5
2.02.5
3.03.5
4.0
4.55.0
0.00% 5.00% 7.50%
0% growth rate of reference asset
5% growth rate of reference asset
7.5% growth rate of reference asset
Ave
rage
num
ber o
f cou
pons
rece
ived
Growth rate of target asset
3. Net e�ect of correlation change to 50%
- 0.5
- 0.4
- 0.3
- 0.2
- 0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.00 (%) 5.00% 7.50%
Net
e�e
ct o
n th
e av
erag
e nu
mbe
r of
coup
ons
rece
ived
Growth rate of target asset
0% growth rate of reference asset
5% growth rate of reference asset
7.5% growth rate of reference asset
7
7
The definitionStructured products with an individual cap call payout are investment
instruments that offer an enhanced exposure to a portfolio of underlying
assets. The individual cap represents a pre-defined limit imposed in each
single asset’s performance. The payout of the structured product is equal to a
participation in the growth of the underlying basket, taking into account the
performance cap.
The buyer of an individual cap structure assumes a leveraged position
on the underlying assets’ growth, with a limit on the upside potential.
This synthetic exposure corresponds to a long position in the underlying
basket and to a short position in each single asset’s performance above
the cap.
The investors become a ‘writer’ of a call option on each asset with a
strike equal to the cap level. The premium obtained by the short position
on this series of call options finances a higher participation in the perform-
ance of the basket.
Behind the scenesThe typical use of individual cap is to obtain higher leverage on the underly-
ing growth, by assuming the risk of losing the performance generated above
a specific cap level by each asset composing the underlying portfolio.
The structure can be particularly interesting when the investor expects
a moderately positive trend for the underlying basket of assets and a rela-
tively high correlation between the components of the basket.
Product rationaleLet’s observe a structure that offers an exposure to the growth of the
basket over a five year investment period; the structured product offers full
capital protection for the amount initially invested. The underlying basket
is composed of five assets and each is capped at 175% of its initial value.
In this example, Asset 1 and Asset 2 register a final value higher than the
cap level and are therefore considered at the fixed value of 175% in the
basket’s performance calculation; the remaining three assets are observed
at their respective final value. The individual cap basket registers a lower
value than the uncapped basket in any scenario where at least one of the
assets reaches a final value higher then the fixed cap level.
However, the individual cap call option is cheaper to purchase than
uncapped call on the same basket and therefore provides for structured
investments with higher participation. This can allow for better returns
overall, even in cases where some of the components perform better than
the cap level.
Scenario simulationsUsing a Monte Carlo simulation approach, we can observe the average
payout of an individual cap call and compare it to the performance of an
uncapped call under various sets of volatility and correlation assumptions.
For the purposes of this simulation, we consider fully capital protected
structured products, linked to a basket of five equity stocks with a maturity
of five years. The leveraged exposure to the growth is equal to 155% for the
individual cap version and 110% for the uncapped version.
Structured products based on individual cap call options allow the investor to assume potentially higher exposure to the performance of the underlying
basket, by accepting a limit to the maximum gain associated to each basket’s component
1. Values observed at maturity
Uncapped basket
0%
50%
100%
150%
200%
250%
Asset 1
Asset 2
Asset 3
Asset 4
Asset 5
Asset 1
Asset 2
Individual cap basket
Asset 3
Asset 4
Asset 5
The Guide to Structured Product Terminology
Individual Cap
8
Individual Cap
The Guide To Structured Products Terminology
8
2. Payout at maturity
135%
137%
139%
141%
143%
145%
Vol 15% Correl 20%
Vol 15% Correl 50%
Vol 20% Correl 20%
Vol 20% Correl 50%
Individual cap Uncapped
Ave
rage
pay
out a
t mat
urity
Parameters of the simulations In the simulations four different combinations of volatility and correlation are
considered: annualised volatility of 15% and 20% for each stock and average
correlation of 20% and 50% for the basket and growth rate of 5% per annum.
The value of the individual cap basket is then compared to the value of
the uncapped basket in order to calculate the payout of the individual cap
call and of the uncapped call.
The following graph represents the average payouts at the end of the
life of a five year hypothetical investment associated with each set of vola-
tility and correlation assumptions.
For example, given a volatility of 15% for each stock and an average cor-
relation between pairs of stocks equal to 20%, the individual cap structured
product offers an average overperformance of more than 6%, thanks to the
higher participation rate to the growth of the basket.
Clearly, a market environment characterised by low volatility will
represent a favourable condition for individual cap structured products to
perform better than uncapped call structures.
Both structures are positively affected by an increase of correlation.
However, the individual cap structure benefits more from the higher cor-
relation assumptions of simulations here presented.
VariationsThe individual cap call payout can be structured in different variations; here
are presented some of the most common.
Variation 1
The premium amount received by imposing cap on the performance of the
asset is used to finance floors on the single performance of the basket, in
order to mitigate the effect of adverse market scenarios.
Variation 2
The cap level is fixed on the average basket’s performance; the premium
received is generally lower than the one obtained by selling a call on each
single underlying asset.
Variation 3
The premium linked to individual cap is not invested to finance a higher
participation to the individual cap basket but to generate fixed coupons
paid to the investor during the product’s life.
Financial terms of the hypothetical individual cap call structure
Maturity Five years
Underlying Five equity stocks
Currency EUR
Capital protection 100% of the initial invested capital
Final payout 155% of the individual cap basket’s growth
Individual cap 175% of the initial asset’s value
9
9
The definitionThe two common approaches in terms of the dividend treatment of
equity indexes are (i) the reinvestment of dividends as they are paid by the
relevant companies; or (ii) the disregard of this cash flow for index return
calculation purposes. The former describes a total return index; the latter a
price return index.
The dividend yield is one of the main components in determining the
price of a structured product, and the choice between a total return index
or a price return index can have an impact on the price of the structure. In
the case of a structured product offering exposure to the growth of a price
return index, the investor will benefit from a higher participation rate. The
same structure linked to a total return index will have a lower participation
rate, due to the higher cost of purchasing the option offering the exposure
in the appreciation of the index (call option). Dividends paid will be
reinvested in the index and, therefore – assuming that all or some of the
underlying stocks pay a dividend – the performance of a total return index
will be higher than the price return version of the same index.
Behind the scenesThe two major factors that could affect the investor’s choice between a
total return index or its price return equivalent are his/her willingness to
have a direct exposure to the dividend cash flows paid during the life of
the product and the level of growth expected for the underlying index.
