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


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%



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 :

>


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





%

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

>


Lookback

4

Lookback


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



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


Annual coupon Digital coupon, paid if outperformance is realised


Outperformance

6

Outperformance


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


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



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


Individual Cap

8

Individual Cap


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


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


Total Return vs. Price Return

10

Total Return vs. Price Return


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


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


Quanto-style Options

Quanto-style Options


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


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


Rainbow

14

Rainbow


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


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


Custom Indexes

16

Custom Indexes


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


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.


Tailored Protection

18

Tailored Protection


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


Final payout 85% of the performance over the life of the product


Secondary Market

Secondary Market


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


Range variants Lower barrier, upper barrier, double barrier


Range Accrual

Range Accrual


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]

citi guide to structured product terminology

Documents