khrishnamoorthysooben fixed income...
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Fitting linkers into a portfolio
Khrishnamoorthy SOOBEN
Fixed Income Strategist
+44 (0)20 7676 7713
1
Contents
� Efficient frontier analysis
� Using historical data
� Forward looking approach: bet on expected return, volatility and
correlation
� Finding value in linkers – common strategies
� Linkers vs nominal bonds
2
Historical return and risk
Source: Calculations from SG Fixed Income & Forex Research
� Definitions:
� Nominal bonds and linkers data are computed from total return Barclays Capital Euro Indices (France). Money market returns are based on 1 month Euribor rates. Finally, equity returns are derived from a total return MSCI Equity index for France. Data are from 1999.
� Return: annualised average monthly total return
� Risk: annualised standard deviation of monthly total returns
Money Market Nominal bonds Linkers Equities
Historical Return 3.1% 4.3% 5.6% 9.3%
Historical Risk 0.3% 3.3% 4.2% 17.6%
Correlations Money Market Nominal bonds Linkers Equities
Money Market 1 0.12 0.03 -0.24
Nominal bonds 0.12 1 0.77 -0.35
Linkers 0.03 0.77 1 -0.28
Equities -0.24 -0.35 -0.28 1
3
Ex-post efficient frontier
� We minimise the portfolio risk for a
given return, using historical
returns, risks and correlation.
Efficient frontier derived from
historical performance
Source: SG Fixed Income & Forex Research
Efficient Frontier
3%
4%
5%
6%
7%
8%
9%
10%
0% 3% 6% 9% 12% 15% 18%Risk
Portfolio Return
4
Ex-post portfolio components
� What does 1999 - 2007 history tell us, based on our chosen assets and indices?
� Nominal bonds may not offer the worst return
AND risk, but positive correlation with other
asset classes implies a 0% weight throughout
� Optimal weight of equity increases steadily for
higher risk and return portfolios, thanks to high
historical return and sufficiently positive
correlation vs other assets
� Except for very low return levels, ex-post
portfolios are essentially made up of linkers
and equity
� Conclusion: Historical analysis is, by definition, backward looking => useful but potentially irrelevant. A forward looking approach is more appropriate.
Portfolio components derived from
historical performance
Source: SG Fixed Income & Forex Research
Portfolio Components
0%
20%
40%
60%
80%
100%
0% 3% 6% 9% 12% 15% 18%
Risk
Weights
Money Market Nominal BondsLinkers Equities
5
Anticipating returns, risks and correlations
Source: SG Fixed Income & Forex Research
� This set of return, risk and correlation is based on a combined historical and theoretical analysis.
� Assumption 1: Equities show negative correlation vs. nominal bonds (-0.1%) and linkers (-0.3%)
� Assumption 2: Equities show positive correlation vs. nominal bonds (+0.1%) and linkers (+0.3%)
Money Market Nominal bonds Linkers Equities
Expected Return 3.5% 4.8% 4.5% 7.5%
Expected Risk 0.5% 7.0% 5.0% 18.0%
Expected Correlations Money Market Nominal bonds Linkers Equities
Money Market 1 0.15 0.05 -0.15
Nominal bonds 0.15 1 0.55 -0.1/+0.1 Correlation
Linkers 0.05 0.55 1 -0.3/+0.3 assumptions
Equities -0.15 -0.1/+0.1 -0.3/+0.3 1
6
Correlation assumptions are crucial
� We now minimise risk for a given
level of return, using expected
return, risk and correlation under
two different assumptions.
� The grey frontier is built assuming negative
correlation between stocks on the one hand,
nominal bonds and inflation-linked bonds
(ILBs) on the other.
� The red frontier is built assuming positive
correlation.
� As expected the grey frontier is the highest,
since the negative correlation increases the
diversification potential.
Efficient frontiers under different
correlation assumptions
Source: SG Fixed Income & Forex Research
3%
4%
5%
6%
7%
8%
0% 5% 10% 15% 20%
-ve Corr Equities vs Linkers & Nominal Bonds
+ve Corr Equities vs Linkers & Nominal Bonds
Expected Return
Risk
7
Moving the efficient frontier - Assumption 1
� We work under assumption 1:
� negative correlation between stocks on the
one hand, nominal bonds and inflation-linked
bonds (ILBs) on the other.
� ILBs exhibiting higher de-correlation to stocks
than nominal bonds to stocks.
