Pavia. October – December 2014
Asset and Portfolio Management
Program: phases of an efficient investment’s process
1.Define Investor’s characteristics and goals
2.Strategic Asset Allocation
1.
Studying Market’s behavior
2.
Forecasting Returns
3.
•
Macroeconomic Analysis
•
Fundamental Analysis
Portfolio’s Construction
•
Risk Budget Approach
•
Optimization
3.Tactical Asset Allocation
1.
Tactical Risk Management (ex ante)
2.
Technical Analysis
4. Fund selection
1.
The process
2.
The model for selection
5. Control and Reporting
1.
Risk Management (ex post)
2.
Performance Analysis
1. Investor’s characteristics and goals
1 – Define investor’s characteristics and goals
It is very important to define:
1. Risk Profile
2. Time Horizon
3. Approach (benchmark vs Total Return)
4. Constraints:
•
Investible universe (equities, bonds, credits, etc)
•
Type of underlying (stocks, mutual funds, Etf, Hedge Funds)
•
Maximum / minimum exposure
Define correctly investor’s characteristics is fundamental: if you make a mistake at
this level is very difficult that the investor will be satisfied, even if you will be right in
forecast returns
Responsability: Private Banker
4
1 – Investment’s approach
Benchmark driven: the investor choose an index of the market (benchmark), the goal oh the fund
manager is try to bet the index (over performance)
1.
The strategic asset allocation is actually delegated to the benchmark chosen
2.
The asset managers stay concentrated to tactical asset allocation and fund (security) selection
3.
NO volatility control over time
4.
The hope is that without volatility constraints over long time period the investor get higher returns (Is that true?)
Total Return: without a benchmark asset managers try to maximize expected return given a certain level
of risk (Value at Risk). The goal is to achieve extra return vs risk free with a define level of risk (volatility)
5
•
The asset manager control all the process: dynamic asset allocation and fund (security) selection.
•
Flexible approach, with 2 explicit goals:
1.
volatility control and capital protection (stability of returns)
2.
over performance vs risk free (o risk free + X basis points)
2. Strategic Asset Allocation
Phases of Strategic Asset Allocation
1 – Define Investible universe on a global basis:
1. Monetary Instruments
2. Government bond (1-3 years, 3-5 years, 5-10 years)
3. Corporate Bond (Investment Grade and High Yield) and Emerging Markets Bonds
4. Global Equity (Europe, USA, Japan, Asia ex Japan, Emerging)
5. Commodities
2 – Studying Markets Behavior
•
Analysis of Assets classes over a defined time horizon (usually 2 / 5 years, weekly frequency)
•
Calculation of annualized statistical indicators (DNA of different Assets Classes)
•
Expected returns
•
Standard deviations
•
Correlations (matrix of interaction among financials activities)
3 – Studying economic and markets environment
1.
Macroeconomic analysis
2.
Fundamental Analysis
4 – Portfolio’s construction
7
•
Risk Budget Approach (Risk’s constraints and allocation)
•
Optimization (Mean Variance and Black and Litterman)
2. Strategic Asset Allocation
Investible Universe and market’s behavior
1 - Investible Universe
Role
Driver Exposure
Strategical
Monetary Unstruments
< 12 mesi Euro
Capital Protection
Government Bonds
 US
 Germany
Decorelation
Risk Budget
Risk Budget
Underlying
Tactical
Views
Short Terms Bonds
Views
Passive Mutual Funds
ETFs
Bonds with spreads
 PIGS
 Corporate Bonds (IG)
Risk Budget
Carry
Risky Assets
 Global Equitis
 Commodities
 Corporate HY / Emerging Bonds
9
Views
Extra Return
Risk Budget
Active Mutual Funds
ETFs
Views
Active Mutual Funds
Dynamic Risk
Management
ETFs
2 - Markets behavior: what the history tells us





10
Markets seem «crazy» and irrational in the short term, but this is not true if we consider a longer
time horizon:
Each financial activity has owns characteristics (DNA), in terms of

Returns (annualized)

Volatility (annualized)

Interaction with the others (correlation).
In particular the interaction between different assets is more important than the features of a
single one. Each portfolio’s risk-return profile is not equivalent to the sum of all the risk-return profiles of
the portfolio’s assets (the importance of diversification!).
Markets behavior often express recurring rules
Is on the basis of those rules and those characteristics that is possible to set up solid and
efficient portfolios (strategic component).
2 - Markets behavior: the numbers
Analysis of Financial’s Activities (DNA)
Volatilidad
Anualizada
Rentabilidad
Anualizada
Monetario
Inflation
linked
Renta fija
AAA Euro
Periféricos
Euro
Corporate Corporate Corporate
IG ST Euro IG Global
HY
Deuda
Em ergente
Renta Variable
Global
Com m odities
0,1%
4,7%
5,2%
1,5%
1,5%
3,8%
7,8%
6,0%
14,4%
16,2%
0,9%
7,9%
7,6%
3,8%
3,6%
8,5%
9,2%
11,2%
12,1%
-9,7%
Monetario
Inflation
linked
Renta fija
AAA Euro
Periféricos
Euro
Corporate
IG ST Euro
Corporate
IG Global
Corporate
HY
Deuda
Emergente
Renta Variable
Global
Commodities
5,2%
100,0%
1,4%
68,8%
100,0%
20,4%
15,3%
19,2%
100,0%
10,5%
23,1%
45,5%
28,8%
100,0%
11,4%
34,9%
44,4%
19,1%
82,3%
100,0%
4,7%
-13,3%
-0,3%
20,4%
60,3%
68,0%
100,0%
9,9%
-3,4%
3,5%
15,1%
59,0%
69,0%
63,1%
100,0%
1,8%
-29,6%
-21,1%
13,4%
19,1%
16,2%
41,1%
38,2%
100,0%
Matriz de
Correlación
Monetario
Inflation linked
Renta fija AAA Euro
Periféricos Euro
Corporate IG ST Euro
Corporate IG Global
Corporate HY
Deuda Emergente
Renta Variable Global
Commodities
11
100,0%
-9,5%
-11,5%
-15,7%
-4,8%
18,7%
23,5%
35,5%
50,3%
36,0%
100,0%
3 – Studying economic and markets environment
 To
improve returns for units of risk over time is important to consider also yours
views of economic and market environment
 To estimate correctly dynamics in financials markets is important to:
 Identify a series of investment’s themes (risks factors) that consistently drive returns across
global markets and asset classes (long-term valuation, short-term momentum, fund flows, risk
premium, macroeconomic policy)

Identify metrics able to describe each investment theme (growth, inflation, multiple, volumes, etc)

Compare owns expectations of the evolution of each risk factor with markets expectations
 Basically there are two main disciplines for strategic exposures
 Macroeconomics analysis – studying economic cycle
 Fundamental Analysis – studying asset’s value and earnings cycle
12
3 – Risk factors for markets forecasting
13
Macroeconomic
Metrics: Growth, Inflation, cash Policy
Tool: Macroeconomic analysis
Valuation
Metrics: Multiples (PE, PB, DY), Fair Value (DDM,
DCF), Fed Model (B/E Yield)
Tool: Fundamental analysis
Earnings cycle
Metrics: Earnings growth, margins, revenues
Tool: Fundamental analysis, quantitative analysis
Liquidity
Metrics: cash policy, yield curve, M1 / M2, foreingns
reserves, companies cash flows
Tool: Macro research, balance sheet analysis
Momentum
Metrics: Price Momentum, volumes, RSI
Tool: Technical analysis
2. Strategic Asset Allocation
Macroeconomic Analysis
3 – Macroeconomic Analysis
15

Economic Cycle Analysis

Economic Clycle and Market Trend

Expectations Role
Economic Cycle: Introduction
Definition: alternation of phases (expansion – contraction) characterized by a different pathos in the
economic activity
Key Variables for markets:
1.
2.
3.
16
Gross Domestic Product  economic growth
Inflation  prices increase
Economic Policy: cash and fiscal
Economic Cycle: GDP
Definition: sum of the markets values of all final goods and services domestically produced in a country
in a given year
Components: C + I + G + (X-M)
C = Consumption
I = Investments
G = Government Spending
(X-M) = Net exports
Personal consumption
Gross private investment
Government spending
Net exports
USA
71%
14%
18%
-3%
EU
56%
22%
20%
2%
TOT
100%
100%
Periodical: quarterly
17
looking at other, more frequent, indicators is necessary
GDP: Consumption
Components: durable goods + non durable goods + services
Leading indicators:
 Labour market indicators:
1.
Unemployment rate (monthly)
2.
jobless claims (weekly)
3.
nonfarm payrolls (monthly)
 Personal income (monthly)
Real indicators
 Durable good orders (monthly)
 Real estate market indicators:
1.
Price (monthly)
2.
Housing starts (monthly)
 Consumer Confidence USA (monthly)
 U. of Michigan’s index of Consumer Sentiment USA (monthly)
 Consumer Confidence EU (monthly)
18
Sentiment indicators
GDP: Investments
Components: residential investments + capital expenditures + inventories
Leading indicators:
 Industrial production (monthly)
 Retail sales (monthly)
Real indicators
 New orders (monthly)
 Philadelphia Fed USA (monthly)
 Chicago Purchasing Manager USA (monthly)
 ISM: PMI manufacturing, services and composite (monthly)
 Sentix, Zew and IFO EU (monthly)
19
Sentiment indicators
Inflation
π = (Pt- Pt -1) / Pt -1
1.
π >0 and increasing Inflation
2.
π >0 and decreasing Disinflation
3.
π <0  Deflation
Indicators:

GDP deflator (quarterly)

Consumer Price Index (monthly)