In the case of a total return index, the dividends effectively paid and
reinvested will be entirely reflected in the value of the index. The investor
will benefit from the dividend capitalisation, while assuming the risk of
receiving lower-than-expected dividend cash flows.
In the price return structure, the investor is basically hedging his exposure
to dividends: if the amount of dividends paid is higher than expected, the
investor will lose the opportunity of extra return but, in the case of a lower-
than-expected dividend cash flow, the investor will be protected. The call
option on the total return index will be generally more expensive.
The level of participation in the growth of the total return index is
generally lower than the level of participation in the growth of the price
return index. However, the outperformance generated by dividend
reinvestment tends to compensate for the effect of a reduced participation
in the growth in scenarios where the realised growth rate is low or moderate.
Product rationaleWe can consider two structures that offer exposure to the growth of an
equity index over a five-year investment period; the product is designed to
offer, at maturity, full protection of the amount initially invested.
The participation rates in the growth of the total return index and price
return index are calculated considering an annualised volatility of 20% and an
expected dividend yield of 3.50%. A first hypothetical structure linked to the
total return index offers a participation rate of 77% in the growth of the index
over the five years. A second structure, linked to the price return version of the
same index, offers higher participation in the growth of the index, equal to
115%. The total return index outperforms the price return index by an amount
equal to the final value of dividends reinvested in the index. In this scenario,
the payout at maturity of the two structures is equal; the lower participation
in the growth of the total return index is offset by a higher performance of the
index compared with that of the price return index.
The performance of structured products can be affected by the way dividends are treated in the underlying equity index calculation. The investor can choose to assume a direct exposure to the dividend flow effectively paid by the stocks composing an index
by opting for structured products linked to the growth of a total return equity index
1. Total return versus price return index
80%
90%
100%
110%
120%
130%
140%
150%
160%
170%
180%
0 1 2 3 4 5Year
Price Return Index Total Return Index Payout of the two structures
The Guide to Structured Product Terminology
Total Return vs. Price Return
10
Total Return vs. Price Return
The Guide To Structured Products Terminology
10
Scenario simulationsUsing a Monte Carlo simulation approach, we can compare average
payouts under different dividend yield and growth rate assumptions and
observe how the choice between a total return and a price return index
could affect the product’s payout at maturity.
In the first step of the analysis, a fixed growth rate is considered and
average payouts at maturity are simulated on the basis of different
assumptions on the realised dividend yield. In a second step of the analysis,
the dividend yield is considered fixed and three different growth rates are
assumed in order to simulate final payouts.
For simulation purposes, the annualised volatility is assumed to be 20%
for both indexes and the growth rate is set at 4.72%, reflecting the level
used to calculate the participation rates for the two structures. In order to
observe the effects on the final average payouts, the realised dividend is
set equal to 2.5%, 3.5% and 4.5%, respectively.
Final average payouts corresponding to each dividend yield hypothesis
are simulated and compared for the two structures. Figure 2 represents
the average payouts at the end of the life of a five-year hypothetical
investment associated with each set of dividend assumptions.
Given a hypothetical scenario in which the realised dividend yield is
equal to 2.50%, the investment in the structured product linked to the price
return index would have generated a higher return on average, offering the
investor an outperformance in respect to the structure linked to the total
return index. Given a dividend yield of 3.5%, equal to the level assumed in
the pricing, average payouts of the two structures present similar levels.
Conversely, in a scenario where the dividend yield is higher (4.5%), the
investment in the structure linked to the total return index would have
been more profitable for the investor. This structured product linked to the
total return index would have offered, in this scenario, participation in the
realised growth of the dividends reinvested in the total return index, greater
than the dividend income of 3.5% estimated in the pricing.
The final payout of the structured product linked to the price return index
is not affected by the amount of dividends effectively paid. Keeping the same
volatility assumption and under the hypothesis of a realised dividend yield
equal to the level of 3.5% assumed in the pricing of the two structures, it is
possible to observe the effect of changes in terms of growth rate.
The results of the simulation show that, for a small reduction in terms
of the growth rate, a structured product linked to the price return index
registers a larger decrease in terms of performance compared with the
equivalent product linked to the total return index, which registers only a few
basis points change in terms of average payout. An increase in the growth
rate produces a better performance in both of the structured products, with
a slight outpeformance for the structure linked to the price return index.
The investment in a structured product linked to the growth of a price
return index will tend to provide, on average, the same expected return as
the one offered by the investment in a structured product linked to the
growth of the total return version of index if the realised growth rate and
the realised dividend yield reflect the same levels considered in the pricing.
In scenarios where the realised dividend yield is higher than the level
assumed in the pricing model, and the realised growth rate is equal or
lower than the level considered in pricing, the investor in a structured
product linked to the growth of a total return index will tend to benefit
from higher returns. The effect will be the opposite when the dividend
yield is lower than the level assumed in the pricing model and the realised
growth rate is equal to or higher than the level considered in pricing.
Considering a realised dividend yield equal to the level assumed in
pricing, the increase of the realised growth rate will have a stronger
positive effect on the payout of the structured product linked to the
growth of a price return index, thanks to the leverage offered by the higher
participation rate in the growth of the underlying index.
2. Average payout at maturity
156%
154%
152%
150%
148%
146%
144%DivYield2.50%
DivYield3.50%
DivYield4.50%
Price return index-linked Total return index-linked
Ave
rage
pay
out a
t mat
urity
Growth rate of 3.72%
Growth rate of4.72%
Growth rate of5.72%
Price return index-linked 144.23% 150.06% 156.31%
Total return index-linked 144.96% 150.05% 155.44%
A. Financial terms of the hypothetical structures
Total return Price return
Maturity Five years Five years
Underlying Equity Total Return Index Equity Price Return Index
Currency EUR EUR
Capital protection 100% of the initial invested capital
100% of the initial invested capital
Final payout 77% of the growth of the index
115% of the growth of the index
11
11
The definitionQuanto-style options (quantos) are options where the currency of the
payout is different to the currency of the option’s underlying. For instance, a
EUR quanto-style call option on the Nikkei index has a payout based on the
performance of the Nikkei, itself measured in YEN, but the currency of that
payout is in EUR.