� Adding ILBs to the portfolio moves the
efficient frontier up, except for extreme risk
levels.
� Under that set of risk/return assumptions, ILBs
win a very large weighting in the portfolio.
Linkers provide diversification benefits
under assumption 1
Source: SG Fixed Income & Forex Research
3%
4%
5%
6%
7%
8%
0% 5% 10% 15% 20%
Linkers included Linkers excluded
Expected Return
Risk
8
Portfolio weights – Assumption 1
� The first set of assumption delivers a very high
weighting to ILBs for portfolio return volatility
around 5%.
� Such weighting may be difficult to achieve on big
portfolios because of the relatively small size of
the ILB market.
� One would need to run optimization under an
additional constraint in that case (capping the
weighting of ILBs).
Linkers win a significant share of the
portfolio under assumption 1
Source: SG Fixed Income & Forex Research
Portfolio Components
0%
20%
40%
60%
80%
100%
0% 5% 10% 15% 20%
Risk
Weights
Money Market Nominal BondsLinkers Equities
9
Moving the efficient frontier - Assumption 2
� We work under assumption 2:
� positive correlation between stocks on the one
hand, nominal bonds and inflation-linked
bonds (ILBs) on the other.
� ILBs exhibiting higher correlation to stocks
than nominal bonds to stocks.
� Adding ILBs to the portfolio hardly moves the
efficient frontier. Yet ILBs win a significant
weighting in portfolios showing a limited risk.
That weight peaks at 31%.
Negligible diversification benefit from
linkers under assumption 2
Source: SG Fixed Income & Forex Research
3%
4%
5%
6%
7%
8%
0% 5% 10% 15% 20%
Linkers included Linkers excluded
Expected Return
Risk
10
Portfolio weights - Assumption 2
� Although ILBs do not greatly
improve the risk/return outlook
under that set of assumptions,
they still win a significant
weighting.
Linkers still win a significant share of the
portfolio under assumption 2
Source: SG Fixed Income & Forex Research
Portfolio Components
0%
20%
40%
60%
80%
100%
0% 5% 10% 15% 20%
Risk
Weights
Money Market Nominal BondsLinkers Equities
11
Stocks vs. bonds and ILBs (1)
� We call Rs, Ri and Rr the nominal total return of stocks, bonds and ILBs (real bonds). The above results partially depend on where you fix ϕϕϕϕ(Rs, Ri) relatively to ϕϕϕϕ(Rs, Rr).
� ϕ(Rs, Ri) = Cov (Rs, Ri) / (σRs * σRi)
� ϕ(Rs, Rr) = Cov (Rs, Rr) / (σRs * σRr)
� Cov (Rs,i) = Cov (Rs, r+BEIR) = Cov (Rs, r) + Cov (Rs, BEIR)
� Assuming Cov (Rs, BEIR) < 0, then Cov (Rs,i) < Cov (Rs, r).
� As in most cases σi > σr then ϕ(Rs, i) < ϕ(Rs, r)
� This also means ϕϕϕϕ(Rs, Ri) > ϕϕϕϕ(Rs, Rr)
� In other words, if stock returns are negatively correlated to inflation expectations, then ILBs show a smaller positive correlation or larger negative correlation to stocks than nominal bonds do. And that is good news (ILBs add to diversification).
• Eg: ϕ(Rs, Ri) = 0.25, ϕ(Rs, Rr) = 0.15 or ϕ(Rs, Ri) = -0.15, ϕ(Rs, Rr) = -0.25
12
Stocks vs. bonds and ILBs (2)
� The result above is intuitive. If both stocks and nominal bonds react badly to increasing inflation expectations (or to a risinginflation risk premium), then that will tend to increase their correlation - ILBs will increase diversification.
� However, it is not clear whether stocks will be negatively correlated to inflation.
� Correlation has been negative in the last twenty years, but not in the
last seven years.
� There is no definite theoretical answer either. The falling inflation
trends have generally been good news to the economy and equities
in the last 20 years. Yet an excessive fall in inflation, potentially
leading to deflation, would clearly be bad news for stocks -
correlation between inflation and stock market returns would
become positive in that case.
13
Stocks vs. bonds and ILBs (3)
� Deciding ex-ante for the nominal and relative levels of ϕϕϕϕ(Rs, Ri) and
ϕϕϕϕ(Rs, Rr) is one difficult task. In the above calculations, we used
� one friendly example ( ϕ(Rs, Ri) > ϕ(Rs, Rr) )� ILBs clearly add
diversification to the portfolio
� and one unfriendly example � ILBs still gain a significant weighting for
limited amount of risks.
