Wealth Management Solutions / Advisory & Distribution

Structured Products in the Portfolio Context

Andreas BlümkeHead Advisory & Distribution+41 44 226 25 37Andreas.bluemke@vpbank.com

2

Andreas Blümke

Andreas BlümkeHead Advisory & Distribution+41 (0)44 226 2537andreas.bluemke@vpbank.com

Professional Experience• Since 2008 VP Bank (Switzerland) Ltd, Head Advisory & Distribution• 2005 Julius Bär & Co. Ltd, Product Manager Structured Products• 1998 Cantrade Privatbank Ltd, Head of Structured Products and OTC

Options business • 1994 Continental Grain Ltd. Commodity trader

Education• Degree in Economics, HEC Lausanne and Certified International

Investment Analyst CIIA

Publication• “How to Invest in Structured Products”, 2009• Blog: www.my-structured-products.com

3

Introduction

4

An Analogy: Cars and Structured Products

=?

Final Terms and Conditions 

Early Redemption Shark Note1 on ABC 30 Index (in EUR) 

2  Instrument Type  Index Linked Redemption Instrument (EMTN) 

3 

Issuer  Issuer Ltd.  

Guarantor  G Bank  

Rating of Guarantor   AA / Aa1 

Lead Manager  LM Ltd.  

Documentation  Issuer Ltd. MTN Programme 

Calculation Agent  CA Bank  

Principal Paying Agent  PPA Bank 

4  Underlying Index (Reference Asset) 

ABC 30 Index (ABC 30)  Bloomberg: ABC30; Reuters: .30ABC 

5 

Trade and Pricing Date (Initial Valuation Date) 

10 January 2008  

Issue & Payment Date  21 January 2008 

Expiration Date (Valuation Date)  10 July 2009  

Redemption Date  15 July 2009 

6  Denominated Currency  Euro (“EUR”)  

7 

Denomination (DN)  EUR 1,000 per Instrument 

Notional Amount  EUR 20,000,000 

Number of Instruments  20,000 

  Issue Price  100% (of Denomination) 

8 

Knock‐Out Event 

A Knock‐Out Event shall be deemed to occur if, on any exchange business day during the period from and including the Pricing Date to and including the Expiration Date, the level of the Underlying Index trades at or above the Knock‐Out Barrier. 

Knock‐Out Barrier  132% (Index level: 4647.06)  

Capital Protection  100% in the case of Early Redemption or Redemption, as defined below

Participation Factor (PF)  100% 

Rebate  7.50% x (n/N) 

where 

n is the number of exchange business days from and excluding the Initial Valuation Date to and including the date on which the Knock‐out Event has occurred. 

                                                                 1 To see the payoff diagram of this hypothetical product, flip to page 42. 

1 

5

Client

Investment Advisor

Buy-side specialist

Sell-side specialist

Structurer / quantitative analyst

What Do Investors Know About Structured Products?

Engineer

Mechanist

Pilot

Co-pilot

Passenger

6

The Concept of Integral Structuring

Structuring factors

Investment horizon

Skew & kurtosis

preferences

Target return

Riskwillingnessand ability

Mico-economicforecast

FX forecast

Macro-economicscenario

Correlation,skew, issuer

rating

Impliedvolatility

Interestrate Level

Assetuniverse

Structured products

Inve

stor

pre

fere

nces

Economic forecast

7

Return Distributions

“A structured product’s return distribution will supplant the one of the underlying asset it is based on.”

8

Simple Return Distribution Explanation

Normal

Right Skew Left Skew

9

Simple Return Distribution Explanation

10

20082002200120001990198119771974197319691966 2010 20091962 2006 20031957 2007 2004 19991953 2005 1988 19981946 1994 1986 19961941 1993 1979 19831940 1992 1972 19821939 1987 1971 1976 19971937 1984 1968 1967 19951934 1978 1965 1963 19911932 1970 1964 1961 19891931 1960 1959 1951 19851930 1956 1952 1943 1980

2001 1929 1948 1949 1942 19751973 1920 1947 1944 1925 19551966 1917 1923 1926 1924 19501957 1914 1916 1921 1922 1945

2002 1941 1913 1912 1919 1915 19381974 1920 1910 1911 1918 1909 1936 1958

2008 1930 1917 1907 1906 1905 1901 1927 1935 19541931 1937 1907 1910 1903 1902 1904 1900 1908 1928 1933