Quanto options are very useful for investors who want to gain exposure
to the performance of an underlying whose currency is different to their
reference currency. For instance, investors who have portfolios denomi-
nated in EUR but want to gain exposure to the performance of the Nikkei
via call options could buy vanilla call options on the Nikkei. But, in doing
so, investors will have to convert some of their EUR funds into YEN, buy
an option on the performance of the Nikkei, receive the payout in YEN
and convert the YEN back into EUR. Investors will therefore be exposed
to foreign exchange (FX) risk in the process of converting YEN back into
EUR at maturity. A quanto option will precisely provide an investor with a
payout in EUR on the performance of the Nikkei (measured in YEN), thereby
eliminating any FX risk of converting funds back and forth.
Behind the scenesThe major reason an investor may seek a quanto is to hedge out any FX
risk. By buying a quanto option, investors receive a payout in the currency
of their choice.
The relative costs of vanilla and quanto-style options depend on
several factors. First, the interest rates of the underlying currency (in our
example the YEN) versus the option currency (in our example EUR) will
influence the respective forwards. The plain vanilla option funding rate
will come from the underlying currency rate (YEN). The quanto will be
funded in the option currency (EUR). Secondly, the correlation between
the volatility of the underlying (Nikkei index) and the FX rate (EUR/YEN)
will greatly influence the value of the quanto as the seller of this option
will have to trade dynamically in both the underlying itself (i.e., the
Nikkei) and the currencies.
Depending on the relative values of the interest rates and the
correlation between the underlying and the FX rate, the quanto option can
be valued either at a premium or at a discount to the vanilla option.
Product rationaleThe main product rationale is for the investor not to take any FX risk. It also
provides the advantage of avoiding currency changes (and conversion
costs), paying off investors directly in the currency of their choice. For
simplicity, we compare here the different payouts of the quanto and
the vanilla option. Because EUR rates are higher than YEN rates, the
discounting effect will tend to make the quanto option cheaper than the
corresponding vanilla. However, the correlation priced between the Nikkei
performance and the EUR/YEN FX rate will also drive the forward of the
quanto and therefore impact the relative costs of the quanto versus the
vanilla option.
Scenario simulationsUsing a Monte Carlo simulation approach, we can compare average
payouts under different growth rate assumptions for either the underlying
(i.e., the Nikkei) and the EUR/YEN FX rate.
Fluctuations in foreign exchange rates can be critical to the success of an investment strategy. What about having a product that will eliminate the FX risk when investing in
a foreign underlying? In this column, Citi examines how quanto-style options can achieve this objective
1. Assumption – Nikkei growth rate of 0% per annum
115.0
120.0
125.0
130.0
135.0
140.0
145.0
150.0
-5% 0% 5% FX rate mvt
Quanto option payout Vanilla option payout
Aver
age
payo
ut
The Guide to Structured Product Terminology
Quanto-style Options
Quanto-style Options
The Guide To Structured Products Terminology
12
For simplicity of analysis, we assume a constant participation rate
for both the quanto and vanilla options. The annualised volatilities are
assumed to be 20% for the equity index and 7.5% for the EUR/YEN FX
rate with an annualised correlation of approximately -25% between the
two. The assumed yearly growth rates for both the Nikkei index and the
EUR/YEN FX rate are -5%, 0% and 5%, respectively, hence we consider nine
cases in total.
Final average payouts corresponding to each case are simulated and
compared for the two structures. Figure 1 represents the average payouts
at the end of the life of a five-year hypothetical investment associated with
our assumptions.
Given this hypothetical scenario in which the Nikkei growth rate is equal
to 0%, the investment in the vanilla option payout would have generated
a higher return on average, offering the investor an outperformance in
respect to the quanto, if the FX rate had depreciated, i.e., if the underlying
currency (YEN) had appreciated versus the derivative currency (EUR). A
similar – though much less pronounced – effect would be obtained for
no growth in the FX rate. However, in a scenario where the FX rate would
appreciate by 5% annually, the investment in the quanto would be more
profitable for the investor (as the depreciation of the YEN versus the EUR
would hurt significantly the conversion of YEN received from the vanilla
option back into EUR).
It is worth noting that, in all cases, a higher average payout will yield a
higher standard deviation of returns. Also, an increase in the Nikkei growth
rate produces a better performance in both the quanto and vanilla payouts
(as one would expect, given a stronger appreciation of the Nikkei will yield
higher payouts in both cases). However, the relative outperformance of
quanto versus vanilla increases with an increasing Nikkei growth rate in the
case of a 5% FX movement.
On average, an investment in a quanto-style structured product will
tend to provide an expected return comparable to the vanilla structured
product when there are no significant FX changes.
VariationsOther structures can also be considered, such as American Depositary
Receipt (ADR)-style options. The payout of an ADR-style option will
be based on the product of the underlying and the FX rate in the final
performance calculation. It is different from either a quanto or a vanilla
option. For instance, suppose the underlying appreciates by 10% but the
FX depreciates by 20%, our at-the-money vanilla call would pay 10% Nikkei
appreciation on a YEN notional and the quanto on a EUR notional. But the
ADR-style option will pay nothing as the product of the FX times the Nikkei
level at maturity (80% * 110% = 88%) will be less than 100% and, hence, the
ADR-style option will expire worthless.
B. 0% equity index growth
FX rate growth -5%
FX rate growth 0%
FX rate growth 5%
Vanilla Average payoutStandard deviation
146%81%
136%63%
128%49%
Quanto Average payoutStandard deviation
133%57%
133%57%
133%57%
2. Assumption – Nikkei growth rate of -5% per annum
106.0
108.0
110.0
112.0
114.0
116.0
118.0
120.0
-5% 0% 5%FX rate mvt
Quanto option payoutVanilla option payout
Aver
age
payo
ut
3. Assumption – Nikkei growth rate of 5% per annum
–
50.0
100.0
150.0
200.0
250.0
-5% 0% 5%FX rate mvt
Aver
age
payo
utQuanto option payoutVanilla option payout
A. Financial terms of the hypothetical structures
Vanilla structure Quanto structure
Maturity Five years Five years
Underlying Nikkei Index Nikkei Index
Currency YEN EUR
Capital protection 100% of the initial invested capital
100% of the initial invested capital
Final payout 120% of the growth of the index
120% of the growth of the index
13
13
The definitionRainbow options, linked to a multiple of underlying assets, cover a wide
variety of payouts; the common denominator is that the exposure to each
underlying is set after an observed parameter has effectively been realised,
usually the performance. Allocation of the specific participation rate to
each underlying asset typically involves a ranking by performance of all
assets at the end of the investment period.