� NB1: Deciding for ex-ante correlation is an important task, but no more than
deciding for ex-ante returns and volatility. Assessing relative valuation of
stocks and bonds is a key step.
� NB2: We run calculations in the nominal world. Yet it makes sense,
especially for pension funds, to work in the real world. Doing so would
generally increase the volatility of money market instruments relatively to
volatility of ILBs, and increase the weighting of ILBs for low levels of
portfolio risk.
Finding value in linkers
Common strategies and technical
considerations
15
Common linker strategies
� Outright positions in linkers: going long or short an inflation
linked bond => position in real yield space
� Breakeven positions: going long or short an inflation linked
bond against a nominal bond => position in inflation space
� Strategies in real yield and breakeven space can be put on as
curve trades (e.g steepening or flattening, butterfly etc…),
cross market trades (e.g French vs European inflation).
16
Strategies in real yield space
� Outright positions in linkers, i.e., in real yield space usually express a view on both nominal yields AND inflation breakevens
� Consider an investor who has a bullish view on 5-year yields (i.e. 5-year yields expected to fall). The classic position to be built from this view would be to go long a 5-year nominal bond. Now consider three possibilities:
� The investor does not have a view on 5-year inflation breakevens. Then going long the 5-year nominal
bond would be the best strategy.
� The investor believes that 5-year inflation breakevens are too low and will increase. In this case, going
long a 5-year linker is a more attractive alternative to the classic position. A long position in the linker
actually allows the investor to position for BOTH his view on nominal yields and inflation
breakevens. NB: Carry/forward levels should be precisely taken into consideration in real yield
strategies (refer to slides on carry)
� The investor believes that 5-year inflation breakevens are too high and will fall. The investor would then
go long the nominal bond or consider a position in breakeven space (next section).
� Strategies in real yields may suit specific needs too. For example, an outright long position on a linker in real yield space may suit the hedging needs of a pension fund, irrespective of its view on yields or inflation breakevens.
17
Strategies in breakeven space
� An inflation breakeven strategy involves trading linkers against nominal bonds. The breakeven inflation rate (BEIR) is defined as the difference between the nominal yield and the real yield.
� Bets in breakeven space can be of two types:
� For “buy and hold” investors, the relative performance between nominal bonds and ILBs
will depend on actual average inflation throughout the remaining life of the bond relatively
to BEIR at time of purchase.
� Trading breakevens over a shorter period implies a view on the dynamics of the BEIR
(forwards should be taken into account). Future actual inflation will drive the relative
performances of the nominal bond and linker.
� Views on the dynamics of the BEIR are usually related to views on future inflation and inflation expectations. Other factors may intervene: impact from other markets (e.g. commodities markets), changes in regulations (e.g. taxes), bond supply etc…
18
Carry on linkers
Source: SG Fixed Income & Forex Research
� Carry is a key technical aspect in linker strategies
Real yield BEIR1Mth Carry
ILB3Mth Carry ILB
6Mth Carry
ILB1Mth Fwd BEIR 3Mth Fwd BEIR 6Mth Fwd BEIR
OATei 3% Jul 2012 2.088 221.0 11.73 13.48 4.90 209.85 208.43 216.79
OATei 1.6% Jul 2015 2.132 219.1 7.35 8.41 3.19 212.13 211.32 216.48
OATei 2.25% Jul 2020 2.200 221.1 4.97 5.74 2.43 216.54 216.05 219.49
OATei 3.15% jul 2032 2.191 230.7 3.11 3.57 1.48 227.86 227.74 230.12