-50 to -40 -40 to -30 -30 to -20 -20 to -10 -10 to 0 0 to 10 10 to 20 20 to 30 30 to 40 40 to 50 50 to 60Total return in percent

2010 20092006 2003

2007 2004 19992005 1988 19981994 1986 1996

2000 1993 1979 19831990 1992 1972 19821981 1987 1971 1976 19971977 1984 1968 1967 19951969 1978 1965 1963 19911962 1970 1964 1961 19891953 1960 1959 1951 19851946 1956 1952 1943 1980

2001 1940 1948 1949 1942 19751973 1939 1947 1944 1925 19551966 1934 1923 1926 1924 19501957 1932 1916 1921 1922 1945

2002 1941 1929 1912 1919 1915 19381974 1920 1914 1911 1918 1909 1936 1958

2008 1930 1917 1913 1906 1905 1901 1927 1935 19541931 1937 1907 1910 1903 1902 1904 1900 1908 1928 1933

-50 to -40 -40 to -30 -30 to -20 -20 to -10 -10 to 0 0 to 10 10 to 20 20 to 30 30 to 40 40 to 50 50 to 60Total return in percent

Structured Products: Non-Normal Return Distributions

Yearly returns S&P 500 Normal Return Distribution

90% capital guarantee (symbolic)

11

Innovative Portfolio Construction Approach

“Think a new Box.”

1. Framework

2. Investment preference

3. Asset return distribution

12

Preferred Distribution of Return Investment Process

1. Framework

3. Asset return distribution

2. Investmentpreferences

7. Fine- tuning

6. Structuringparameters

5. Macro, micro, FXforecast

4. Portfolio

13

1. Framework: the Return Distribution Cube

Risk category

Skew

Kurtosis

Left RightFlat

High

Low

High

14

2.1 Investment Preferences

Behavioral Finance

Prospect theory (Kahneman & Twersky)

Questionnaire Summary:

“Cut losses and let profits run?”

“Buy low sell high?”

“Buy and hold?” Kurtosis

Risk

Skew

Individual distribution of returns

Losses Gains

Value

Reference point

15

2.2 Questionnaire

Risk (volatility) <11% 11% - 17% >17%

Category: Low Medium High

Skew <-0.4 -0.4 – 0.4 >0.4

Category: Left None Right

Kurtosis <2.5 2.5 – 3.5 >3.5

Category: Flat Normal High

• expected return and volatility

•adjustments for volatility, skew and kurtosis

•Adjustment for investor‘s personal information

Part 1

Part 2

Part 3

16

3.1 Asset Return Distribution: Capital Guarantee

Name Underlying asset CG level Maturity Currency Cap

Capital Guar. 1 Eurostoxx50 index 100% 5 years EUR No

Results SX5E Index Capital Guar. 1Mean return over h.p. 1.1% (TR : 12.6%) 16.9%Mean return p.a. 0.22% (TR: 2.52%) 3.38%Volatility of returns 39.0% 27.6%Skew 0.88 1.40Kurtosis 2.45 3.41

17

3.2 Asset Return Distribution: Yield Enhancement

Stock name Coup. Bar.Basket mean return

Prod. mean return

Prod. vol. of returns

Prod. skew

Prod. kurtosis

ALV/SIE 9% 65% 9.3% -3.5% 22.8% -1.6 4.13ALV/SIE/FP 9.25% 65% 9.4% -3.3% 22.8% -1.6 4.13SIE/FP 7.25% 65% 13.8% 0.2% 14.8 -1.97 5.65NES/NOV 4.75% 75% 4.3% 2.1% 7.8% -2.7 8.61NES/ROG/UBS 10.25% 70% 5.9% 2.2% 16% -2.04 6.41NES/NOV/UBS 9.25% 75% 4.6% 2.3% 15% -2.47 8.60ROG/UBS 7% 70% 5% -0.8% 15.9% -2.09 6.65UBS/ABB 7.75% 65% 11.8% -11.7% 28.6% -0.93 2.08

18

3.3 Asset Return Distribution: Participation

Name Type Underlying asset Bonus Barrier Mat.Partic. 1 Bonus Eurostoxx50 index 20% 75% 2Y

Results SX5E index Partic. 1Mean return over h.p. 7.2% (TR: 11.6%) 9.7%Mean return p.a. 3.6% (TR: 5.8%) 4.85%Volatility of returns 34.3% 34.3%Skew -0.17 -0.39Kurtosis 2.09 2.17

19

The Return Distribution Cube

Risk cat.