Producer Price Index (monthly)
There are rate-numbers
Only the percentage variations are important
For each indicator there are general data and core data (ex food & energy)
20
USA consensus
Fonte Bloomberg - Pagina ECFC
21
EU consensus
Fonte Bloomberg - Pagina ECFC
22
Economic calendar
Fonte Bloomberg – Pagina WECO
23
Economic cycle and market’s returns
High growth
Potential output
Zero growth or negative
Inflation
Disinflation
Commodities + + +
Commodities + + +
Commodities +
Equity ++
Equity ++
Bond =
Credits + +
Credits + +
Liquidity =
Bond - - -
Bond - -
Equity -
Liquidity - - -
Liquidity - - -
Credits -
Equity + + +
Equity + +
Bond + + +
Credits + +
Credits + +
Equity =
Commodities + +
Commodities +
Credits =
Liquidity –
Bond =
Commodities =
Bond - -
Liquidity =
Liquidity =
Bond + + +
Deflation
Liquidity + + +
Equity - - Credits - - Commodities - - -
24
Economic cycle and trend of the market: role of macroeconomic analysis
Eurosystem Staff forecast for year 2006
PIL %
CPI %
December-05
1,4 - 2,4
1,6 - 2,6
March-06
1,7 - 2,5
1,9 - 2,5
Data ex post, 2006
June-06
1,8 - 2,4
2,1 - 2,5
September-06
2,2 - 2,8
2,3 - 2,5
December-06
2,5 - 2,9
2,1 - 2,3
Eurosystem Staff forecast for year 2007
PIL %
CPI %
March-07
2,1 - 2,9
1,5 - 2,1
June-07
2,3 - 2,9
1,8 - 2,2
September-07
2,2 - 2,8
2,4 - 2,8
PIL %
CPI %
25
June-08
1,5 - 2,1
3,2 - 3,6
September-08
1,1 - 1,7
3,4 - 3,6
2006
3,0
2,2
Data ex post, 2007
December-07
2,4 - 2,8
2,0 - 2,2
Eurosystem Staff forecast for year 2008
March-08
1,3 - 2,1
2,6 -3,2
PIL %
CPI %
PIL %
CPI %
2007
2,1
2,35
Data ex post, 2008
December-08
0,8 - 1,2
3,2 - 3,4
PIL %
CPI %
2008
0,4
3,85
1.
Expectations change and they adapt themselves to new events and
data (adaptive expectations)
2.
The aim does not consist in becoming infallible forecasters
3.
The speed of adaptation to new evidences is the matter
Economic cycle and trend of the market: role of macroeconomic analysis
1.
Building an own main scenario
•
2.
It is important to have a central scenario and an alternative one based on the analyzed indicators
Adapting the scenarios to the evidences
•
3.
The scenarios can change through time due to new data and new events
Rebuilding and monitoring what the market incorporates
• Every moment the market incorporates a specific scenario of growth-inflation
• The market is one of the best forecaster (the best?), efficient and conservative
• Are the markets the reflection of the economy, or the opposite? During last years often the opposite
has been often true (see currencies)
180
1,7
170
1,6
160
150
1,5
140
1,4
130
1,3
120
10/31/2009
8/31/2009
6/30/2009
4/30/2009
2/28/2009
12/31/2008
10/31/2008
8/31/2008
6/30/2008
4/30/2008
2/29/2008
10/31/2009
8/31/2009
6/30/2009
4/30/2009
2/28/2009
110
12/31/2007
EuroDollaro
12/31/2008
10/31/2008
8/31/2008
6/30/2008
4/30/2008
2/29/2008
12/31/2007
1,2
EuroYen
4.
Analyzing and understanding if and why yours and market’s scenarios differ one from another
•
26
In order to find investment’s opportunities it is necessary to identify the differences between your own
scenario and the one incorporated by the market
Expectations’ role: what the market incorporates
1. Growth:
yield curve
spread corporate
sectors’ trends (cyclical – defensive)
2. Inflation:
break even inflation
commodities
3. Cash policy:
future on Fed Funds and on Eonia
2 years yields
27
2. Strategic Asset Allocation
Fundamental Analysis
Fundamental Analysis

Introduction to fundamental analysis

Valuation’s methods:
 DCF e DDM
 Multiples

29
Conclusions
Introduction to fundamental analysis
Valuation process: analyze the relationship between Value and Price of financials assets
Issue: identify the “theoretical fair value” of an asset that should be different, at least temporarily, than the market price.
By selecting assets undervalued is possible to get extra returns compare to the market’s average.
When is used
1.
Security Selection (equities, bonds, real assets)…
2.
Asset Selection
3.
Generally speaking in the active management
Is useful only if:
30
1.
The investment’s time horizon is medium/long
2.
The investment process is structured and disciplined
Intruduction to fundamental analysis
Fundamental analysis works better in inefficient markets, where markets price often differs from
fair value
Should anyway be used also in efficient markets. Markets becomes efficient for the action of many
investors looking for returns and undervaluation, therefore there are possibilities of temporaries
inefficiencies also in efficient markets
Valuation is not objective. Every valuation model depends on inputs and estimations that we put into
the valuation’s process
The valuation’s process is much more important than the result (fair value). A transparent and
coherent process is helpful in order to better understanding the value’s drivers of financials assets
31
Valuation’s methodologies
Discounting cash flows
1.
DDM (Dividend Discount Model). Is the simplest methodology. It allows to estimate the equity value as the
Net Present Value (NPV) of the future Cash Flow to equity (dividends)
2.
DCF (Discounted Cash Flow). Is the methodology most complete. It allows to estimate the value of the Firm
(equity + debt) as the Net Present Value (NPV) of future cash flow to firm
Multiples
32
1.
PE (Price to Earnings)
2.
PB (Price to Book)
3.
PS (Price to Sales)
4.
PEG (Price to Earnings Growth)
5.
Fed Model (relative valuation equity – bond)
Valuation’s methodologies - DDM e DCF
DDM: Equity value
DCF: Firm Value (Equity + Debt)
Equity Value
t
e
CF
t 1 (1  k )t
e
n
33
Firm (EV) Value

CFft
n
t 1
(1  WACC )t
Ke= Cost of Equity
WACC= Weighed Average Cost of Capital
n = life of the asset
n = life of the asset
CFe= Cash flow to Equity (dividends)
CFf = Cash flow to firm
Firm Value and DFC
Value drivers in a DCF model:
1.
Cash flows to firm (CF), that depends on:
•
Sales Growth
•
Profitability – Margins (EBITDA & EBIT margins)
•
Investments for future growth (CAPEX)
•
Net Working Capital variations (NWC)
2. Discount rate: Weighted Average Cost of Capital (WACC)
3. Terminal value of the firm
34
Value drivers in DCF Model: Sales Growth
There are 3 options for estimating sales growth:
 Compare growth estimations with historical data
 Make assumptions on market growth and market’s share expectations
 Compare growth estimates with analyst estimates
Estimating sales growth needs:
 Good knowledge of company history and sector perspective
 Keep in touch with analyst and company management
 High level of discipline making our assumptions
35
Value drivers in DCF Model: Margins and Capex Spending
There are 3 options for estimating margins

Compare estimates with historical data

Compare estimates with competitors

Compare estimates with analysts assumptions
Capex spending shows how the company invest for future growth and consist of 2
elements:


36
Net Capex: shows how much the company invests in new equipment in addition to what is
necessary to maintain the efficiency of the existing facilities.
Non Cash Working Capital: allows us to consider the level of inventories and the policy regarding
accounts receipts and payments (rise in inventories means drain in cash flow).
Value drivers in DCF Model: Discount rate
Discount Rate = weighted average cost of capital (WACC)
WACC =
Cost Equity 
Equity
Debt
 Cost Debt 
Debt  Equity
Debt  Equity
Cost of equity = return required by investors to invest into the firm compare to risk free
Cost del debt = rate of interest paid by the firm on own debt
1.
Depends on credit profile of the firm
2.
Is calculated by using financials indicators of rating’s agencies
Equity
Debt  Equity
37
= Financial leverage
DCF: estimation of cost of equity
Cost of equity is calculated using the CAPM (Capital Asset Pricing Model)
K = Rfr + (Beta * RP)
K = Cost of equity (expected return)
Rfr = Risk-free rate
Beta
RP = Risk Premium
Exemple: ENI
Risk Free = 3.5%
Beta = 1 (Bloomberg)
Risk Premium = 4.5% (should be different but on average stay between 4% and 5%)
Cost of equity for ENI = 3.5% + 1*4.5% = 8%
38
DCF: estimation of WACC
Cost Equity 
WACC =
Equity
Debt
 Cost Debito 
Debt  Equity
Debt  Equity
exemple: ENI
Cost of Equity = 8%
Cost of Debt = 6%
Tax Rate
Cost of Debt after tax = 6% x (1- 45%) = 3.3%
Debt = 16.3 bn € (al 31/12/2007)
Equity = 42.9 bn € (al 31/12/2007)
WACC = 8 % 
42.9
16.3
 3.3% 
= 8% x 0.72 + 3.3 % x 0.28 = 6.68%
16.3  42.9
16.3  42.9
Note: Leverage and WACC
Se ENI would have debt of 3 x Ebitda ~ 90 bn €
WACC = 8 % 
39
42.9
16.3
 3.3% 
= 8% x 0.32 + 3.3% x 0.68 = 4.8%
90  42.9
90  42.9
DCF: ratios that affects cost of equity
40
Debt risk
41
Return
Bond asset return
R  Rrf    L
42
Rfr
= Free Risk asset return
α
= risk premium
L
= liquidity premium (same qualities securities)
Risk
Definition: returns’ variability around expected medium return
Rational investor theory: given two securities that offer the same expected return, investors will
prefer the less risky one
Risk types in fixed interest bonds’ market
1. Credit risk
2. Market risk
3. Liquidity risk
Instruments for risk evaluation
1. Rating (credit)
2. Duration (market)
43
Credit risk : Rating
Definition: evaluation of a
borrower's ability to repay debt
44
potential
Market risk: Duration
Definition: Measure of the sensitivity of the asset's price to interest rate movements
It is a measurement of how long, in years, it takes for the price of a bond to be repaid by its internal
cash flows
 Fixed interest and zero coupon bonds
Formula
N
Ct
1
D
t

t
P t 1 (1  r )
P = Price
C = Cash flows (coupon and debt)
r = Interest rate
N = Time to maturity (yearly, quarterly,…)
45
Liquidity risk
Definition: lack of marketability of an investment that cannot be bought or sold quickly
enough to prevent or minimize a loss
 > Liquidity
 < Costs (market debt)
 < Tempi
Instruments to evaluate the liquidity of a fixed income asset
1. Exchanges’ scale on the secondary market
2. Emission size
3. Market makers’ number
4. Bid/Ask spread
5. Quotations’ transparency
46
Value drivers in DCF Model: Terminal Value
We are at the last step of our DCF Model
There are 2 options to calculate terminal value:


47
Liquidation Value. Usually is calculated using multiples: what kind of multiple shall
we consider on sales, Ebidta, etc. to sell our company? Better methodology for fast
growing company or restructuring stories
Stable Growth. The alternative is to estimate the appropriate stable growth level for
the future. Better methodology for mature companies for which there is good visibility
on growth rate
Relative valuation - Multiples
1/3
The value of financials asset should be estimated by putting in relation the price and a series of
fundamentals indicators.
Multiples allows relative valuation, looking at how the markets is pricing similar assets (peer
comparison).
Markets inefficiencies among similar assets are easier to get and exploit. Using multiples it is
possible to compare different assets over time.
It is important to remember that multiples should change over time, given the same fundamentals,
according to some factors:
1.
2.
3.
Liquidity
Earnings cycle
Sentiment
There are different type of multiples:
1.
2.
3.
4.
5.
48
earnings
book value
sales
normalized for growth (Price Earnings Growth)
relative (Fed Model)
Relative valuation - Multiples
Multiples of earnings
Price-earnings ratio or PE: ratio between price and EPS (earnings per share)
1.
2.
PE Forward (earnings estimated for the next 12 months)
PE Trailing (on realized earnings in the last 12 months)
Multiples of operating earnings
Enterprise Value / EBITDA o EBIT (*)
Cash Earnings multiples
Price/Cash Flow (earnings + amortization)
*Ebitda = Earnings Before Interest Taxes Depreciation & Amortization
*Ebit = Earnings Before Interest Taxes
49
2/3
Relative valuations – Multiples
3/3
Multiples on Book Value (BV)
Price / Book value: ratio between price and the value of own capital
Enterprise Value (EV) / Capital: ratio between (Equity + Debt) and Capital
Multiples on sales
Enterprise Value (EV) / Sales: ratio between EV and sales
Multiples normalized for growth
PEG = PE / Expected Growth Rate. Allows to compare peers normalizing multiple for the growth factor
Realative multiples
Fed Model: Bond Yield (10Y) – equity Yield (Earnings / Price). Express relative valuation between
equity and bond markets
50
31-Jan-95
40
3,00
20
2,00
0
1,00
51
PE
Mean
DY
Mean
31-Jan-09
31-Jan-08
31-Jan-07
31-Jan-06
31-Jan-05
31-Jan-04
31-Jan-03
31-Jan-02
PB
31-Jan-01
1-Jan-09
1-Jan-08
1-Jan-07
1-Jan-06
1-Jan-05
1-Jan-04
1-Jan-03
1-Jan-02
1-Jan-01
1-Jan-00
1-Jan-99
1-Jan-98
1-Jan-97
1-Jan-96
FED Model MSCI Europe
31-Jan-00
31-Jan-99
60
31-Jan-98
80
31-Jan-97
100
31-Jan-96
Price to Earnings MSCI Europe
1-Jan-95
1-Jan-09
1-Jan-08
1-Jan-07
1-Jan-06
1-Jan-05
1-Jan-04
1-Jan-03
1-Jan-02
1-Jan-01
1-Jan-00
1-Jan-99
1-Jan-98
1-Jan-97
1-Jan-96
1-Jan-95
11%
9%
7%
5%
3%
1%
-1%
-3%
-5%
-7%
-9%
-11%
-13%
-15%
31-Jan-95
31-Jan-09
31-Jan-08
31-Jan-07
31-Jan-06
-2 SD
31-Jan-05
31-Jan-04
+1SD
31-Jan-03
31-Jan-02
31-Jan-01
-1SD
31-Jan-00
31-Jan-99
Fed Model
31-Jan-98
31-Jan-97
31-Jan-96
Equity Market - Valuation
Price to Book MSCI Europe
4,50
4,00
3,50
3,00
2,50
2,00
1,50
1,00
+2 SD
Mean
8,00
Dividend Yield MSCI Europe
120
7,00
6,00
5,00
4,00
Fundamental analysis – some conclusions
Disciplined evaluation process improve risk – return profile of the investment
DCF models help to better understanding companies' operational dynamics and therefore to
better interpret different phases of the markets
It is important to knows the evaluation’s drivers (sales, margins, cash flows) to catch market’s
movements
Multiples allow to get a picture of the evaluation context immediately, and help to compare
evaluation over time
It is important to remember that even with non change on fundamentals, multiples should change
over time as a function of macro and market environment.
52
2. Strategic Asset Allocation
Portfolio’ s Construction
3 – Portfolio’s construction

The aim of Strategic Asset Allocation is to build solid and efficient portfolios over the long run.
•
Forecast accurately is difficult and not enough to generate stable performances in the long period.
Must have a framework in terms of rules and instruments for portfolio construction.
•
It requires a solid asset allocation tool and systematic approach to risk allocation and management.
•


54
1.
Knowing the risk exposure and the potential losses of the portfolio
2.
Knowing each tool’s contribution to overall risk
3.
Be able to intervene to modify the risk level
4.
Allows invested capital protection (discretionary choices are not enough)
In that sense risk management ex ante is a tool for managing portfolios, not only a tool for
controlling risk exposure. At the end portfolio management is the “discipline” of managing risk ex
ante.
If the phase of forecasting should be also qualitative and intuitively managed, the phase of
portfolio’s construction in by definition quantitative. Combining 10 assets classes, 2616 (!!!)
different portfolios can be created (thus compared)
There is empirical evidence that optimized portfolios generate better and more stable
performances for units of risk (Sharpe Ratio)
Diversification: Importance of activities’ number
Increasing activities’ number:
• efficient frontier improves, shifting upward
• single activities’ portfolio's variances contribution ( i hi i2) tends to 0, whereas covariance’s contribution
(

j
R
EFFICIENT
i
2hi h j  ij i2 2j ) tends to the mean covariance
FRONTIER
σ
n securities
n -1 securities
n -2 securities
σ
σij
n. attività
The more negatively correlated and more assets compose the portfolio, the
better the benefit of the diversification is
55
3 – Portfolio’s Construction: why is so important to diversify

Is impossible to forecast the best Asset Class on a systematic ways

History tells us that no exist asset class able to produce stable and positive return each year
Obbl. Gov. 3-5
Debito Emerg.
Corporate HY
Debito Emerg.
Commodities
Corporate HY
Commodities
Obbl. Gov. 3-5
Corporate HY
Commodities
Debito Emerg.
6,1%
13,1%
28,2%
11,7%
37,7%
11,7%
9,7%
8,8%
60,6%
26,2%
8,5%
Monetario
Obbl. Gov. 3-5
Debito Emerg.
Corporate HY
Az. globale
Debito Emerg.
Debito Emerg.
Monetario
Debito Emerg.
Az. globale
Obbl. Gov. 3-5
4,6%
8,7%
25,7%
11,4%
24,2%
9,9%
6,3%
4,0%
28,2%
18,1%
3,3%
Corporate HY
Monetario
Az. globale
Obbl. Gov. 3-5
Debito Emerg.
Az. globale
Monetario
Debito Emerg.
Az. globale
Corporate HY
Corporate HY
3,3%
3,4%
8,6%
5,6%
10,7%
5,7%
4,0%
-10,9%
22,7%
15,2%
3,1%
Debito Emerg.
Commodities
Obbl. Gov. 3-5
Az. globale
Corporate HY
Monetario
Obbl. Gov. 3-5
Corporate HY
Commodities
Debito Emerg.
Monetario
1,4%
-1,7%
3,8%
4,6%
3,1%
2,9%
3,4%
-27,1%
11,4%
12,0%
0,9%
Az. globale
Corporate HY
Monetario
Monetario
Obbl. Gov. 3-5
Obbl. Gov. 3-5
Corporate HY
Commodities
Obbl. Gov. 3-5
Obbl. Gov. 3-5
Commodities
-13,2%
-2,1%
2,4%
2,1%
2,9%
0,5%
1,6%
-36,0%
5,5%
1,5%
-4,2%
Commodities
Az. globale
Commodities
Commodities
Monetario
Commodities
Az. globale
Az. globale
Monetario
Monetario
Az. globale
-19,3%
-33,7%
-3,2%
0,9%
2,1%
-9,6%
-4,2%
-38,7%
0,7%
0,4%
-4,6%
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011

56
The best approach is a dynamic and systematic management of diversification
3 – Indicators for allocating and managing Risk
Main indicators to estimate ex-ante risk:
1.
VAR (Value at Risk) = maximum possible loss for a time horizon, given a certain level of
probability
2.
Expected Volatility = standard deviation of portfolio’s returns; indicates the possible returns’
fluctuations around the mean
3.
Beta (equity) and Duration (bond)
4.
Risk attribution for asset classes and financials tools
Expected volatility provides a simple information of portfolio overall risk. Limits of Var
methodology:
1. It forces a return’s distribution estimation, often mistaken
2. It does not explain the “rare event” outside the estimated probability
3. It is dangerous to declare to clients
57
3 – Volatility breaking down
It is important to break down the result in order to understand the different risk sources. The two
main fundamental indicators are:
1.
MCTR = Marginal Contribution To Risk; indicates how total portfolio volatility varies with an infinitesimal
increase of the weight of a security
2.
CAR = Contribution to Active Risk; indicates the contribution of the single security to the overall risk of the
portfolio
Increasing securities’
weight, overall risk
decreases
Increasing securities’
weight, overall risk
increases
58
3 – Inputs for Risk Budget, Optimizations and Portfolio’s Construction
Analysis of Financial’s Activities (DNA)
Volatilidad
Anualizada
Rentabilidad
Anualizada
Monetario
Inflation
linked
Renta fija
AAA Euro
Periféricos
Euro
Corporate Corporate Corporate
IG ST Euro IG Global
HY
Deuda
Em ergente
Renta Variable
Global
Com m odities
0,1%
4,7%
5,2%
1,5%
1,5%
3,8%
7,8%
6,0%
14,4%
16,2%
0,9%
7,9%
7,6%
3,8%
3,6%
8,5%
9,2%
11,2%
12,1%
-9,7%
Monetario
Inflation
linked
Renta fija
AAA Euro
Periféricos
Euro
Corporate
IG ST Euro
Corporate
IG Global
Corporate
HY
Deuda
Emergente
Renta Variable
Global
Commodities
5,2%
100,0%
1,4%
68,8%
100,0%
20,4%
15,3%
19,2%
100,0%
10,5%
23,1%
45,5%
28,8%
100,0%
11,4%
34,9%
44,4%
19,1%
82,3%
100,0%
4,7%
-13,3%
-0,3%
20,4%
60,3%
68,0%
100,0%
9,9%
-3,4%
3,5%
15,1%
59,0%
69,0%
63,1%
100,0%
1,8%
-29,6%
-21,1%
13,4%
19,1%
16,2%
41,1%
38,2%
100,0%
Matriz de
Correlación
Monetario
Inflation linked
Renta fija AAA Euro
Periféricos Euro
Corporate IG ST Euro
Corporate IG Global
Corporate HY
Deuda Emergente
Renta Variable Global
Commodities
59
100,0%
-9,5%
-11,5%
-15,7%
-4,8%
18,7%
23,5%
35,5%
50,3%
36,0%
100,0%
3 - Risk Budgeting and Portfolio’s Construction
Asset Class
Monetario
Liquidez
Periféricos Euro 6/12m
Renta Fija Core
Renta fija AAA Euro
Renta fija gobierno real
Renta Fija Spread
Peso
Contributo al
rischio
Contributo al
rischio
normalizzato
23%
0%
1%
8%
15%
0%
0%
0%
1%
5%
0%
0%
5%
0%
0%
0%
0%
30%
1%
14%
Corporate IG ST Euro
Corporate IG Global
10%
20%
0%
0%
2%
12%
Actividad de riesgo
42%
3%
85%
8%
14%
17%
3%
0%
1%
2%
0%
11%
17%
51%
7%
Corporate HY
Deuda Emergente
Renta Variable Global
Commodities
TOT
Vol max
Vol cartera
Risk Budget
60
100%
10,0%
4,0%
40%
Constraints:






Data from history: 104 weekly returns
Risk Profile: balanced
Maximum Volatility: 10%
Strategic Risk Budget: 40%
Duration: maximum 5 years
Max Equities + Commodities: 40%
3 - Optimization
A. Classic model: Mean-Variance
Minimize risk given a certain level of target return
Efficient Frontier
B. Model with views: Black- Litterman
Mean Variance + Views of Investment Committee
Efficient Frontier adjusted according to Asset Allocation’s Inputs
61
1 - Risk budget: example
Risk profile:
1.
Low (L): max volatility = 4%
2.
Medium (M): max volatility = 7%
3.
High (H): max volatility =10%
Base Portfolio (without views): Risk budget = 25%
Target volatility L = 25%*4% = 1%
Target volatility M = 25%*7% = 1,75%
Target volatility H = 25%*10% = 2,5%
R
H
M
L
1%
62
Target
portfolios
1,75%
2,5%
σ
1 - Example: output
Efficient Frontier
8,00%
7,00%
Target porfolio
Ret
6,00%
5,00%
4,00%
3,00%
2,00%
0,00%
2,00%
4,00%
6,00%
8,00%
10,00%
Risk
Efficient Frontier Portfolio
100%
Portafogli della FE
90%
100%
80%
90%
70%
80%
60%
70%
50%
60%
40%
50%
30%
40%
20%
30%
10%
20%
Commodities
63
Corporate
3,5%
3,2%
9,4%
3,0%
8,2%
2,8%
7,2%
2,6%
2,4%
6,5%
2,2%
5,9%
2,0%
5,3%
1,8%
4,8%
1,6%
4,3%
1,4%
3,9%
1,3%
3,5%
1,1%
CashCorporate
Govt Bond
3,1%
0,9%
Monetario
2,7%
0,8%
2,3%
1,9%
1,5%
0,6%
1,2%
0,5%
0,8%
0,3%
0,4%
0,2%
0%
0,2%
0,2%
0%
10%
Risk
Obbligazionario Govt
Equity
Commodities
Azionario
Risk
3. Tactical Asset Allocation
3- Tactical Asset Allocation
 To
improve returns for units of risk over time is important to adapt strategic
exposures according to short terms markets movements
 Basically there are two main disciplines for tactical allocation
 Tactical Risk Management – capital protection
 Technical Analysis – studying price movements
65
3. Tactical Asset Allocation
Tactical Risk Management
Risk management (ex ante) for Tactical Asset Allocation

To reduce volatility over time and try to protect capital part of the investment process must be
delegated to risk management tools not only to markets forecast

Independently of your forecast it is important having methodologies to adapt your portfolio
according to markets movements (often market itself is the best predictor..)

The quality of portfolio management depends also on the stability of return (management of
volatility)

Risk managemnt ex ante:
1.
Capital protection instruments (Total Return Products)
2.
Tracking Error ex ante (Benchmark’s products)
Responsibility: portfolio’s management department
67
Risk management ex ante: CPPI
CPPI (Constant Proportion Portfolio Insurance) is a quantitative management methodology strongly
oriented to risk control
It is based on dynamic portfolio rebalancing according to market’s movements. Basically correspond
to portfolio's insurance: portfolio has a floor that must be protected.
This strategy well performances in trend phases (up or downtrend)
CPPI better performance if:
1.
Main objective is volatility minimization (capital protection)
2.
The issue is Sharpe Ratio maximization (return for each unit of risk)
Strategies opposite to CPPI:
68
1.
Constant Mix: buys equities when they loss and sells when they grow. This strategy well performance along
“lateral” markets and bad along bear or bull markets
2.
Buy-and-hold: buy at the beginning and do not operate
CPPI: functioning
Components of dynamic portfolios:
1.
“Risky Asset”
2.
“Risk-Free Asset”
The two components’ weights are periodically optimized to benefit from eventual market increases,
giving capital protection.
•
Classical CPPI criteria:
“Risky Asset” = m (Nav – Floor) where:
m = constant multiplier
NAV = net asset
Floor = protected level
CPPI is worth only for m > 1 otherwise 2 special cases:
(a) m=1, floor= cash value -> “buy-and-hold” strategy.
(b) 0<m<1, floor= 0, -> “constant-mix” strategy .
69
CPPI - Example
Nav = 100 (net asset)
Floor= 75 (wealth protection level)
Multiplier = 2
Equity investment = 2 * (100 - 75) = €50
1.
Initial asset allocation = 50 € equity, 50 € cash.
2.
Net asset value remains >= 75 unless equity value is more than 25 €, thus –50%.
3.
Ratio 1/m = max loss endurable to protect the floor. 1/m in this case is –50%.
When risky activity loss value, total asset decreases
1.
Equity value from €50 to €45, Nav decreases to € 95 (=45+50).
Appropriate equity allocation:
1.
2 * (95-75) = €40
2.
 sell €5 equity; buy €5 cash  40 € equity, 55 € cash.
On the contrary, if equity gains -> buy.
70
Portfolio rebalancing
60
45
50
RiskFree
Asset
71
50
Risky
Asset
RiskFree
Asset
Risky
Asset
55
40
RiskFree
Asset
Risky
Asset
4 – Equity portfolio: tracking error management
Optimization
Titolo
ENI SpA
Tenaris SA
Saipem SpA
Buzzi Unicem SpA
Italcementi SpA
Finmeccanica SpA
Prysmian SpA
Impregilo SpA
Atlantia SpA
Fiat SpA
Pirelli & C SpA
Luxottica Group SpA
Bulgari SpA
Geox SpA
Lottomatica SpA
Autogrill SpA
Mediaset SpA
Arnoldo Mondadori Editore SpA
Seat Pagine Gialle SpA
Gruppo Editoriale L'Espresso SpA
Parmalat SpA
UniCredit SpA
Intesa Sanpaolo SpA
Unione di Banche Italiane SCPA
Banco Popolare SC
Banca Monte dei Paschi di Siena SpA
Banca Popolare di Milano Scarl
Mediobanca SpA
Assicurazioni Generali SpA
Alleanza Assicurazioni SpA
Fondiaria-Sai SpA
Unipol Gruppo Finanziario SpA
Mediolanum SpA
STMicroelectronics NV
Telecom Italia SpA
Fastweb
Enel SpA
Terna Rete Elettrica Nazionale SpA
Snam Rete Gas SpA
A2A SpA
Settore
Energy
Energy
Energy
Materials
Materials
Capital Goods
Capital Goods
Capital Goods
Transportation
Automobiles & Components
Automobiles & Components
Consumer Durables & Apparel
Consumer Durables & Apparel
Consumer Durables & Apparel
Consumer Services
Consumer Services
Media
Media
Media
Media
Food Beverage & Tobacco
Banks
Banks
Banks
Banks
Banks
Banks
Diversified Financials
Insurance
Insurance
Insurance
Insurance
Insurance
Semiconductors & Semiconductor
Telecommunication Services
Telecommunication Services
Utilities
Utilities
Utilities
Utilities
+
Quantitative Screening
+
Fundamentals analysis
Peso
19.52%
2.57%
0.61%
Final Portfolio
1.64%
0.51%
1.59%
1.94%
0.34%
1.05%
0.42%
0.81%
1.56%
0.19%
0.16%
1.04%
11.00%
11.32%
4.33%
2.85%
=
1.77%
11.18%
1.31%
0.70%
1.75%
4.92%
11.09%
1.84%
2.03%
+
Pair trades, only on particulat stocks
+
Markets exposure (80% - 100%)
72
Risk and
performance
control
4 - Optimization and minimization of tracking error
1. Way to replicate a portfolio with a wide number of securities in one with less securities in order to:
•
Reduce the transactional costs of re-balancing
•
Provide a background for the following active bets
2. Way to immunize the portfolio from: market, currency, sectors, style and size exposure
3. Way to concentrate on stock-picking
•
Market coverage 70%
• Sectors’ and market neutral
• “Style and size bias” monitoring
Benchmark
Titolo
73
ENI SpA
Tenaris SA
Saipem SpA
Buzzi Unicem SpA
Italcementi SpA
Finmeccanica SpA
Prysmian SpA
Impregilo SpA
Atlantia SpA
Fiat SpA
Pirelli & C SpA
Luxottica Group SpA
Bulgari SpA
Geox SpA
Lottomatica SpA
Autogrill SpA
Mediaset SpA
Arnoldo Mondadori Editore SpA
Seat Pagine Gialle SpA
Gruppo Editoriale L'Espresso SpA
Parmalat SpA
UniCredit SpA
Intesa Sanpaolo SpA
Unione di Banche Italiane SCPA
Banco Popolare SC
Banca Monte dei Paschi di Siena SpA
Banca Popolare di Milano Scarl
Mediobanca SpA
Assicurazioni Generali SpA
Alleanza Assicurazioni SpA
Fondiaria-Sai SpA
Unipol Gruppo Finanziario SpA
Mediolanum SpA
STMicroelectronics NV
Telecom Italia SpA
Fastweb
Enel SpA
Terna Rete Elettrica Nazionale SpA
Snam Rete Gas SpA
A2A SpA
Settore
Energy
Energy
Energy
Materials
Materials
Capital Goods
Capital Goods
Capital Goods
Transportation
Automobiles & Components
Automobiles & Components
Consumer Durables & Apparel
Consumer Durables & Apparel
Consumer Durables & Apparel
Consumer Services
Consumer Services
Media
Media
Media
Media
Food Beverage & Tobacco
Banks
Banks
Banks
Banks
Banks
Banks
Diversified Financials
Insurance
Insurance
Insurance
Insurance
Insurance
Semiconductors & Semiconductor
Telecommunication Services
Telecommunication Services
Utilities
Utilities
Utilities
Utilities
Minimum tracking error portfolio:
Peso
18.82%
1.88%
1.39%
0.34%
0.27%
1.50%
0.37%
0.29%
1.59%
1.94%
0.34%
0.98%
0.35%
0.14%
0.55%
0.27%
1.52%
0.15%
0.12%
0.08%
1.04%
10.37%
10.69%
3.70%
2.22%
1.71%
0.81%
1.77%
10.93%
1.06%
0.45%
0.41%
0.33%
1.75%
4.80%
0.12%
10.78%
1.53%
1.72%
0.93%
Titolo
ENI SpA
Tenaris SA
Saipem SpA
Buzzi Unicem SpA
Italcementi SpA
Finmeccanica SpA
Prysmian SpA
Impregilo SpA
Atlantia SpA
Fiat SpA
Pirelli & C SpA
Luxottica Group SpA
Bulgari SpA
Geox SpA
Lottomatica SpA
Autogrill SpA
Mediaset SpA
Arnoldo Mondadori Editore SpA
Seat Pagine Gialle SpA
Gruppo Editoriale L'Espresso SpA
Parmalat SpA
UniCredit SpA
Intesa Sanpaolo SpA
Unione di Banche Italiane SCPA
Banco Popolare SC
Banca Monte dei Paschi di Siena SpA
Banca Popolare di Milano Scarl
Mediobanca SpA
Assicurazioni Generali SpA
Alleanza Assicurazioni SpA
Fondiaria-Sai SpA
Unipol Gruppo Finanziario SpA
Mediolanum SpA
STMicroelectronics NV
Telecom Italia SpA
Fastweb
Enel SpA
Terna Rete Elettrica Nazionale SpA
Snam Rete Gas SpA
A2A SpA
Settore
Energy
Energy
Energy
Materials
Materials
Capital Goods
Capital Goods
Capital Goods
Transportation
Automobiles & Components
Automobiles & Components
Consumer Durables & Apparel
Consumer Durables & Apparel
Consumer Durables & Apparel
Consumer Services
Consumer Services
Media
Media
Media
Media
Food Beverage & Tobacco
Banks
Banks
Banks
Banks
Banks
Banks
Diversified Financials
Insurance
Insurance
Insurance
Insurance
Insurance
Semiconductors & Semiconductor
Telecommunication Services
Telecommunication Services
Utilities
Utilities
Utilities
Utilities
Peso
19.52%
2.57%
0.61%
1.64%
0.51%
1.59%
1.94%
0.34%
1.05%
0.42%
0.81%
1.56%
0.19%
0.16%
1.04%
11.00%
11.32%
4.33%
2.85%
1.77%
11.18%
1.31%
0.70%
1.75%
4.92%
11.09%
1.84%
2.03%
4 - Quantitative screening
1. Way to limit the broad investible universe within logical criteria
2. First step of the active portfolio management
DJ STOXX 600
(600 stocks)
Quantitative
Screening
100
securities
Financial
Analysts
50 securities
For a good quantitative screening it is necessary:
1. Breaking down the investible universe in comparable subgroups (sectors)
2. Implementing the screening models in subgroups, according to specific indicators applied to each
group
74
4 - Risk management
1. Tracking error
2. Tracking error decomposition
75
3. Tactical Asset Allocation
Technical Analysis
76
Context
77