OATei 1.8% jul 2040 2.155 233.6 2.28 2.58 1.00 231.58 231.54 233.36
BTANei 1.25% Jul 2010 2.037 224.4 18.09 20.88 6.79 207.28 204.94 218.54
OATi 3% Jul 2009 2.196 208.1 18.47 23.01 11.26 190.99 187.13 198.16
OATi 1.6% Jul 2011 2.260 202.9 9.57 11.70 6.04 194.11 192.36 197.70
OATi 2.5% Jul 2013 2.252 205.3 6.68 8.02 3.96 199.15 198.10 202.02
OATi 1% Jul 2017 2.289 206.3 3.97 4.76 2.43 202.70 202.18 204.56
OATi 3.4% Jul 2029 2.258 223.6 2.34 2.76 1.35 221.64 221.54 223.24
BUNDei 1.5% Apri l 2016 2.198 210.1 6.75 7.84 3.24 203.71 202.83 207.33
BTPei 1.65% Sep 2008 2.006 229.3 44.60 55.48 19.34 186.79 177.10 213.12
BTPei 0.95% Sep 2010 2.139 221.4 17.38 20.44 8.01 205.02 202.62 215.15
BTPei 1.85% Sep 2012 2.205 216.6 11.22 13.15 5.60 206.29 205.10 212.76
BTPei 2.15% Sep 2014 2.231 217.6 8.38 9.79 4.27 209.89 209.06 214.79
BTPei 2.1% Sep 2017 2.325 219.2 6.20 7.36 3.60 213.65 213.17 217.44
BTPei 2.35% Sep 2035 2.460 232.8 2.83 3.42 1.91 230.48 230.53 232.76
GGBei 2.9% Jul 2025 2.414 224.3 4.11 4.96 2.70 220.75 220.62 223.69
GGBei 2.3% Jul 2030 2.466 232.3 3.30 4.02 2.29 229.46 229.33 231.77
19
Inflation seasonality
Source: SG Quantitative Research and Fixed Income & Forex Research
� An accurate estimation of the seasonality of a linker’s underlying inflation index is key for inflation carry estimations
0.994
0.9965
0.999
1.0015
1.004
D J F M A M J J A S O N D- 0 .4%
- 0 .2%
0 .0%
0 .2%
0 .4%
J F M A M J J A S O N D
Deme tr a Dumm ie s
MoM a d ju s tme n ts
Average seasonality adjustments for
HICP for the 96-06 periodEMU inflation seasonality coefficient
multiplier
20
Carry and P&L
Source: SG Fixed Income & Forex Research
1M P&L of long OATi 2009 BEIR trade
when 1M carry is positive
1M P&L of short OATi 2009 BEIR trade
when 1M carry is negative
-30
-20
-10
0
10
20
30
Mar-02 Mar-03 Mar-04 Mar-05 Mar-06 Mar-07
Gain
Loss
bp
-30
-20
-10
0
10
20
30
Mar-02 Mar-03 Mar-04 Mar-05 Mar-06 Mar-07
Gain
Loss
bp
21
ILB market increasingly efficient
� It is remarkable that the P&L of long
BEIR positions (trade locked for 1
month in our case) has declined
steadily over the past few years.
� This suggests that the market is now
efficient in pre-adjusting to carry
conditions. Making systematic profits
from carry is no longer possible –
unless you get a superior CPI
forecasting model.
3-month standard deviation of P&L on
long BEIR OATi 2009 trade
Source: SG Fixed Income & Forex Research
0
4
8
12
16
May-02 May-03 May-04 May-05 May-06
Linkers vs Nominal bonds
Relative volatility and correlation
The inflation risk premium
23
Fisher – linking nominal and real rates
� The fundamental equation assessing the link between nominal
rates and real rates has been postulated be the American
economist Irving Fisher (1867-1947):
(1+Nominal rate)=(1+ Break-even inflation rate)*(1+real rate)
Nominal rate = real rate + break-even inflation rate + (break-even inflation rate * real rate)
Neglecting 2nd order terms, we get: Nominal rate = real rate + break-even inflation rate
Nominal rate = real rate + expected inflation + risk premium
� The break-even inflation rate (BEIR) is made of expected
inflation and a risk premium covering inflation forecast
uncertainties and the difference in the liquidity of the nominal
and the inflation bond
24
Fisher – what it means for volatility
� i = r + e + p
� with i nominal bond yield
� r real bond yield
� e inflation expectation
� p inflation risk premium
� i = r + BEIR
� with Break-Even Inflation Rate BEIR = e + p
� Var (i) = Var (r) + Var (BEIR) + 2 * Cov (r,BEIR)
� Var(i) > Var(r) unless Cov (r, BEIR) < - 0.5 * Var (BEIR)
i.e. unless Correl (r, BEIR) < -0.5 * STDV (BEIR) / STDV (r)
� Unless real yields and inflation expectation + premium exhibit a large negative correlation, nominal yields will be more volatile than real bond yields.
