“It`s the economy, stupid!”

Active Management
“It’s the
economy,
stupid!”
2
“It’s the economy, stupid!”
Content
4 “It’s the economy, stupid!”
5 Understand
5 Act
6 Looking at the economy from a financial
market perspective: the “Macro for
Markets” approach
7 Analytical framework
7 Macro data flow vs asset returns:
global equities
9 Macro data flow vs asset returns:
global sovereign bonds
12 Signal quality of different indicators
13 Macro data flow, surprises and
consensus forecasts vs asset returns:
adding additional layers of economic
information pays off
14 Can we exploit any leading properties
of macroeconomic indicators for asset
allocation?
17 Technical note
18Appendix
Imprint
Allianz Global Investors GmbH
Bockenheimer Landstr. 42 – 44
60323 Frankfurt am Main
Global Capital Markets & Thematic Research
Hans-Jörg Naumer (hjn)
Ann-Katrin Petersen (akp)
Stefan Scheurer (st)
Data origin – if not otherwise noted:
Thomson Reuters Datastream
Allianz Global Investors
www.twitter.com / AllianzGI_VIEW
3
“It’s the economy, stupid!”
“It’s the economy, stupid!”
In which ways and to what extent are financial markets
affected by the economic news flow? This question remains
a hotly debated topic among both academics and market
participants. In the following research note, we apply our
proprietary “Macro for Markets” approach to shed some light
on the relationship between macroeconomic indicators and
asset returns in the United States, the Eurozone and globally.
Our study shows that active asset allocation based on macro
fundamental analysis can be a meaningful source of return for
investors and therefore a meaningful active management tool.
Martin Hochstein;
Senior Strategist, Global
Economics & Strategy
AllianzGI
“It’s the economy, stupid!” The reference to
Bill Clinton’s presidential campaign slogan in
1992 is a perfect summary for the findings of
our study. While there are other important
market drivers, such as valuation or the stance
of monetary policy, cyclical swings in asset
returns over the past 15 to 20 years can be
largely explained by the short-term flow of
economic data. This is good news for all topdown, fundamentally based active investment
approaches. If you do it right, macro number
crunching pays off!
But what is the right way to view financial
markets through macroeconomic eyes?
In order to avoid the behavioural pitfalls
of common fundamental investment
approaches, our analysis focuses on the
4
underlying directional trend of a wide range
of economic indicators as a starting point.
Combining the data trend with economic
surprises and changes in consensus growth
expectations increases the explanatory power
for asset returns even more.
It is the consensus perception of the current
economic environment, based on the macro
data flow and related surprises, that drives
financial markets – not our own forecasts for
growth and inflation! As a result, fundamental
asset allocators should focus on anticipating
the actual macro data trend instead of
wasting too much time with forecasting
medium-term gross domestic product (GDP)
and consumer price inflation (CPI) figures.
Description of indicators
Macro Breadth Index (MBI)
MBIs track the directional change of macro data on an aggregate level. By focusing on the direction (rather than the
magnitude) of change, the index enables the evaluation of the broadness of underlying growth and inflation trends and
is less prone to potential historical revisions of the embedded indicators over time. The monthly fluctuation of the MBIs
is scaled from –1 to +1, with a value of +1 (–1) implying an improvement (deterioration) in all macro indicators
included. The aggregate measure contains three sub-indices for activity (e. g. industrial production, retail sales,
unemployment rate), sentiment (e. g. consumer confidence, business confidence, leading indicators) and inflation
(e. g. CPI, unit labour costs) indicators. Regionally, MBIs for the world (based on 226 indicators), industrialized countries
(135) and emerging markets (80) are available. Furthermore, we calculate detailed country indices for the US (50),
the Eurozone (61), Japan (39) and the UK (38).
Economic Surprise Index (ESI)
Economic surprise indices track the high-frequency macro data flow relative to analysts’ expectations.
A rising (falling) index suggests that economic releases have been beating (trailing) economists’ average estimates.
As in the case of MBIs, we prefer equally weighted concepts such as the UBS surprise indices, which were used in the
subsequent analysis.
Consensus GDP forecasts & Global Consensus Breadth Index (CBI)
Consensus GDP forecasts track the average growth expectations of a large number of analysts for certain countries
or regions. The CBI measures the underlying directional trend of consensus GDP forecasts for 31 countries on an
aggregate level.
Understand
Act
Cyclical swings in macroeconomic data are
highly correlated with concurrent financial
market returns.
The most promising macro cyclical approach
for asset allocation is to anticipate the actual
data flow and look for potential vulnerabilities
of consensus expectations for short-term
economic indicators and medium-term GDP
growth.
Combining the data trend with economic
surprises and changes in consensus growth
expectations increases the explanatory power
for asset returns even more.
Broader-based concepts such as our Macro
Breadth Indices tend to dominate individual
economic indicators when explaining
equity and bond returns. It’s important to
capture the whole economic picture, not just
fragments!
Macro number crunching, if done smartly,
could be rewarded with superior active
returns and should therefore be seen as a
crucial contribution to active management.
5
“It’s the economy, stupid!”