Introduction

Trend Analysis

Chart types

Moving Averages

Oscillators

Market size
Technical Analysis
Why useful: once fundamental analysis says an asset is under or overvalued, technical analysis helps
in determine the market entry and exit timing
Strength point: flexibility and adaptability:
1.
Applicable to any market and activity
2.
It identifies what fundamental analysis fails to, as asset price patterns
3.
Mix of analysis methodologies easily affordable
4.
No difficult data retrieval
5.
Useful in formulating short, medium and long term forecasts
Technical analysis contribute to limit mistakes identifying stop profits and losses
78
2 – Market has three trends ( long, medium, short )
Primary trend is the most important and lasts more than a year. Can be bullish or bearish
Secondary trend traces corrective phases of the primary trend, moving in countertrend compared to it.
Can last from three weeks to months
Minor trend, short lasting, easily “manipulable”, thus can be ignored
Examinee graphic bias enables to identify three trend typologies:
1. Uptrend, when quotations move drawing a set of increasing troughs and peaks
2. Downtrends, when quotations move drawing a set of decreasing troughs and peaks
3. Sideways, when quotations move draw a set of troughs and peaks which confirm previous
levels
79
3 – Trend line
Trend lines are straight lines which define the identified trend
The bullish trendline is obtained by linking a set of increasing troughs, the bearish trendline is
obtained by linking a set of decreasing peaks
The larger the number of troughs or peaks reached are and the longer the time horizon is, the more
significant are the trendlines
The break of a trendline, along with an increase in volumes and with the impossibility of shortly
recovering of the lost level, indicates that the actual upward movement is near the reverse tendency
The correction movement subsequent to the break of a trendline causes a re-trace of the previous
movement generally included between 33 and 66%, in the most cases the re-trace places aroud 50%
80
AMERICAN EXPRESS - da 05/03 a 12/07 - Long uptrend trendline
81
4 – Volumes must support the trend
Volumes must move in the same direction as the trend one, thus during the trends:
1.
uptrend, volumes increase during bullish phases and decrease during bearish phases
2.
downtrend, volumes increase during bearish phases and decrease during bullish phases
Volume is an important confirmation of the trend
The maximum peak of volumes occurs short before the trend inversion in action, independently to
its direction. This is one of the most important alarm signal provided by the volumes.
82
Chart types
Chart types most used are:
1 – Line chart
2 – Bar chart
3 – Candlestick chart
4 – Point & Figure chart
For the graphic representation arithmetic or log scale can be used
1 – Line chart
Line chart does not provide much information, the one point represents the closing price of the
evaluated asset
This chart type is generally used to represent:
84
1.
economic data
2.
indicators
3.
very long graph
2 – Bar chart
Bar chart provides more pieces of information:
1. open, left dash
2. close, right dash
3. minimum, inferiore tip of the vertical line
4. peak, upper tip of the vertical line
5. maximum daily range, difference between peak and
minimum
85
3 – Candlestick chart
Candlestick chart provides visual information for both single and composed
figures:
1. Bullish market, white body
2. Bearish market, black body
3. opening, white rectangle lower side and black rectangle upper side
4. closing, white rectangle upper side and black rectangle lower side
5. minimum, figure’s lower extremity
6. peak, figure’s upper extremity
7. maximum daily range, difference between peak and minimum
8. shadow, lines outside the rectangle representing price levels not
sustainable in that specific period. The longer the lines, the more
significant they are
86
Nasdaq composite – from 05/08 to 10/08 – Candlestick chart
87
Moving Averages
Moving averages provide market’s direction. Their sensibility derives from the data numbers which has
created with
Three types of moving averages are used: simple, weighted and exponential
Simple moving average is the ratio between the sum of the data of a specific period and the total of the
values
Weighted and exponential moving average are made up to overweight data momentum
For more correct analysis combination of moving averages are frequently used. Averages follow the
trend, thus during uptrends they are bullish oriented and vice versa
88
S&P 500 - form 04/00 to 10/08 – Simple Moving Average at 100 and 200 days
89
Oscillators
Oscillators are secondary indicators subordinated to trend analysis.
During well defined trend phases (bullish or bearish) oscillators are useful in order to:
1. Point out short term “excesses” (overbought or oversold)
2. Signal “strength” losses of the in action trend (momentum)
3. Anticipate the end of the trend (negative or positive divergences)
Oscillators are tools extremely useful during “lateral” markets as peaks and minimums of the graph
exactly coincide with oscillator’s peaks and minimums, given that they both move sideways
90
1 – Oscillators
Momentum + ROC (Rate of Change)
“Momentum” and ROC are oscillators that estimate the speed and acceleration with which prices move
Momentum = Closing price x – Closing price of x-n
ROC = 100 * [(closing price x – closing price x-n) / closing price x-n]
Values obtained oscillate around zero line. A value over/under these levels indicates increasing/decreasing prices during
the esteemed period.
RSI (Relative Strength Index)
Oscillator estimates market’s strength, resolving the problem of erratic movements and satisfying the constant need of
a superior and inferior track
RSI = 100 – {100 / [1+ (average of the uptrend closings of n days / average of the downtrend closing of n days)]}
Values obtained oscillate between zero and 100, furthermore, conventionally, a upper line and a lower line at a level of
70 and 30 respectevely (80 and 20 for more sensible oscillators)
91
Market size
Advance / Decline line
The indicator is made up with the total of the cumulated differences between the securirties componing an uptrend
index and those downtrend, given a specific period
Markets made up of marked trend must be confirmed by a huge numbers of securities coherent (with their
fluctuations) with that movement
% of equities over/under a moving average
The indicator highlights the number of securities over or under the specified moving average. The most used moving
averages are those at 50, 100 and 200 days
This indicator usually moves alongside the index trend
Divergence points between indicator, index and excess hypothetical situations must be taken into account
Securities which mark new peaks/minimums
The indicator is made up calculating the equities’ number that registered new peaks and new minimums at 53 weeks
The basic principle is that an upside marked must come with a fair number of new net peaks
92
4. Global Fund Selection
2 – Portfolio management: financials tools selection
Portfolio Return = asset classes returns + alfa generation – costs (management fees).

To create stable returns is very important to allocate costs efficiently

Identify Optimal trade off between costs and Alfa generation


Concentrate costs where there is evidence of Alfa generation (active funds). Typically equities
and credits markets
Minimize costs where there is not evidence of Alfa generation (passive funds or Etfs). Typically
money markets and governments bonds markets
Importance of open architecture: possibility to buy the best products for each asset class or markets
Responsibility: fund’s analysis department
94
Global Funds Selection Process
A team focused on the analysis and selection of third party funds globally with the objective of:
1. Homogenize the fund selection procedure
2. Elaborate a Global Focus List
3. Continuous monitoring of the funds within the list
In a process with the following characteristics:
1. Independence
2. Open Architecture
3. Proprietary Model
4. Integrated into the bank: Risk Management division involved in the fund admission process
Fund Selection Team
95
Risk Management
GLOBAL FOCUS LIST
Global Team Analysis
Homogenize the fund
selection
Elaborate a Global Focus
List

To enhance the selection model interaction among product
specialist of different units

Adapting the Focus List to the local needs of every Division
(registration, distribution, niches, etc).

Determination of niches and funds recommended at a global
level.

Compatible with all the platforms: Custody, Advisory and
Discretionary Management.

A monthly Committee will revise the focus list and analyze new
niches from a double perspective; distribution and management

Dynamic review and monitoring of the recommended Focus List.
Monitoring
96
Global Team Analysis
Indipendence
Own & Third Partis Funds Analysis
Quantitative & Qualitative Analysis
Risk – Funds Ammission
Team dedicated to the selection of funds globally, with the aim of:
Selection process
consistent in all units
97
Global Focus
List
Systematic
Monitoring
Fund Selection Process
Fund Universe of 20.000 Funds / 400 Fund Houses
Minimum
Requirements
Track-record, liquidity, AUM
Quantitative Model
Risk – Return Binomial
Qualitative Model
Team Management Quality
Risk Management
Team
Due-diligence
80 Funds / 40 Fund Houses
98
The Best Funds
Universe of Analysis
Start Point: no restrictions in choosing the best funds
Wide range via the platform AllFundsBank
20.000 Funds
400 Fund Houses
Open Architecture: 20.000 Funds out of 400 Fund Houses available
 Broader investment funds universe
 No restrictions in choosing from the largest number of fund houses and funds
 Searching for the best funds and the most prestigious and specialized fund houses
99
Minimum Requirements
First qualitative and quantitative screening:

Asset Under Management: minimum 100 Million Euro or equivalent

Liquidity: Daily NAV

Track Record: minimum 1 years of fund’s history

100
Documentation: availability of information needed to analyze and process the credit
rating of the fund and housing management
Funds Selection: the importance of Proprietary Model
Quantitative Rating
Minimum fund analysis requirements:

€100 MM of AUM or equivalent

Daily NAV

One year from inception (3 years preferably)

Enough documentation to elaborate a proper
rating of the fund and the asset management
company
Weight of 60%
+
Qualitative Rating
Weight of 40%
101
Proprietary Model
Rt
 Profitability:
Absolute Ratios
1 and 3 Rolling
years

 Standard Deviation :
SR 
 Sharpe Ratio :
Re ntabilidadanualizada Rf
Downside deviation
 Maximum Drawdown
 Sortino Ratio
 Kurtosis
 Skewness
Kurtosis 
S
(
FRt  Rt
 ft
xx

)4
n
Quantitative Rating
3
x x
n
 ( i ) 3
(n  1) (n  2)
Weight of 60%
Relative Ratios
1 and 3 Rolling
years
FRi  MRi
T .E
  R p  R t   R m  R t  
Jensen’s Alpha :
R2:
102
IR 
Info Ratio:
S 2 XY
R  2 2
S XS Y
2
Proprietary Model
Quantitative analysis is necessary… but before arriving to a conclusion
funds should be analyzed from a different point of view too
103
Proprietary Model
 AM Company Valuation
Qualitative Rating
Based on:
 Transparency
Weight of 40%
 Service
Information quality, etc
 Due Diligence
Questionnaires with key information regarding:
Investment Process
Organization
Risk Management, etc...
 Fund Manager Valuation
Minimum qualitative fund analysis requirements:

Access to portfolio details

Monthly information of AUM´s evolution

Monthly Attribution

At least, quarterly meeting or CC with the fund
managers

Communication of relevant information regarding
investment process, team changes, NVA
suspension, etc.
 Made
by the asset class analyst after
meeting the manager team
104
Risk Management
Once the analysis and selection of funds has been completed, according to the model explained
in the previous pages, Control and Risk department will centralize the admission process and
the monitoring of the funds
The admission process implies:
1. Send a request to Risk Management in order to evaluate the inclusion of a fund. The following
documentation must be attached:
 Asset management company
 Asset management company’s Due Diligence
 Audited financial accounts (last 2 years)
 Fund
 Fund’s due diligence
 Latest factsheet
 Full prospectus and/or offering memorandum
 Audited financial accounts
Once a year the admitted funds list, volumes and general situation will be reviewed
105
The result: Global Focus List
GLOBAL
FOCUS LIST
Bi-Weekly Committee
E
Q
U
I
ABSOLUTE
T
RETURN
Y
F
I
X
E
D
I
N
C
O
M
E
106
TEMATICS
LOCAL
FOCUS LISTS
Fund Committee
 The committee’s objective is to establish which funds compounds the Global Focus
List as well as those of the Local Focus List in each business unit
 The Fund Committee is the place where the Fund Selection Team will:
 Present the current Focus List.
 Include in the Focus List a potential new entry requested by different divisions if
there is a real demand due to diversification or investment needs
 Will follow the funds evolution included in the Focus List.
107
Funds Selection Process: Monitoring single instrument
 Relevant management team
changes
Critical
Alerts (C)
 NAV suspension
UNDER REVISION (UR)
MAX 3 MONTHS
 Reputational Risk (sanctions o
irregulars practices)
 Control Alert
DECISION
HOLD
SELL
Underperformance vs.
peers
Follow Up Alerts
(FU)
AUM drop > 20% month
Max. Drawdown
2 Standard Dev. break
Investment process change
M&A
108
DUE DILIGENCE
MAX 48 HOURS
The process: the importance of communication
Key Information elaborated by Fund Selection Team:
 The issue of alerts, quick updates and following updates will be sent to all the committee members by
e-mail.
 The team will elaborate a monthly and quarterly document of each asset class and each time there is
a meeting with a Focus List PM.
ALERTS
+
Critical (C)
QUICK UPDATES &
FOLLOWING
Focus Fund
Follow up (FU)
MONTHLY
Asset class
Focus Fund
109
+
QUARTERLY
E-MAIL
Committee
assistants
DOCUMENTATION
Markets
Mail
Asset class + fund FL
Intranet
Results
The goal is not to select the best fund of the month but select funds that are firmly
in the top quartile.
The Focus List of Funds have outperformed the market average in all
categories
110
5. Control and Reporting
3 – Control and reporting


Risk management ex-post: verify that risk constraints (volatility, Var) are respected
1.
Volatility ex-post
2.
VaR ex-post
3.
Risk Attribution ex post
Performance analysis: absolute and for units of risk
•
•
Benchmark
Security Selection:
(Rp-Rb)*Wb
Asset Allocation:
(Wp-Wb)*Rb
Interaction Effect:
(Rp-Rb)*(Wp-Wb)
Total return
Asset Allocation:
Rb*Wp
Security selection:
(Rp-Rb)*Wp
Rp is the Return of the asset (security) in the portfolio, Rb is the Return of the asset in the benchmark, Wp is the weight
of the asset in the portfolio and Wb the weight of the asset in the benchmark.
112
3 – Risk management ex post: indicators for control
Daily verify mandate constrains respect
1. Ex-post volatility: square root of the sum of the daily square returns’ standard deviations (Rt)
R
and the returns mean sample
( )
ˆ 