The highest participation rate is applied to the best-performing asset
and decreasing co-efficients are applied to assets that have registered a
lower performance.
The mechanism allows the investor to have greater exposure to
the best-performing underlying and reduced exposure to the assets
generating lower return.
In some variations it is possible to assign a participation rate of zero,
allowing the investor to exclude the underperforming asset from the
portfolio. Additional rainbow option categories can include a negative
participation rate for the worst-performing underlying, generating an
automatic short position.
Behind the scenesTo observe how the rainbow option mechanism works, we can consider
an example from a classic asset management scenario, where the
option’s underlying assets are represented by a long-only portfolio. A
basic rainbow call option allocates the underlying assets as an automatic
optimisation tool, reserving the largest proportion of the portfolio for
the underlying that has registered the best performance, and offering
lower exposure to the worst-performing assets. The allocation is defined
retrospectively when the performance has already been realised, but
is applied to the payout calculation as if the investor had chosen this
favourable allocation at the start of the investment. At the end of the
investment period, the investor will receive participation in this optimised
portfolio. A structured product with capital protection offers the investor
participation in the growth of underlying assets, while protecting the
initial invested capital from adverse market scenarios.
Product rationaleWe can consider a structure linked to the growth of a basket composed
of three indexes, each representative of a different equity market. The
structure has a five-year investment term, offers full capital protection
and is denominated in euros. At maturity, the investor receives 80% of the
growth of the basket, calculated by attributing a weight of 50% to the best-
performing index, a weight of 30% to the second-best index and a weight
of 20% to the worst-performing index. The performance is calculated by
comparing the final value of each index at the end of the investment term
with the initial value observed on the strike date.
In the example presented in figure 1, the best-performing asset registers
a performance of +60% during the five-year investment period, the second
performer increases by 25% and the worst performer decreases by 10%.
The automatic allocation mechanism of the rainbow option allows
the investor to benefit from higher participation in the best-performing
index, reduced exposure to the worst-performing index and moderate
participation in the second-best-performing index.
The indexes are ranked on the basis of realised performance, allowing
a retrospective allocation that is more favourable for the investor than an
equally weighted allocation.
1. Rainbow mechanism
Structured products with a rainbow option payout are investments that offer systematic optimisation of exposure to a basket of underlying assets.The rainbow payout offers
automatic asset allocation, allowing the investor to benefit from higher participation in the best-performing assets and lower or short exposure to the worst-performing ones
Bestperformer
Secondperformer
Worstperformer
-20%
-10%
0%
10%
20%
30%
40%
50%
70% Best performer
Second performer
Worst performereR
alis
eep d
fror
man
ce
60%
Underlying indexes’ performance Example of rainbow automatic allocation
The Guide to Structured Product Terminology
Rainbow
14
Rainbow
The Guide To Structured Products Terminology
14
Scenario simulationsUsing a Monte Carlo simulation approach, we can observe how the
performance of a rainbow call option is affected by changes in volatility
and correlation parameters and compare its behaviour with that of a
simple call option on an equally weighted basket.
For the purposes of this simulation, we consider a fully capital-protected
structured product, linked to a basket composed of three equity indexes
and with a maturity of five years. The investor receives, at the end of the
fifth year, 100% of the initial invested capital plus 80% of the growth of the
rainbow basket.
Parameters of the simulationsInitial correlation parameters are modified in order to observe the impact
on average performance at maturity. A similar analysis is then performed
by changing the levels of volatility.
The average payout of a rainbow call structured product is compared to
the payout of a structured product with an embedded vanilla call option
on the equally weighted underlying basket. Different levels of participation
are assumed in order to have a comparable indicative cost for the rainbow
call and vanilla call options. Figure 2 represents the distribution of average
simulated payouts associated with each set of correlation assumptions.
When realised volatility and correlation values reflect levels considered
in pricing, the average payout of the two structures is similar. In scenarios
characterised by lower correlation between indexes, the rainbow option
tends to outperform the vanilla call on the equally weighted basket.
Conversely, the effect of an increase in terms of average correlation is
positive for the vanilla call and negative for the rainbow call option’s
payout. Assuming levels of correlation equal to values used in the
calculation of participation rates, it is possible to observe the effect of a
change in volatility levels. Figure 3 represents the distribution of average
simulated payouts associated to changes in volatility assumptions.
Both structures are positively affected by an increase of volatility and
negatively affected in a similar way when the volatility is reduced.
VariationsIn the wide range of derivatives defined as rainbow options, we have
selected a few variations that represent some of the most common
structures.
Dynamic exposure – the weights attributed to each underlying asset
are not predefined but depend on the amplitude of the index variation;
the more an index increases, the higher its respective weight.
Asian rainbow – the rainbow allocation process is applied at each
predefined observation date and the investor receives, at maturity,
participation in an average of the basket performance observations.
Profile rainbow – the performances of different asset allocation
schemes, each representing a different risk/return profile, are observed
at maturity and then ranked on the basis of realised performance. The
investor receives higher participation in the best-performing allocation.
3. E�ect of changes in volatility
Structured 80% rainbow call
Structured 100% vanilla call
-3.00% Unchanged +3.00%
136.0%
124.0%
126.0%
128.0%
132.0%
134.0%
122.0%
vAresbo egare
ytirutam ta tuoyap dev
130.0%
120.0%
2. E�ect of changes in correlation
130.0%
127.5%
128.0%
128.5%
129.0%
129.5%
127.0%-20.00% Unchanged +20.00%
Structured 80% rainbow call
Structured 100% vanilla call
vAresbo egar e
r ut am t a t uoyap dev
ity
A. Financial terms of the hypothetical rainbow structure
Maturity Five years
Underlying Three equity indexes
Capital protection 100% of the initial invested capital
Final payout 80% of the Rainbow basket’s growth
Exposure to best
Exposure to middle
Exposure to worst
15
15
The definitionCustom equity indexes allow investors to implement a specific investment
rationale and/or gain tailored exposure to particular elements of the equity
markets. For example, a custom index may focus on certain geographic
markets, sectors or investment themes or it may implement a quantitative
investment model. Custom indexes may be developed from scratch on a
stand-alone basis or they may be variations of existing equity indexes that
are devised to fine-tune risk return parameters.