Skew

Kurtosis

Left RightFlat

High

Low

High

“A structured product’s risk parameters will supplant the ones of the underlying asset it is based on.”

20

Product Know-How

• Yield Enhancement: Barrier Reverse Convertibles (BRC)

• Participation: Bonus Certificates

• Capital Guarantee: Capital Guaranteed Notes (CGN)

21

Structuring Factors

Structuring factorsCorrelation,skew, issuer

rating

Impliedvolatility

Interestrate Level

Assetuniverse

Structured products

Inve

stor

pre

fere

nces

Economic forecast

22

Example: Classification of Reverse Convertibles

Reverse Convertible

Knock-in Barrier No Knock-in Barrier

Am. Style Eu-Style

SingleUnderlying

MultipleUnderlying

SingleUnderlying

MultipleUnderlying

WorstOf

BestOf

WorstOf

BestOf

Callable

Auto-Callable

Callable

Auto-Callable

Non-C

allable

Quanto

Com

posite

Berm. Style

Bonus

Norm

al

Express

Bonus

Norm

al

Express

Clicket

Norm

al

Bonus

Clicket

Norm

al

Bonus

Callable

Auto-Callable

Non-C

allable

Callable

Auto-Callable

Callable

Auto-Callable

Non-C

allableC

allableAuto-C

allableN

on-Callable

… … …

SingleUnderlying

MultipleUnderlying

WorstOf

BestOf

… …

a

a a a

a a

…b

b

Trigger

Auto-Callable

23

-30%

-20%

-10%

0%

10%

20%

70%

75%

80%

85%

90%

95%

100%

105%

110%

115%

120%

t=1.0

t=0.5

t=0.0

Market

Example: Stock XYZ, 1 year maturity, vol 13%, interest rate 4.5%, div yield 4%, barrier75%, coupon 10%.

Lower Volatility

BRC: Behavior During Lifetime

Each line -10% time, starting at 1.0 and ending at 0.0

P&L

24

-30%

-20%

-10%

0%

10%

20%

70%

75%

80%

85%

90%

95%

100%

105%

110%

115%

120%

t=1.0

t=0.5

t=0.0

Market

Example: Stock XYZ, 1 year maturity, vol 23%, interest rate 4.5%, div yield 4%, barrier75%, coupon 10%.

Initial VolatilityP&L

BRC: Behavior During Lifetime

25

-30%

-20%

-10%

0%

10%

20%

70%

75%

80%

85%

90%

95%

100%

105%

110%

115%

120%

t=1.0

t=0.5

t=0.0

Market

Example: Stock XYZ, 1 year maturity, vol 33%, interest rate 4.5%, div yield 4%, barrier75%, coupon 10%.

Higher VolatilityP&L

BRC: Behavior During Lifetime

26

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

50%

60%

70%

80%

90%

100%

110%

120%

t=1.0

t=0.5

t=0.0

Market

Initial Data: 2 years, 23 vol, 109 strike 4.5% IR, 4% div yield

Lower VolatilityP&L

Bonus Certificate: Behavior During Lifetime

27

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

50%

60%

70%

80%

90%

100%

110%

120%

t=1.0

t=0.5

t=0.0

Market

Initial Data: 2 years, 23 vol, 109 strike 4.5% IR, 4% div yield

Stable VolatilityP&L

Bonus Certificate: Behavior During Lifetime

28

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

50%

60%

70%

80%

90%

100%

110%

120%

t=1.0

t=0.5

t=0.0

Market

Initial Data: 2 years, 23 vol, 109 strike 4.5% IR, 4% div yield

Higher VolatilityP&L

Bonus Certificate: Behavior During Lifetime

29

CGN: Behavior During Lifetime

Example: 4 year maturity, from 23% to 33% vol, 4.5% IR, 100% CG, 100% Participation

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

150%

t=1.0

t=0.5

t=0.0

Market

P&L

Higher Volatility

30

CGN: Behavior During Lifetime

Example: 4 year maturity, 23% vol, 4.5 IR, 100% CG, 100% Participation

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

150%

t=1.0

t=0.5

t=0.0

Market

P&L

Initial Volatility

31

CGN: Behavior During Lifetime

Example: 4 year maturity, from 23% to 13% vol, 4.5% IR, 100% CG, 100% Participation