n
t 1
( Rt  R ) 2
n 1
n = observations’ number
2. VaR ex-post: α-esim percentile of a normal distribution with mean and variance equal to mean
( R ) and variance sample ( ˆ 2) of daily observed returns
VaR  R  Zˆ
Zα = α-esim percentile of a normal standardized
3. Tracking Error Volatility (TEV): historical volatility of the mean sample gap between asset
return (i) and benchmark return (b):
TEVi  ˆ ( Ri  Rb )
113
3 – Ex-post risk control
4. Information Ratio (IR): active return divided by tracking error, where active return is the
difference between the return of the security and the return of a selected benchmark index, and
tracking error is the standard deviation of the active return
IRi 
Ri  Rb
TEVi
5. Sharpe Ratio (SR):measure of the excess return per unit of risk in an investment asset or a
trading strategy (used for total return approach)
Ri  Rrf
SRi 
ˆ i
•
Maximum Draw Down (MDD): max cumulated loss from the former peak during a specific time
horizon [t0, T]
MDD t0T  max R(t1 )  R(t 2 )
t1t 2 [ t0 ,T ]
114
4 – Performance analysis
 Monitoring absolute portfolio performance
 Determining performance’s contribution of each asset class
 Breaking down of asset allocation and stock picking contributions with Brinson model:
Benchmark
Asset Allocation:
(hp- hb)*Rb
Stock picking:
(Rp- Rb)*hb
Interaction Effect:
(Rp- Rb)*(hp- hb)
Total Return
Asset Allocation:
Rb*hp
Stock picking:
(Rp-Rb)*hp
hp = weight asset in the portfolio, hb = weight asset in the benchmark
Rp = return of the asset in the portfolio, Rb = return of benchmark
115
Breaking
down
DELTA
RETURN against benchmark
Breaking
RETURN
down
portfolio
4 – Performance: benchmark VS Total Return
Benchmark
Total Return
Strategic and tactical Asset Allocation  Management
Strategic Asset Allocation  Benchmark
Tactical Asset Allocation  Management
Monitoring portfolio absolute return and breaking
down in :
Monitoring delta contribution against benchmark
and breaking down in:
Tactical Asset Allocation
Security selection
Interaction Effect (security selection effect induced
by asset allocations decisions)
116
 Asset Allocation
 Security selection
4 – Example: Benchmark
Growth Strategy
Month to date
TOT PTF
-1,50%
TOT BCMK
-1,11%
Update date 08-30-2013
Start Date 04-16-08
AA = Asset Allocation
DELTA
-0,39%
SP = Selection
IN = Interaction effect
Asset Class
Cash
Bond
SANTANDER EURO CREDIT
PIMCO GLOBAL IG
Present
Weight
Bcm k
Weight
Delta
Perf
Delta
Contribution
11,9%
10,8%
5,0%
20,0%
6,9%
-9,2%
0,01%
0,02%
0,00%
-0,06%
0,04%
-0,95%
4,4%
6,4%
Equity
77,3%
Global
14,2%
MFS MERIDIAN GLOBAL EQUITY "I1" (EUR) 7,3%
JPM GLOBAL FOCUS "B"
6,9%
Europe
27,5%
MFS MER-EUROPEAN VALUE-I1€
5,5%
INVESCO PAN EUROPEAN EQUITY
11,4%
THREADNEEDLE PAN EUR-€
10,8%
USA
19,2%
JPM US Select Equity D Acc USD
12,1%
ROBECO US PREMIUM EQ-I$
7,2%
Japan
6,8%
SCHRODER INTERN SELECT FUND-JAPANESE
6,8%
Asia Ex Japan
4,1%
M&G Investment Fund-ASIAN
4,1%
Emerging
5,4%
ABERDEEN GL-EMMKT EQTY-I2
5,4%
TOT
117
100,0%
75,0%
2,3%
-7,5%
20,0%
-0,8%
8,0%
-1,2%
5,0%
-0,9%
7,0%
-1,6%
100,0%
0,0%
AA
SP
-0,30% -0,18%
DELTA
0,08%
IN
0,09%
IN
Perf
Delta
Contribution
0,00% 0,00%
0,00% -0,11%
0,00%
0,05%
0,02%
0,35%
0,00%
-0,07%
0,00%
-0,06%
0,00%
0,00%
0,00%
-0,12%
0,00%
0,05%
0,33%
-0,25%
-1,31%
-0,34%
-0,30% -0,07%
0,03%
-2,81%
-2,12%
-0,75%
-0,90%
1,30%
-1,02%
-2,84%
-2,81%
-2,93%
-2,27%
-3,06%
-0,51%
-1,50%
-1,60%
-4,72%
-0,11%
-0,08%
-0,03%
0,23%
0,00%
0,25%
-0,01%
0,02%
-0,14%
-0,09%
-0,04%
-0,04%
-0,04%
-0,04%
-0,15%
-0,15%
-0,16%
-0,08%
-0,08%
0,04%
0,01%
0,02%
0,02%
-0,22%
-0,14%
-0,08%
0,02%
0,02%
0,00%
0,00%
0,02%
0,02%
0,02%
0,00%
0,02%
-0,05%
0,00%
-0,07%
0,01%
0,24%
0,00%
0,00%
0,01%
0,01%
0,01%
0,01%
0,05%
0,05%
14,2%
35,0%
Quarter to date
TOT PTF
1,49%
TOT BCMK
1,41%
AA
SP
0,03%
0,00%
0,03%
0,25%
-0,01%
0,30%
-0,04%
0,00%
0,00%
-0,01%
-0,07%
-0,07%
-0,05%
-0,05%
-0,22%
-0,22%
Year to date
TOT PTF
8,14%
TOT BCMK
5,33%
AA
SP
-0,33% 0,17%
DELTA
2,80%
IN
0,23%
AA
SP
IN
0,80%
2,07%
-0,07%
AA
SP
IN
IN
Perf
Delta
Contribution
0,00% 0,00%
-0,03% -0,07%
0,00%
0,03%
0,05%
0,86%
0,03%
-0,31%
0,00% 0,01%
-0,07% -0,43%
0,02%
0,20%
-0,01%
-0,06%
-0,01%
-0,02%
0,00%
0,03%
1,11%
-2,91%
-0,02%
-0,29%
-0,03%
-0,04%
0,02%
-0,45%
-0,01%
0,21%
1,30%
-0,13%
-0,30% 0,25%
-0,08%
5,78%
2,94%
0,88%
2,51%
-0,44%
1,45%
3,69%
4,32%
3,07%
8,52%
3,88%
0,47%
1,90%
1,21%
-2,92%
-3,04%
1,19%
-1,02%
-2,31%
-6,48%
0,26%
-0,01%
0,23%
-0,09%
-0,15%
0,27%
-0,21%
0,27%
0,20%
0,07%
0,01%
0,01%
-0,11%
-0,11%
-0,21%
-0,21%
0,03%
-0,13%
0,01%
-0,40%
-0,08%
-0,16%
-0,16%
0,04%
0,03%
0,02%
0,02%
0,02%
-0,01%
-0,01%
0,02%
0,02%
0,10%
0,05%
0,09%
-0,09%
0,02%
-0,13%
0,01%
0,09%
0,07%
0,02%
0,00%
0,00%
0,02%
0,02%
0,07%
0,07%
12,58%
10,37%
6,31%
11,60%
18,27%
12,10%
14,14%
18,65%
21,61%
12,41%
12,03%
-4,56%
-3,39%
-12,18%
-13,44%
-0,06%
-0,01%
0,11%
1,25%
0,10%
0,87%
0,28%
1,82%
1,04%
0,78%
-0,27%
-0,27%
0,08%
0,08%
0,07%
0,07%
0,73%
-0,13%
0,35%
-0,70%
-0,15%
-0,28%
-0,28%
0,92%
0,59%
0,34%
-0,22%
-0,22%
0,03%
0,03%
0,11%
0,11%
-0,49%
0,07%
-0,16%
2,57%
0,32%
1,51%
0,74%
0,53%
0,26%
0,27%
-0,06%
-0,06%
0,06%
0,06%
-0,10%
-0,10%
-0,29%
0,05%
-0,09%
-0,62%
-0,08%
-0,37%
-0,18%
0,37%
0,19%
0,18%
0,00%
0,00%
-0,01%
-0,01%
0,06%
0,06%
AA
SP
0,00%
-0,07%
0,14%
0,07%
0,13%
0,41%
-0,09%
0,56%
-0,06%
0,13%
0,10%
0,03%
-0,02%
-0,02%
-0,11%
-0,11%
-0,30%
-0,30%
4 – Example: Total Return
Rainbow 7
Month to date
Update date 08-30-2013
AA = Asset Allocation
Start Date 12-15-08
SP = Selection
Asset Class
Monetario
Obbligazionario Gov
CCT-eu 15/12/2015
Obbligazionario IG
SANTANDER EURO CREDIT
HENDERSON H. EURO CORPORATE BOND "I2"
PIMCO GLOBAL IG
M&G European Corporate Bond
Attività di rischio
Obbligazionario Emergenti
MFS Emerging Markets Debt Fund
Obbligazionario Corporate HY
GS GLOBAL HIGH YIELD PORTFOLIO "I" (EURHDG)
Azionario
Globale
JPM GLOBAL FOCUS "B"
MFS MERIDIAN GLOBAL EQUITY "I1" (EUR)
Europa zona €
BGF-EURO MKTS FUN-D2
Stati Uniti Hedged
THREADNEEDLE AMER SEL "2" INA (EURHDG)
Emergenti
ROBECO EMERGING MARKETS EQ "I" (EUR)
Commodities
VONTOBEL BELVISTA COMMODITY "HI" (EURHDG)
TOT
Duration
118
Quarter to date
TOT
-0,64%
AA
SP
-0,62%
-0,02%
Year to date
TOT
0,87%
AA
SP
0,51%
0,35%
TOT
-0,12%
AA
SP
-0,45%
0,33%
Present Weight
Perf
Contribution
AA
SP
Perf
Contribution
AA
SP
Perf
Contribution
AA
SP
27,38%
10,09%
0,01%
0,02%
0,01%
0,02%
0,00%
0,00%
0,01%
0,02%
0,02%
0,41%
0,06%
0,11%
0,00%
0,04%
0,05%
0,07%
0,05%
0,96%
0,14%
-0,01%
0,02%
-0,06%
0,13%
0,06%
10,09%
0,22%
0,02%
0,00%
0,02%
1,08%
0,11%
0,04%
0,07%
2,86%
0,17%
0,08%
0,09%
31,80%
-0,26%
-0,09%
-0,08%
-0,01%
0,47%
0,22%
0,15%
0,07%
0,51%
-0,14%
0,03%
-0,17%
9,12%
8,70%
5,93%
8,05%
0,04%
-0,25%
-0,95%
-0,18%
0,00%
-0,02%
-0,06%
-0,01%
0,01%
-0,03%
-0,02%
-0,03%
0,00%
0,01%
-0,03%
0,02%
0,33%
0,94%
-0,25%
1,61%
0,03%
0,08%
-0,01%
0,13%
0,05%
0,04%
0,03%
0,04%
-0,02%
0,04%
-0,04%
0,09%
1,11%
0,77%
-2,91%
2,00%
0,10%
-0,14%
-0,20%
0,10%
0,12%
-0,15%
0,04%
0,02%
-0,02%
0,01%
-0,23%
0,08%
30,73%
-1,65%
-0,58%
-0,55%
-0,04%
1,52%
0,48%
0,32%
0,16%
3,57%
-0,12%
-0,43%
0,31%
-2,68%
-3,32%
-0,59%
-0,93%
-1,95%
-2,04%
-2,12%
-2,81%
-1,10%
-0,37%
-3,16%
-2,04%
-1,60%
-0,49%
2,97%
2,47%
-0,18%
-0,18%
-0,06%
-0,06%
-0,37%
-0,25%
-0,09%
-0,17%
-0,05%
-0,05%
-0,06%
-0,06%
0,00%
0,00%
0,02%
0,02%
-0,14%
-0,14%
-0,04%
-0,04%
-0,40%
-0,21%
-0,08%
-0,13%
-0,08%
-0,08%
-0,10%
-0,10%
-0,01%
-0,01%
0,03%
0,03%
-0,04%
-0,04%
-0,02%
-0,02%
0,03%
-0,05%
0,00%
-0,04%
0,03%
0,03%
0,04%
0,04%
0,01%
0,01%
-0,01%
-0,01%
-1,76%
-1,93%
1,63%
1,43%
2,27%
1,53%
3,69%
1,45%
5,11%
6,23%
1,51%
3,28%
-2,31%
-0,96%
3,83%
4,40%
-0,09%
-0,09%
0,08%
0,08%
0,43%
0,15%
0,14%
0,01%
0,20%
0,20%
0,10%
0,10%
-0,01%
-0,01%
0,04%
0,04%
-0,08%
-0,08%
0,10%
0,10%
0,26%
0,08%
0,06%
0,02%
0,16%
0,16%
0,04%
0,04%
-0,02%
-0,02%
0,04%
0,04%
-0,01%
-0,01%
-0,01%
-0,01%
0,17%
0,07%
0,08%
-0,01%
0,04%
0,04%
0,05%
0,05%
0,01%
0,01%
0,00%
0,00%
-9,84%
-9,15%
2,18%
3,05%
8,20%
9,69%
10,37%
12,58%
5,75%
12,74%
14,15%
15,24%
-12,18%
-11,81%
-4,35%
-7,75%
-0,66%
-0,66%
0,16%
0,16%
0,48%
0,23%
0,10%
-0,10%
0,33%
0,33%
0,33%
0,33%
-0,45%
-0,45%
-0,10%
-0,10%
-0,76%
-0,76%
0,11%
0,11%
0,27%
0,17%
0,10%
-0,13%
0,12%
0,12%
0,31%
0,31%
-0,43%
-0,43%
-0,05%
-0,05%
0,10%
0,10%
0,05%
0,05%
0,21%
0,06%
-0,01%
0,04%
0,22%
0,22%
0,01%
0,01%
-0,02%
-0,02%
-0,05%
-0,05%
5,20%
5,20%
5,92%
5,92%
18,60%
9,66%
4,00%
5,66%
4,92%
4,92%
3,02%
3,02%
1,00%
1,00%
1,01%
1,01%
100,00%
2,28
Module 5. Case Study
119
Phases of an investment’s process
1. Identify investor’s characteristics and goals
•
Risk profile
•
Approach (Total Return vs Benchmark)
•
Time horizon
2. Portfolio management
•
Forecast risk and return for each asset class
•
Construct efficient portfolios (optimization)
•
Choosing the most efficient financials instruments (stocks, Etf, mutual funds, etc)
•
Risk management ex ante (CPPI, risk attribution)
3. Control and reporting
120
•
Risk analysis ex post
•
Performance attribution
1 – Total Return Approach: Risk profile
Low
Medium
High
4%
7%
10%
Equity:
0 – 20%
0 – 35%
0 – 50%
Bond:
80% - 100%
65% - 100%
50% - 100%
Mifid profile:
Conservative
Moderate
Equilibrate
2 years
3 years
5 years
Maximum volatility
Investment term:
121