25
Real and nominal yield volatility
Source: SG Fixed Income & Forex Research
30
50
70
90
110
Sep-02 Mar-04 Sep-05 Mar-07
26-wk STDEV real yield OATei 201226-wk STDEV nominal yield OAT 2012
bp
30
45
60
75
90
May-03 May-04 May-05 May-06 May-07
26-wk STDEV real yield OATei 203226-wk STDEV nominal yield OAT 2032
bp
Real and nominal yield volatilities are currently very low and close
� We look at annualised volatility of nominal and real bond yields
26
Yield volatility vs Price volatility
Source: SG Fixed Income & Forex Research
� When deciding for volatility through the asset allocation process, we need to look at (annualised) volatility of total returns instead of yield volatility.
� Importantly, the clean (full) invoice price of an ILB is obtained by multiplying the clean (full) price by an index ratio. One could be concerned that this index adds to the volatility of an ILB. Actually it does not -as the left-hand chart shows. That is because the clean price and the index ratio are negatively correlated (due to immediate price reaction to CPI release and lag in price indexation).
0
20
40
60
80
100
120
Sep-00 Nov-02 Jan-05 Mar-07
26-wk STDEV real yield OATi 200926-wk STDEV nominal yield OAT 2009
bp
0
1
2
3
4
5
6
00 01 02 03 04 05 06 07
Vol. of Clean Price OATi 09
Vol. of (Clean P * Index Ratio) OATi 09
Vol. of Clean Price OAT Apr 09
Rolling 12Mth volatility, %
27
Yield beta (sensitivity)
� Above we discussed correlation
between real yields and BEIR - key to
relative volatility between nominal and
real bond yields.
� ϕ(r, BEIR) = Cov (r,BEIR) / (σr * σBEIR)
� Now we look at the yield beta, which
tells us about the sensitivity of real bond
yields to nominal bond yields.
� β = Cov (i,r) / Var (i)
� We calculate yield beta by regressing
changes in real yields vs. changes in nominal
yields.
� NB: When deciding for correlation through
the asset allocation process, we use
correlation between total returns, not
yields.
1-month beta (daily data) between real
and nominal yields
Source: SG Fixed Income & Forex Research
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
2005 2006 2007
BTPei 2010 OATei 2015 OATei 2032
28
The role of beta
� Guessing the beta is key because:
� Correlation between nominal bonds and ILBs is instrumental in the asset
allocation process; beta and correlation are closely related: ϕ(i, r) = β (i,
r) * σi / σr
� The beta will decide of the duration of the ILB sub-portfolio
� Effective duration of ILB = Modified duration of ILB * yield beta
� Which duration should you attach to ILBs, i.e. what beta to choose?
Looking at historicals can be a useful starting point. However, betas
may be unstable. Ideally, the choice of beta should reflect the
investors’ expectations about the relative moves in nominal and
real yields within the expected market context.
29
Relative performance
� Under- or out-performance of ILBs relatively to nominal bonds is
often discussed in terms of Break-even Inflation rates (BEIR). This
is misleading. If one attaches a 0.5 beta to an inflation-linked bond
in one’s portfolio, one should expect that BEIR widen in a bear
market, and narrow in a bull market. If one assumes that long-term
yield beta is 0.5, then:
� ILB out-performance:
� beta > 0.5 in a bull bond market
� beta < 0.5 in a bear bond market
� ILB under-performance
� beta < 0.5 in a bull bond market
� beta > 0.5 in a bear bond market
30
Directionality of betas (1)
Source: SG Fixed Income & Forex Research
0
1
2
3
4
Sep-00 Apr-02 Nov-03 Jun-05 Jan-07
0.2
0.4
0.6
0.8
1
Yield of OATi 2009
26-week yield beta
%
1.3
1.6
1.9
2.2
2.5
2.8
May-03 May-04 May-05 May-06 May-07
0.5
0.7
0.9
1.1
1.3
1.5
Yield of OATei 2032
26-week yield beta
%
� Are betas directional? The answer is not simple!
31
Directionality of betas (2)
� Short history suggests that betas tend to be higher when bond yields fall. Our view is actually that betas will tend to be high when nominal bonds yields move towards extreme levels (low or high).
� Low yields: Following Fisher, a decline in nominal bond yields comes from either falling real bond yields or falling BEIR. If one assumes yield beta constant at 0.5, BEIR fall as much as real bond yields through that process. Yet BEIR tend to quickly meet support, which pushes betas up:
• “Sticky” inflation in Eurozone - ECB has generally struggled to keep inflation below 2% since 1999.