The customisation process is highly flexible, both in the selection of the
initial elements comprising the index and in the definition of the rules that
govern changes in the index composition over time. Accordingly, unlike a
traditional equity index, a custom equity index may be designed to react
to certain market conditions, providing for the index composition to adjust
according to preset rules.
At the same time, the typical end-result of the customisation process
is an index that offers transparency, diversification and efficiency in the
transaction process, just like a traditional equity index. Therefore, unlike
a managed fund where the manager can unilaterally decide to change
strategy at will (or can even be replaced), a custom equity index will ensure
an allocation methodology that remains constant throughout the life of
the product.
Behind the scenesA custom index can provide exposure to a particular geographic market or
business sector by selecting stocks from a universe that represents the target
equity segment. It may also focus on implementing an investment strategy
or theme, such as long/short exposure, call overwriting or momentum-driven
investment. In addition, the composition rules can ensure that the desired
exposure and/or strategy are appropriately maintained over time.
Custom indexes usually aim to offer investors the advantages of
customised exposure along with the benefits of a transparent investment
process. They are built to suit specific investor views and offer them preset
investment rules that implement their views over time. At a basic level,
investors can obtain exposure to the investment rationale with a simple
long-only investment in the custom index.
A further level of customisation can be offered through structured
products, which allow investors to benefit from efficient risk reward
profiles through a combination of both customised underlyings and
customised payoffs.
Citi offers a wide range of structured product payouts including capital
protected or capital at risk, income products or products that focus on
delivering exposure to the growth or even leveraged exposure to the
selected custom index. Custom indexes can also be included in a basket
with other underlyings or they may be used for alpha generation – for
example, through going long the custom index and short a traditional
equity index.
Product rationaleFigure 1 provides an example of a simple structured product over the Citi
Climate Change Index (CECCP Index).
The CECCP Index reflects the performance of a basket of stocks selected
from a universe of companies that have the potential to benefit from
climate change. The stocks constituting the universe are selected by
Citi Investment Research (CIR). The universe may comprise, for example,
stocks in companies developing alternative fuels, electric vehicles or
renewable energy technologies. The rationale for developing this index is
that companies that are well-positioned with respect to climate-change-
friendly activities have significant opportunities for economic growth as
Structured products on custom indexes can offer very attractive investment opportunities. Custom indexes are compelling investment propositions in themselves, as each is designed to implement a specific investment rationale. Structured products on custom indexes add another layer of value by offering payouts that allow investors
to tailor products to their own risk return profiles
The Guide to Structured Product Terminology
Custom Indexes
16
Custom Indexes
The Guide To Structured Products Terminology
16
climate change becomes an increasing (political, public and corporate)
concern throughout the developed world and many emerging markets
and creates new niche opportunities.
The CECCP Index benefits from a bottom-up selection process based
on predetermined rules. Figure 1 provides a summary of the simplified
construction methodology of the CECCP Index:
The CECCP Index is rebalanced semi-annually. This construction and
rebalancing methodology enables the CECCP Index to capture growth
from new niches and business opportunities created by climate change.
Hypothetical performanceAn outperformance structure enables an investor to implement the
view that stocks benefiting from the consequences of climate change, as
represented by the CECCP Index, may perform better than other stocks
over the next three years.
By way of example, an outperformance structure linked to the
CECCP Index offers a potential coupon of up to 20% per annum over an
investment period of three years. The payout would be as follows: on each
annual observation date, if the CECCP Index outperforms a predefined
reference equity index, the investor receives a coupon equal to the excess
performance generated by the CECCP Index over the reference equity
index, with an upper limit of 20% per annum. Otherwise, the investor
receives no coupon for that specific year.
At maturity, if the CECCP Index is the best performer of the two indexes,
the final payout is equal to 100% of initial capital invested, plus the value
of the third annual coupon. Otherwise, the investor receives the difference
between 100% and the underperformance of the CECCP Index, with a
minimum guaranteed redemption of 75% of the initially invested capital.
In the hypothetical performance scenario illustrated in figure 2, the
CECCP Index underperforms the reference equity index at the end of the
first year and then outperforms in the next two years.
In this scenario, the investor would receive the maximum coupon of 20%
at the end of the second year and a coupon of 5% at the end of the third
year, in addition to the full redemption of initial capital invested.
Custom indexes offer investors the opportunity to implement a specific
investment rationale (geographic or business sectors and/or investment
strategies) within the framework of a transparent and consistent
underlying portfolio construction and reallocation methodology.
Structured products provide a further element of customisation, allowing
investors to gain exposure to and potentially benefit from tailored
products on custom indexes that can optimise their risk reward profile.
2. Example of outperformance – Custom Index versus Reference Index
180%
170%
160%
150%
140%
130%
120%
110%
100%
90%
80%70%
60%0 1 2 3
Year
av xednIlu
e
Custom Citi Climate Change Index
Reference World Equity Index
1. UNIVERSE Citi Climate Change Universe (approximately 100 stocks, reset every six months)
2. RESEARCH Only stocks rated “BUY” by CIR are eligible FILTERING to be index constitutents
3. STOCK MARKET For example, market accessibility, FILTERING
4. RANKING Ranking of the stocks by market capitalisation
5. GEOGRAPHIC Not more than 18 stocks from the same region DIVERSIFICATION
6. SELECTION Of up to 30 stocks
1. Simpli�ed construction methodology of the CECCP Index
Financial terms of the hypothetical outperformance structure
Maturity Three years
Target index Citi Climate Change Index EUR PR
Currency EUR
Capital protection 75% of the initial invested capital
Participation level 100% of annual outperformance, up to 20% p.a.
Observation frequency Annual
17
17
IntroductionStructured products with full capital protection offer investors a safeguard
against adverse market moves, neutralising any potential erosion of the initial
invested capital. However, the cost of this unconditional protection could
have a strong impact on the overall investment structure. Citi has developed
a comprehensive range of tailored protection profiles to allow investors to
optimise the trade-off between protection and potential performance.
The definitionOne of the advantages of structured products is the capability to protect
the capital invested. The protection can apply to the entire capital or to a
proportion thereof. It can also be applied to any potential cash flows offered
by a product, in the form of fixed coupons or minimum level of performance.
The protection offered safeguards the investor against adverse movements
in the underlying markets; however, in the case of most structured notes, the
investor is exposed to the credit risk of the issuer.