2 - Macroeconomic Forecasts
122
World
GDP
Inflation
USA
GDP
Inflation
Fed Funds
10 yrs Interest Rate
Europe
GDP
Inflation
BCE Funds
10 yrs Interest Rate
Japan
GDP
Inflation
O/N Call Rate
10 yrs Interest Rate
Emerging
GDP
Inflation
2013 Forecast
2014 Forecast
3,1%
2,6%
3,9%
3,0%
1,8%
1,5%
0,2%
2,8%
2,9%
1,6%
0,2%
3,8%
-0,4%
1,5%
0,5%
2,0%
1,0%
1,6%
0,5%
2,9%
1,7%
0,0%
0,02%
1,0%
1,5%
1,8%
0,02%
1,7%
5,2%
4,5%
5,6%
4,6%
Central scenario
Recovery as U
80%
Recovery as W
20%
Developed economies benefit from the cycle
of stocks and emerging demand.
Comsumption, even slighly, increases both to
avoid negative GDP data
Recovery from the supply side is not
supported by demand in developed
economies. Increased risk of relapse in
the US than in Europe
Probability of strong increase of raw
materials, thanks to the economic recovery
Correction of the rise of raw materials,
without the slightest touch of 2009
The lending improves slowly both on supply
and demand side
Specific episodes of financial stress.
Lending below the historical average
Small inflationary pressures as for the
weakness of demand in the OECD
Very low inflation
Interest rates stable in the medium term. The
central banks start to thinkn about exit
strategy
Expansionary monetary policy and
backwardness of the exit strategy. Rates
steady until 2014
123
Our scenario (80%)
 We’re positive on fundamental side. Last economic data support our
scenario of a global sustainable growth:
•
USA: last data confirm the strengthening of the economy
•
Eurozone: signals of recovery, although remains some differences between core economies
and peripheral countries
•
Emerging: lack of momentum, even if macro context is still positive. Chinese data shows a
moderate growth, but more healthy and sustainable
 Central Banks are still supporting
accommodative monetary policies
economic
growth
through
– Fed: markets are expecting the beginning of tapering for the end of the year
– ECB: interest rates will remain low for a long time. Draghi adopts a new way of communication
(pre-commitment)
– Emerging markets: monetary policies still supportive, even if some central banks adotped
restrictive measures to defend currencies
– Japan: first positive results for Abeconomics
124
2 - Equity Valutations
1. European equities still undervalued
2. At these levels the market discounts a progressive and gradual exit from the
recession
3. Valuations are not an issue nor a driver for the markets. The ratings could become
an important element for the continuation of the rebound only if the fundamentals
continue to improve
125
2 – Parameters’ estimation for portfolio construction
Annualized Volatility
Annualized Returns
Cash
Inflation
linked
Govt
Bond
AAA
Govt
Periph.
Euro
Corporate
Corporate Corporate Em erging
IG Short
IG Global High Yield
Debt
term Euro
0,1%
0,7%
5,6%
1,5%
5,1%
3,3%
1,5%
3,7%
1,4%
3,4%
4,2%
4,8%
6,6%
9,9%
7,3%
3,8%
12,9%
18,3%
18,2%
0,9%
14,0%
-11,6%
Cash
Inflation
linked
Govt Bond
AAA
Govt
Periph.
Euro
Corporate
IG Short
term Euro
Corporate
IG Global
Corporate
High Yield
Emerging
Debt
Global
Equity
Emerging
Equity
Commodities
15,7%
100,0%
7,5%
71,3%
100,0%
29,9%
18,4%
24,2%
100,0%
17,3%
31,8%
46,4%
37,3%
100,0%
20,0%
58,1%
53,6%
24,5%
74,4%
100,0%
10,5%
4,9%
6,0%
27,4%
59,8%
60,4%
100,0%
17,4%
28,2%
19,3%
20,3%
60,4%
77,5%
60,5%
100,0%
5,9%
-13,3%
-3,4%
14,2%
36,0%
25,8%
45,2%
46,9%
100,0%
7,6%
-3,0%
4,7%
11,9%
45,6%
40,5%
44,5%
58,5%
76,2%
100,0%
Global
Equity
Em erging
Com m odities
Equity
Corretlation Matrix
Cash 100,0%
Inflation linked
Govt Bond AAA
Govt Periph. Euro
Corporate IG Short term Euro
Corporate IG Global
Corporate High Yield
Emerging Debt
Global Equity
Emerging Equity
Commodities
Historical data of the last 2 years (weekly basis)
126
-7,1%
-8,2%
-17,0%
-4,7%
28,6%
25,7%
39,3%
48,5%
40,4%
47,7%
100,0%
Optimal Portfolio: Example High Risk
Asset Class
Cash
Cash
Govt Periph. 6/12 m
Governement Bond "core"
Govt Bond AAA
Inflation Linked
Corporate IG
Corporate IG ST Euro
Corporate IG Global
Risky Assets
Corporate HY
Emerging Debt
Developed Equity
Emerging Equity
Commodities
TOT
Vol max
Risk Budget
Duration
YTM
127
Weight
Risk
Contribution
Normalized
Risk
Contribution
33%
0,1%
3%
8%
25%
0,0%
0,1%
0%
3%
0%
0,0%
0%
0%
0%
0,0%
0,0%
0%
0%
25%
0,4%
9%
15%
10%
0,1%
0,2%
3%
6%
42%
3,6%
88%
10%
8%
19%
1%
4%
0,5%
0,5%
2,2%
0,2%
0,3%
11%
12%
53%
4%
8%
100%
4%
10%
40%
2,8
2,5%
INPUT:
1. Statistics: 104 data on a
weekly basis
2. Profile: High Risk
3. Max volatility: 10%
4. Risk Budget: 40%
5. Duration: max 5 years
Tactical Asset Allocation
 Equity: 130% - Overweight, neutral bias
 We had a BUY signal at the beginning of the month. With the change of the strategic
weight, it also changes the signal of the relative weight
Equity
Strategic Weight
Last Committee
New Strategic
Weight
Signal as regards to
new strategic weight
17,0%
20,0%
130%
Notes:
 Theorical exposure of assets can range from 0% until 200% of the strategic weight
 Weight of 100%: theorical exposure = strategic weight
128
Tactical Asset Allocation: CPPI
High Risk
Equity
Commodities
129
Theor.
Weight
26,70%
1,46%
Ptf
Weight
20,12%
1,38%
Delta
-6,58%
-0,08%
Strategic Portfolio: security selection
Asset Class
Cash
Government Bond
CCT-eu 15/12/2015
Corporate IG
SANTANDER EURO CREDIT
HENDERSON H. EURO CORPORATE BOND "I2"
PIMCO GLOBAL IG
M&G European Corporate Bond
Risky assets
130
Emerging Debt
MFS Emerging Markets Debt Fund
Corporate HY
GS GLOBAL HIGH YIELD PORTFOLIO "I" (EURHDG)
Equity
Global
JPM GLOBAL FOCUS "B"
MFS MERIDIAN GLOBAL EQUITY "I1" (EUR)
Eurozone
BGF-EURO MKTS FUN-D2
USA Hedged
THREADNEEDLE AMER SEL "2" INA (EURHDG)
Emerging
ROBECO EMERGING MARKETS EQ "I" (EUR)
Commodities
VONTOBEL BELVISTA COMMODITY "HI" (EURHDG)
TOT
Weights
16,2%
10,0%
10,0%
30,4%
10,0%
3,5%
8,4%
8,5%
43,4%
7,5%
7,5%
8,0%
8,0%
26,5%
13,9%
6,8%
7,1%
7,0%
7,0%
4,3%
4,3%
1,3%
1,3%
1,5%
1,5%
100,0%
Performance attribution
Rainbow 10
Month to date
Update Date 09-13-2013
AA = Asset Allocation
Start Date 12-31-08
SP = Selection
Asset Class
Cash
Quarter to date
TOT
1,02%
AA
SP
1,16%
-0,14%
Year to date
TOT
2,06%
AA
SP
1,80%
0,26%
TOT
0,73%
AA
SP
0,56%
0,17%
Weights
Perf
Contribution
AA
SP
Perf
Contribution
AA
SP
Perf
Contribution
AA
SP
18,09%
0,00%
0,00%
0,00%
0,00%
0,02%
0,04%
0,00%
0,04%
0,06%
0,11%
0,01%
0,10%
0,00%
0,00%
0,00%
0,32%
0,54%
0,02%
0,03%
0,00%
0,00%
0,00%
0,00%
0,02%
0,02%
1,45%
2,27%
0,04%
0,02%
0,00%
0,00%
0,00%
0,00%
0,04%
0,02%
Liquidità
BTP 3,00% 010414
SPAGNA 4,75% 300714
6,62%
6,85%
4,63%
0,02%
0,02%
0,00%
0,00%
0,00%
0,00%
0,00%
Government Bond
11,91%
0,01%
-0,01%
0,00%
-0,01%
0,41%
0,10%
0,04%
0,06%
0,97%
-0,12%
-0,14%
0,02%
4,98%
6,93%
0,06%
-0,22%
0,01%
-0,01%
0,00%
0,00%
0,00%
-0,01%
0,65%
0,85%
0,01%
0,09%
0,00%
0,04%
0,00%
0,05%
0,98%
2,63%
0,01%
0,11%
0,00%
0,05%
0,00%
0,05%
25,91%
-0,10%
-0,08%
-0,04%
-0,05%
0,37%
0,10%
0,11%
-0,01%
0,52%
-0,19%
0,08%
-0,27%
9,92%
3,50%
5,50%
7,00%
-0,01%
-0,11%
-0,26%
-0,66%
0,00%
0,00%
-0,02%
-0,06%
0,01%
-0,01%
-0,02%
-0,02%
-0,01%
0,00%
0,00%
-0,04%
0,33%
0,83%
-0,51%
0,94%
0,03%
0,03%
-0,04%
0,08%
0,06%
0,01%
0,02%
0,02%
-0,02%
0,02%
-0,06%
0,06%
1,11%
0,66%
-3,16%
1,33%
0,11%
-0,04%
-0,32%
0,06%
0,14%
-0,05%
-0,01%
0,00%
-0,03%
0,01%
-0,30%
0,05%
44,08%
2,79%
1,11%
1,19%
-0,09%
4,38%
1,80%
1,63%
0,16%
6,69%
0,96%
0,62%
0,33%
0,92%
0,49%
0,71%
0,40%
4,11%
3,67%
4,28%
3,35%
5,16%
3,75%
3,35%
4,09%
5,69%
6,29%
-1,38%
-0,80%
0,04%
0,04%
0,03%
0,03%
1,05%
0,53%
0,29%
0,24%
0,26%
0,26%
0,18%
0,18%
0,08%
0,08%
-0,01%
-0,01%
0,07%
0,07%
0,06%
0,06%
1,09%
0,51%
0,25%
0,26%
0,36%
0,36%
0,14%
0,14%
0,07%
0,07%
-0,02%
-0,02%
-0,03%
-0,03%
-0,02%
-0,02%
-0,04%
0,02%
0,04%
-0,02%
-0,10%
-0,10%
0,03%
0,03%
0,01%
0,01%
0,01%
0,01%
-0,85%
-1,45%
2,35%
1,84%
6,50%
5,26%
8,13%
4,85%
10,53%
10,21%
4,91%
7,51%
3,25%
5,27%
2,41%
3,56%
-0,09%
-0,09%
0,14%
0,14%
1,69%
0,76%
0,54%
0,23%
0,54%
0,54%
0,31%
0,31%
0,07%
0,07%
0,05%
0,05%
-0,05%
-0,05%
0,18%
0,18%
1,46%
0,62%
0,35%
0,27%
0,59%
0,59%
0,21%
0,21%
0,05%
0,05%
0,03%
0,03%
-0,04%
-0,04%
-0,04%
-0,04%
0,23%
0,14%
0,18%
-0,04%
-0,04%
-0,04%
0,11%
0,11%
0,02%
0,02%
0,01%
0,01%
-9,00%
-8,70%
2,90%
3,46%
12,70%
13,71%
15,09%
16,36%
11,21%
16,98%
17,97%
19,95%
-7,19%
-6,26%
-5,67%
-8,49%
-0,90%
-0,82%
0,25%
0,25%
1,75%
0,88%
0,37%
0,17%
0,73%
0,73%
0,64%
0,64%
-0,56%
-0,56%
-0,15%
-0,15%
-0,98%
-0,87%
0,22%
0,22%
1,48%
0,76%
0,32%
0,14%
0,52%
0,52%
0,59%
0,59%
-0,54%
-0,54%
-0,10%
-0,10%
0,08%
0,06%
0,04%
0,04%
0,27%
0,12%
0,05%
0,03%
0,21%
0,21%
0,05%
0,05%
-0,03%
-0,03%
-0,06%
-0,06%
BGF Euro Short Duration Bond Fund
CCT-eu 15/12/2015
Corporate IG
SANTANDER EURO CREDIT
HENDERSON H. EURO CORPORATE BOND "I2"
PIMCO GLOBAL IG
M&G European Corporate Bond
Risky assets
Emerging Debt
MFS Emerging Markets Debt Fund
Corporate HY
GS GLOBAL HIGH YIELD PORTFOLIO "I" (EURHDG)
Equity
Global
JPM GLOBAL FOCUS "B"
MFS MERIDIAN GLOBAL EQUITY "I1" (EUR)
Eurozone
BGF-EURO MKTS FUN-D2
USA Hedged
THREADNEEDLE AMER SEL "2" INA (EURHDG)
Emerging
ROBECO EMERGING MARKETS EQ "I" (EUR)
Commodities
VONTOBEL BELVISTA COMMODITY "HI" (EURHDG)
TOT
131
7,41%
7,41%
7,94%
7,94%
27,31%
14,24%
7,03%
7,21%
7,24%
7,24%
4,46%
4,46%
1,37%
1,37%
1,42%
1,42%
100,00%