• In the US, when the Fed cut rates to record lows to erase the deflation risk, this has prevented a dramatic fall in BEIR.
� High yields: Inversely, if nominal bond yields rise due to a positive shock on final demand, the central bank makes it clear it will fight inflation - that tends to cap BEIR, which pushes yield betas up.
32
The inflation risk premium
� In the long run, assuming inflation expectations are correctly priced
in the market, ILBs are expected to under-perform nominal bonds.
That is because ILBs protect the investor against the inflation risk.
Nominal bonds pay an inflation risk premium.
� Inflation risk premium: excess expected real yield of a nominal
bond over an equivalent inflation-linked bond.
� Inflation risk premium: expected saving on interest payments
realized by issuing an inflation-indexed bond rather than a nominal
bond.
� This relation is unbiased if the inflation expectations priced in
nominal bonds are rational.
33
Portfolio investment and the inflation risk
� Consider the position of an investor in 10-year Treasuries carrying
a nominal yield of 5%. Assume that the investor’s inflation
expectation for the coming decade is 2% per year, and therefore
that the expected annual real yield is 3%. Consider two situations
(we assume that the inflation rate has a normal distribution)
� E.g 1 - standard deviation of inflation is 3% .There is a 16%
probability that the inflation rate is above 5% (2% + 1 standard
deviation), and therefore that the real return actually obtained
from the bond is negative.
� E.g 2 - standard deviation of inflation is 1% . The probability
falls to just 0.1%. In other words, the division of the standard
deviation by three divides the probability of a negative real return
by 117.5.
� This difference in risk has to be incorporated in the bond’s price.
34
What is driving the inflation premium?
� Since we cannot precisely extract inflation expectations from
market data, it is difficult to assess the value of the inflation risk
premium.
� Intuitive thoughts about the inflation risk premium:
� The premium is growing with inflation volatility. Gain in central
bank credibility over the last twenty years has cut the premium.
� The premium is growing with the needs for inflation protection.
As the baby-boomers get ready for retirement, the increased
demand for inflation protection may cause an increase of the
premium.
�Of course, shocks on relative supply/demand on ILBs
relatively to nominal bonds will affect the premium, too.
35
Measuring the premium (1)
� A recent ECB article, “Inflation risk premia in the term structure of
interest rates” by Peter Hördahl and Oreste Tristani, offers a review of
recent research on the inflation premium, and makes its own estimate.
� The State of the Art shows dramatically different results, depending on
the model specifications.
� Their own study, focusing on the 10-year maturity, concludes that “on
average, the inflation risk premium on euro area nominal yields was
insignificantly different from zero over the EMU sample. Nevertheless,
fluctuations around the average have been relatively small, but
statistically significant, in the 2004-2006 period.” However, “fluctuations
in the raw break-even rate have mostly reflected variations in the
inflation risk premium: adjusting for such premium, long-term inflation
expectations appear to have remained well-anchored in the euro area
from 1999 to date.” They show, in particular, that the premium tends to
grow when short term rates are low and/or the output gap rises.
36
Measuring the premium (2)
� The models unfortunately have their shortcomings.
� Those based on historical nominal and real yield series suffer from the
relatively short history of the inflation-linked market. UK series are
longer, but this market has been heavily distorted by supply and demand
considerations.
� Models using inflation-linked bonds’ price or yields fail to properly
measure the liquidity premium, especially for older data.
� Results are often dependant on the assumptions and specifications of
the models. Hördahl and Tristani themselves use output gap data in the
macro specification of the model, that are not broadly used or even
known by market participants.
� History will tell (maybe). In the long run, comparing the return (or cost) of investing (or issuing) in inflation-linked bonds to that of nominal bonds will help to measure the value of the inflation premium, but even there the results will be dependant on the assumption that inflation expectations priced in nominal bonds are rational.
37
Conclusion
� Linkers add to global portfolio diversification. The diversification
potential increases when stock returns are negatively correlated to
inflation expectations.
� The key decision in the asset allocation process is to decide about
� expected return EXPECTED PERFORMANCE
� volatility (relative valuation)
� CORRELATION
� Carry is key in linker strategies. Always look at linkers on a forward
basis.
� The relation between nominal linkers and linkers is not stable. When
assessing beta and correlations, historicals should only be the
starting point.