The cost of full capital protection depends on a wide range of factors
and the main impact can be attributed to the relevant interest rates
with regard to the product currency and maturity, as well to the financial
strength of the issuer. The latter factor will determine the spread applied to
relevant interest rates.
When only a proportion of the capital is protected, the money available
to be invested in the derivatives component is higher and this, in turns,
tends to increase the performance potential.
Behind the scenesStructured products offer the capability to provide tailored protection,
which can be, for example, full, partial or conditional.
Product rationaleAs an example, we can consider a simple structured product linked to
the growth of a basket composed of three equity indexes. Each index
represents a specific European market and is equally weighted within
the basket. The investor receives at maturity 105% of the final value of
the basket at the end of the five-year investment period with a minimum
redemption of 100%. It is possible to observe the impact of a lower
protection level by considering a structured product linked to the same
underlying basket but with a minimum redemption of 80% of the initial
invested capital. The multiplier applied to the final value of the basket
increases from 105% to 120%. Figure 1 represents the payout profile of the
two products at maturity.
In the case of the full capital-protected product, the leveraged
exposure to the final basket allows the investor to profit even in flat or
slightly negative scenarios. The 80% protected product offers a positive
performance even if the underlying basket registers a loss of 16.66%.
Conditional protectionAs a further example, we consider a structured product with conditional
protection, which allows the investor to benefit from higher exposure to
Citi’s comprehensive range of structured products with tailored protection has been developed to enable optimisation of trade-offs between protection and performance
1. Examples of unconditional capital protection
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
0% 20% 40% 60% 80% 100% 120% 140%
Underlying basket value at maturity
Payo
ut a
t mat
urity SP 100% capital
guarantee payout
SP 80% capitalguarantee payout
Underlying basket(dividends excluded)
In this example (above) the payout is linked to the basket level at maturity and
not to the basket growth. This allows the product to present positive returns even
in negative scenarios.
The Guide to Structured Product Terminology
Tailored Protection
18
Tailored Protection
The Guide To Structured Products Terminology
18
the market and full protection to their investment, provided that the trig-
ger index doesn’t fall by more than 25%. The investor protects their capital
from adverse moves in the underlying three indexes of the basket but is
accepting exposure to the event of a negative performance of the trigger
index, representing the world equity market.
As an example, let us look at a structure that offers leveraged exposure
of 110% to the final underlying basket value and a full capital protection
of initial invested capital if the trigger index does not register a loss of
more than 25% of its initial value at any time during the life of the product.
If this adverse scenario is realised, the investor maintains their leveraged
exposure to the underlying basket but no longer benefits from a protected
minimum redemption. The underlying basket is the same one considered
for previous structures and the trigger index represents in this example the
global equity market. The leverage offered by the conditional protected
structure (110%) is higher than would be possible for a full capital-
protected structure (105%). However, the investor is assuming a global
equity market risk.
Figure 2 represents the payout profile at maturity of the conditional
protected structured product. The blue line in figure 2 represents payouts
associated with each final level of the underlying basket in a scenario
where the trigger index has not fallen by more than 25% of its initial value
at any time during the investment term. If the trigger index representing
the world equity market registers a loss higher than 25%, the payoff profile
at maturity is the one represented by the orange dotted line.
If the frequency of observations of the world index performance is
switched to a semi-annual basis, the level of participation changes from
110% to 108%. In this case, the world index could register values lower
than the 75% during the six-month period between observation dates and
recover before being observed, without affecting the principal protection;
this advantage for the investor is reflected in a lower level of participation.
SimulationsUsing Monte Carlo simulations, we can examine the probability of the
different structures analysed to deliver a payout lower than the initial
invested capital. For simulation purposes, levels of volatility, correlation and
growth are the same as those used in the indicative pricing model.
Table A presents the probability of receiving a payout lower than
the initial invested capital and the associated potential of performance,
expressed as an average expected payout in scenarios where the final
return is higher than 100%.
Defining the appropriate degree of protection is a critical element
of customisation offered by structured products. Full capital protection
safeguards the investment from adverse market scenarios but tends
to present high costs for the investor. A lower level of unconditional
protection allows a wider proportion of available capital to be invested
in the derivatives component, enhancing the performance potential
versus increased risk exposure to the performance of the underlying. A
conditional protection allows the investor to safeguard their capital from
the risk connected to the underlying performance, while transferring
part of their risk exposure to a different asset, that acts as a trigger for
the protection.
2. Conditional capital protection at maturity
40%
50%
60%
70%
80%
90%
100%
110%
120%
130%
140%
40% 50% 60% 70% 80% 90% 100% 110% 120%
Paity
SP conditional triggerindex >75%
SP conditional triggerindex <75%
Underlying basket value at maturity
A. Average expected payout scenarios
SP 100% protectedSP conditional protected with semi-annual observation
SP conditional protected with daily observation SP 80% protected
lower than 100% 0.00% 30.16% 33.36% 40.18%
Expected average positive payout (scenarios where payout is higher than 100%)
126.01% 140.34% 144.50% 162.60%
19
19
IntroductionThe presence of a liquid secondary market gives investors the comfort of
knowing that they can trade out of a structured product prior to its expected
maturity. The change over time in market factors that affect the value of a
structured product can generate opportunities to sell early in order to realise
profit. Alternatively, an investor may wish to close a position on a structure
that has developed a risk profile that is no longer interesting. Investors
should, therefore, have an understanding of the expected behaviour of the
price of structured product over the term of the investment in addition to
their understanding of the defined payout at maturity.
The definitionEach structured product may have a specific sensitivity to various market
factors, such as volatility, correlation and interest rates. These market
factors are used to determine the price of the structured product on the
strike date.
After the strike date, the product becomes ‘live’ and all of the market
factors relevant to pricing are subject to constant change; in addition, the
‘time’ factor begins to play a role, having a major impact on the present
value of expected future cashflows. Furthermore, the sensitivity of the price
to the various factors shifts over time, altering the way the product reacts
to these dynamic parameters.