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

150%

t=1.0

t=0.5

t=0.0

Market

P&L

Lower Volatility

32

CGN: Behavior During Lifetime

Example: 4 year maturity, 23% vol, from 4.5% to 2.5% IR, 100% CG, 100% Participation

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

150%

t=1.0

t=0.5

t=0.0

market

P&L

Lower rates

33

CGN: Behavior During Lifetime

Example: 4 year maturity, 23% vol, from 4.5% to 6.5% IR, 100% CG, 100% Participation

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

150%

t=1.0

t=0.5

t=0.0

P&L

Higher rates

34

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

150%

t=1.0t=0.2t=0.0Market

Example: 4 year maturity, 23% vol, interest rate 4.5%, 100% CG, 100% ParticipationP&

LOne capital guarantee is not like another

35

One capital guarantee is not like another II

Example: 9 months maturity, 30% vol, interest rate 1.5%, 95% CG, 100% Participation, upper knock-out 125% (no rebate), lower knock-out 70% (8% rebate)

P&L

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

130%

140%

150%

t=1t=0.2t=0Market

36

Portfolio Construction Examples

37

Portfolio Construction Process: Building Blocs

Investor’spreferences

Product characteristics

Risk Category

Return Skew

Return Kurtosis

ExpectedReturn

ReturnVolatility

Risk cat.

Skew

Kurtosis

Left RightFlat

High

Low

High

38

Building Blocs Concept: Example

Task

• Build a portfolio with a right-skewed return distribution

• Diversify over several asset classes

• Keep risk at a low level

Goal

• Achieve an excess returncompared to money-market orshort-term bonds

39

Portfolio Example using Building Blocs

Maturity

Asset Class 9M 12M 18M Allocation

Stocks 5% 15% 10% 25%

Interest Rates 0% 10% 25% 35%

Commodities 0% 0% 10% 15%

Foreign Exchange 10% 0% 25%

Allocation 20% 35% 45% 100%

15%

Description Allocation

Bloc 1 Shark Note EUR/USD

Bear Spread Note CHF/BRL qEUR

…

Bloc 2

7%

4%

4%Bloc3

Allocation 15%

-2% +3.5% +6%

40

Sample Portfolio I

• Mr. Bob Sample, age 62, freshly retired, married, bankable assets of EUR 3 Mio, transfers his funds to investment advisor Marc Council (you). Bob has no other revenue than what he can earn on his assets, which he has accumulated over his life. He further comments that his current single stock and mutual funds holdings represent less than 10% of his assets. He plans to retire to southern France where he would like to buy a house near the coast in exchange for the house he would sell in the Netherlands.

• The answers of the questionnaire lead to the following results:

Risk Category 1 (low)Skew RightKurtosis High

41

Sample Portfolio II

• Mr. John Model, age 49, manager and owner of a small privately held industrial company, married family father with two children, bankable assets of EUR 2.5 Mio, transfers most of his funds to his long-time friend Marc Council (you). You know from your relation that John has a good knowledge of FX instruments. His firm operates in foreigncountries and he invests in stocks from fellow industrials he makes business with, often selling them when he reaches his target return. Due to the nature of his business, John knows the relation between risk and reward pretty well, and you know he is ready to take controlled risks.

• The answers of the questionnaire lead to the following results:

Risk Category 3 (medium)Skew Normal - RightKurtosis Normal

42

Sample Investor Portfolios

Risk category Skew KurtosisBob Sample Low Normal - Right NormalJohn Model Medium Normal Normal

Bob Sample’s Portfolio % Risk cat. Skew KurtosisCash 5% - - HighST IG bonds 50% Low - HighLT IG bonds 30% Low - HighCapital Guarantee1 (FX) 10% Low Right DualCapital Guarantee2 (Eq) 5% Low Right Normal

John Model’s Portfolio % Risk cat. Skew KurtosisST IG bonds 15% Low(1) - HighLT IG bonds 5% Low(1) - HighST EM - HY bonds 10% Low(2) - NormalLT EM - HY bonds 5% Medium(3) - NormalShark Note (FX) 10% Low(1) Right High (dual)Stocks 20% High(4) None FlatParticipation1 (FX) 20% Medium(3) None FlatParticipation2 (Comm) 15% Medium(3) None Flat

43

Conclusion

Integral structuring:

• Find out investor’s investment preferences

• Consider structuring parameters

• Consider market views, forecasts etc.

• Construct and invest in according products, by using building blocs.

44

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