Behind the scenesAs a general principle, basic structured products that offer full capital
protection at maturity comprise: (1) a zero-coupon bond component that
protects the minimum redemption amount at the end of the investment
period; and (2) a derivative component that offers the exposure to the
underlying market. If the credit risk of the issuer and interest rates remain
stable, the zero-coupon bond component’s value tends to increase
approaching the maturity date because of the lower discount effect on
the protected cashflows. The zero-coupon bond component is generally
the main contributing factor to the overall value of a capital protected
structured product. It tends to reduce the volatility in valuations of the
instrument. Even if the value of the derivative component fluctuates
significantly, the overall value of the structure will never be lower than
the value of the zero-coupon bond component.
In the case of a structured product that has capital at risk, or conditional
protection, the overall value of the structure can fluctuate more widely
over time, because of the lack of the ‘stabilising’ component represented by
the zero-coupon bond.
The behaviour of different structured products in the secondary market
can vary significantly when relevant market parameters change and
maturity approaches. The investor should consider this potential variability
in addition to the return profile at maturity and evaluate the extent to
which this could impact an overall portfolio .
Product rationaleWe can observe the behaviour of two different structures by simulating
their value in hypothetical secondary market scenarios.
The first product we consider in this analysis is a fully capital protected
structure that offers at maturity 85% participation in the positive
performance of a European equity index (table A).
The second structure is an auto-callable product with a maximum
maturity of five years and conditional capital protection (table B). At the
end of each year, the underlying value is observed and, if it is higher than
its original level on strike date, the product redeems at 100% plus a coupon
of 14% multiplied by the number of years since the issue date. For example,
if the product is called at the end of year two, investors receive 128%; if it is
called at the end of year three, the payout is 142%.
Citi discusses trading during the life of a structured product
A. Financial terms of the hypothetical fully protected structure
Maturity Five years, EUR
Underlying European equity index
Capital protection 100% of the initial invested capital
Final payout 85% of the performance over the life of the product
The Guide to Structured Product Terminology
Secondary Market
Secondary Market
The Guide To Structured Products Terminology
20
If the product is not called before the final observation date, investors
have the benefit of soft protection at maturity. This means that, provided
the level of underlying has not fallen lower than 50% of its initial value, the
entire invested capital is protected and redeemed at maturity. However,
if the soft protection barrier has been breached at anytime during the
investment term, investors will receive the final value of the underlying at
maturity, expressed as percentage of its initial value.
SimulationsFigures 1 and 2 show the simulated secondary market values of the two
structures at different points in time following inception. The analysis
shows an indicative fair value for the structures, disregarding any potential
bid/offer spread, assuming that volatility and interest rates remain static
over time. For the purposes of these simulations, the soft protection
barrier of 50% on the auto-callable structure is deemed to have never
been breached.
The simulations of the fully capital protected structure in the secondary
market illustrate the smoother reaction of the product to changes in the
underlying value. For example, if after 35 months from the strike date
the underlying has risen by 10%, the value of the fully capital protected
product is around 107.4%, compared to a value of 141.3% for the auto-
callable structure.
On the downside, the auto-callable product tends to drop in value
quickly in negative market scenarios. By contrast, the value of the fully
capital protected does not drop below the present value of protected
amount at maturity, even when the derivative component tends to be
worthless. For example, where the underlying has dropped by 40% after 47
months, the simulated value of the auto-callable structure is 69.9%, while
the simulated value of the protected structure is 95.1%.
The auto-callable structure is clearly more sensitive to variations in the
underlying and has a concave distribution of values, due to the fact that
the maximum potential payout is capped at specific levels (14% multiplied
by the number of years elapsed since inception).
The results of these simulations, based on the hypothetical behaviour
of the underlying index and on simplified assumptions on volatility and
interest rates, show how widely the valuations of these structures can vary
during their investment terms, even though both are linked to the same
underlying index.
The volatility of secondary market pricing can have a significant
impact on an investment strategy and should be considered as a major
factor in the investment process. During the life of a structured product
investment, market conditions could offer the opportunity to realise profits
early through liquidating the position. Trading out of the product in the
secondary market may also enable an investor to close out of a position
in order to avoid excessive risk. Citi offers a daily secondary market on
most of its structured product issues with a typical bid/offer spread of
approximately 1%. The level of liquidity and transparency available in the
secondary market plays a crucial role and should be highly regarded in the
selection process of the product.
1. Secondary market hypothetical behaviour of the fully capital protected structure
40%
60%
80%
100%
120%
140%
160%
180%
40.0% 60.0% 80.0% 100.0% 120.0% 140.0% 160.0%
1 month into the life11 months into the life23 months into the life35 months into the life47 months into the life59 months into the life
Hyp
othe
tical
pro
duct
val
ue
Underlying value
2. Secondary market hypothetical behaviour of the auto-callable structure
40%
60%
80%
100%
120%
140%
160%
180%
40.0% 60.0% 80.0% 100.0% 120.0% 140.0% 160.0%
Hyp
othe
tical
pro
duct
val
ue
Underlying value
1 month into the life11 months into the life23 months into the life35 months into the life47 months into the life59 months into the life
B. Financial terms of the hypothetical auto-callable structure
Maturity Five years, EUR
Underlying European equity index
Capital protection Conditional, with soft protection barrier at 50%
Auto-callability Annual observation, 100% barrier
Auto-callable coupon 14% multiplied by the number of years since inception
21
21
IntroductionRange-accrual products generate value for the investor during the period
in which the underlying asset’s price remains within a specific corridor.
Unlike traditional knock-out barrier structures, range accruals offer the
opportunity of mitigating the digital risk, thanks to an accrual process
distributed over time. If one of the barriers is touched, the return is affected
only for the portion associated with the single observation period, this is
without directly impacting future potential performance.
The definitionA basic range-accrual structure offers a target level of return, multiplied by
an accrual ratio. For each observation period when the underlying value
fixes in a specific range, the product accrues a portion of the coupon. Each
observation period contributes independently to the whole target return.
The accrual ratio is calculated by dividing the number of observations, where
the underlying is within the range, by the number of total observations in
the investment period. If the underlying always remains within the range, the
ratio is equal to one, and the whole target return is received.
Behind the scenesWe consider the traditional knock-in barrier structure with a fixed-target
return as a particular type of range-accrual structure with an accrual
period extended to the whole life of the product. By increasing the accrual
frequency from one period to multiple periods, and by considering each
observation as independent and able to contribute to a portion of the
overall return, we obtain a range-accrual derivative.
This structure can be conceived as a series of independent knock-out
barrier structures embedded in a single derivative. A higher number
of accrual periods will result in a finer granularity in the distribution of
potential payouts. The portion of the overall return affected by a single
observation falling outside the range will be inversely proportional to the
frequency of single accrual intervals.
In more complex structures, barriers can be referenced to the value of
different assets.
Product rationaleWe can consider a full capital protected range-accrual product with a
five-year life and a target coupon of 7.5% annual equivalent, distributed at
maturity. The underlying is an index representative of the European equity
market and the structure is denominated in EUR.
The coupon is accrued on a daily basis if the index daily closing price is
above the lower barrier of 95% of initial strike price; this is equivalent to an
accrual surface ranging from 95% to +infinite. For each day the condition is
met, the portion of the coupon is secured for payment. For example, if the
condition is met for two-thirds of the total observed days of the first annual
period, the secured coupon for the first year is equal to 5% (= 7.5% x 2/3).
If we substitute the lower barrier with an upper barrier fixed at 120%, the
return is accrued when the underlying index fixes below 120% of its initial
price at daily observation dates. Maintaining the indicative cost of the
structure above, the potential payout offered by this alternative structure
is 6% per year; the probability implied in the pricing of observations
occurring outside the range is lower and this is reflected in a reduction of
the potential return. We can observe the effect of restricting the range by
combining the two previous barriers in a single range-accrual structure.
The coupon is accrued when the underlying index fixes between 95% and
120% at observation dates. The effect of narrowing the range, therefore
increasing the probability of being out of the accrual zone, is reflected in a
higher target coupon of 13% (see figure 1).
Right place, right time – Citi examines range accrual products
A. Financial terms of the hypothetical range-accrual structure
Maturity Five year
Underlying index Equity index representative of the European market
Currency EUR
Capital protection 100% of the initial invested capital
Range variants Lower barrier, upper barrier, double barrier
The Guide to Structured Product Terminology
Range Accrual
Range Accrual
The Guide To Structured Products Terminology
22
SimulationsWe can compare the Monte Carlo simulations of a hypothetical range-
accrual structure with the simulated performance of a traditional
knock-out barrier structure; both structures have full capital protection
at maturity.
The barriers of the range-accrual structure are fixed at 95% (lower
barrier) and 120% (upper barrier). The return of the knock-out barrier
structure is generated with the same mechanism as the range-accrual
structure (i.e. the index should fix between the barriers at daily observation
dates) with the difference being that, if one of the barriers is touched, the
whole return is lost and the investor will receive at maturity only the initial
investment capital equivalent. The knock-out risk affecting the entire
payout at maturity is reflected in a wider accrual range of a lower barrier of
55% and an upper barrier of 150%.
Figure 2 shows the simulated payout distribution at maturity: the grey
bars represent the frequency of range-accrual payouts for each return
bracket and the red bars are associated with the traditional knock-out
barrier structure.
The mitigation of the digital risk of the range-accrual structures is
evidenced in this graphical representation of payouts. While the knock-in
effect results in a polarisation of two possible scenarios – full target coupon
of 65% paid at maturity (= 13% x 5 years) if barriers are never touched
or zero additional return – the accrual mechanism over time presents a
smoother distribution.
Range-accrual structures could represent an alternative to traditional
knock-out barrier structures, offering the opportunity of mitigating the digital
risk of losing the entire payout if the barrier is touched at a single observation.
2. Simulated payout distribution at maturity
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
Range-accrual
Traditional knock-out barrier
up to100.01%
100.01–105.01%
105.01–110.01%
110.01–115.01%
115.01–120.01%
125.01–130.01%
130.01–135.01%
135.01–140.01%
140.01–145.01%
145.01–150.01%
150.01–155.01%
155.01–160.01%
120.01–125.01%
160.01–165.01%
from
165.01%
Simulated payout
Freq
uenc
y
125%
120%
115%
110%
105%
100%
95%
90%0 1 2 3 4 5 6 7 8 9 10 11 12
First daily observation dates
Inde
x va
lue
Lower barrierIndexUpper barrier
1. Range-accrual structure
23
23
Citi Equity First Sales Contacts
Asia Pacific Harold Kim Tel. +852 2501 2317 [email protected]
Germany / Austria Matthias Riechert Tel. +44 20 7986 0276 [email protected]
Portugal Jorge Oliveira Tel. +35 12 13116 309 [email protected]
Australia Irfan Khan Tel. +61 2 8225 6126 [email protected]
Italy Francesco Milio Tel. +39 02 8648 4460 [email protected]
Spain Juan Pablo Ruiz-Tagle Tel. +34 91 538 4329 [email protected]
Central Europe Karim Rekik Tel. +44 20 7986 0457 [email protected]
Japan Atsushi Oka Tel. +81 3 5574 3159 [email protected]
Switzerland Jan Auspurg Tel. +41 58 750 60 50 [email protected]
Eastern Mediterranean Karim Rekik Tel. +44 20 7986 0548 [email protected]
Middle East Karim Rekik Tel. +44 207 986 0548 [email protected]
UK / Ireland Russell Catley Tel. +44 207 986 0408 [email protected]
France / Benelux Mikael Benguigui Tel. +44 20 7986 0589 [email protected]
Nordic Christian Eck Tel. +44 207 986 0389 [email protected]
USNicholas Parcharidis Tel. +1 212 723 7005 [email protected]
Sales Contacts
Asia PacificHarold KimTel. +852 2501 [email protected]
Germany / AustriaMatthias RiechertTel. +44 20 7986 [email protected]
PortugalJorge OliveiraTel. +35 12 13116 [email protected]
AustraliaShane MillerTel. +61 2 8225 [email protected]
ItalyFrancesco MilioTel. +39 02 8648 [email protected]
SpainJuan Pablo Ruiz-TagleTel. +34 91 538 [email protected]
Central EuropeThomas GlyrskovTel. +44 20 7986 [email protected]
JapanAtsushi OkaTel. +81 3 5574 [email protected]
SwitzerlandJan AuspurgTel +44 20 7986 [email protected]
Eastern MediterraneanPhilippe GedeonTel. +44 20 7986 [email protected]
Middle EastPhilippe GedeonTel. +44 20 7986 [email protected]
UK / IrelandEmma Louise DavidsonTel. +44 20 7986 [email protected]
France / BeneluxFrederic MelkaTel +33 1 7075 [email protected]
NordicThomas GlyrskovTel. +44 20 7986 [email protected]
USNicholas ParcharidisTel. +1 212 723 [email protected]