Looking at the economy from a
financial market perspective: the
“Macro for Markets” approach
In this research note, we apply our proprietary
“Macro for Markets” framework to shed
some more light on the relationship between
macroeconomic indicators and asset returns
in the United States, the Eurozone and
globally. The approach is predicated on the
assumption that the consensus perception
of the current economic environment, based
on the actual macro data flow and related
surprises, can to some extent explain cyclical
swings in financial markets. We are fully
aware that there are other important drivers
of financial markets, such as valuation or
the stance of monetary policy, but those are
beyond the scope of this analysis.
In order to derive meaningful economic
signals for asset allocation, one has to avoid
common behavioural pitfalls, such as:
Framing: The right analysis set-up is key.
We try to keep the approach as plain and
straightforward as possible by using intuitive
indicators such as our “Macro Breadth Index”,
a robust measure of the underlying data trend
of an economy.
Analysis of paralysis: We process macro
data in a simple and uniform way to avoid
being overwhelmed by the sheer amount of
information available. Focus on directional
signals and aggregate indicators of economic
trends.
Anchoring: De-anchor the approach! Our
analysis confirms that financial markets are
mainly affected by directional changes, not
the level of macro indicators.
Representativeness: We avoid anecdotal
evidence by not relying on individual macro
indicators. Instead, we look at the aggregate
economic trend based on a broad range of
economic data. Be sure to capture the whole
picture, not just fragments.
While the broad underlying trend of
economic data is the single most important
cyclical macro factor for explaining asset
returns, adding economic surprises and
changes in consensus growth expectations to
the analysis increases the explanatory power
of the approach.
Chart 1: The “Macro for Market” approach
Macro data flow
Economic
scenario
Economic
surprises
Tools
1. Focus on broad
direction of
economic data
flow
2. Track data
releases vs
analysts‘
expectations
3. Track consensus
growth and
inflation
forecasts
4. Verify
consistency of
consensus GDP
forecasts
Macro Breadth
Indices
Economic Surprise
Indices
Consensus
Breadth Indices
Sentiment-Based
GDP Models
Source: Allianz Global Investors Global Economics & Strategy
6
Consensus
forecasts
Analytical framework
In our analysis of the relationship between
economic indicators and financial market
returns, we follow a three-stage process:
1.
nderlying data trend: In a first step, we
U
measure the impact of the current data
flow on asset returns as measured by
our “Macro Breadth Indices” (MBI). In
a nutshell, MBIs track the direction of a
large number of economic sentiment,
activity and inflation indicators to give
an aggregate view as to whether the
economic environment is improving or
deteriorating.
2.
ata trend and related surprises: In a
D
second step, we complement the data
trend analysis by adding economic
surprises. Obviously, economic data
that is improving and surprising on the
upside has a different effect on financial
markets than weaker macro data that is
still exceeding analysts’ expectations.
3.
Data
trend, surprises and consensus
growth forecasts: Finally, we combine
the data trend and related surprises
with medium-term consensus
expectations for GDP growth in
the respective economy. Although
consensus forecasts tend to lag behind
the actual macro data flow, they
embed additional explanatory power
for asset returns in certain cases. An
improvement in all three areas usually
constitutes a sweet spot for risky
assets and spells trouble for “riskless”
sovereign bonds.
Macro data flow vs asset returns:
global equities
In a first step, we analyse the coincident
relationship between the directional flow of
economic data and financial markets. We
therefore compare the three-month changes
of our Macro Breadth Indices with the
corresponding returns of several asset classes.
Please see disclosure
at the back of the paper
concerning back-tested
hypothetical performance.
1
Apart from the average return in different
macro regimes (improving or deteriorating
economic data), we calculate a hit ratio
(percentage of profitable signals) and an
information ratio (risk-adjusted excess return
vs passive investment in the respective
asset class) of a “perfect foresight” trading
strategy based on our MBIs. In this context,
“perfect foresight” assumes that we
correctly anticipate the signal of our MBI at
the beginning of each month.1 Returns are
calculated in USD hedged terms to avoid
unwanted distortions due to currency effects.
The strategy is rebalanced on a monthly basis
according to the respective macro signal,
which means long (short) risky assets vs cash
when the MBI increases (decreases).
For global equities, the results are quite
telling. Returns have been significantly above
(below) average in periods of a rising (falling)
Global Macro Breadth Index (see Chart 2).
Furthermore, equity markets responded
to the momentum in the data trend. The
stronger the increase (decrease) of the MBI,
the higher (lower) the corresponding returns
(see Chart 3). Obviously, global stock markets
have been significantly affected by cyclical
swings in the world economy. The findings
for global equities are confirmed by our
country analysis. Equity returns in the United
States and the Eurozone have been highly
correlated with their respective country MBIs
(see Appendix). However, long-term results
for the US also unveil that the relationship
has been strongest in times of pronounced
economic cyclicality. During the steady
“Goldilocks” episode of the mid- to late 1990s,
the macroeconomic impact on US equities
was rather subdued.
7
“It’s the economy, stupid!”
Chart 2: Global equity returns strongly affected by direction ...
Global Macro Breadth Index (growth)
average
0.77
increase
3.52
decrease
–2.27
–5
–4
–3
–2
–1
0
1
2
3
4
5
6
average 3-month return of global equities vs cash (in %)
Global Macro Breadth Index (growth)
Chart 3: ... and directional momentum of global macro data flow
average [185]
0.77
unchanged [0]
0
increase (faster) [51]
5.24
increase (slower) [46]
1.61
decrease (slower) [39]
1.06
decrease (faster) [49]
–4.91
–5
–4
–3
–2
–1
0
1
2
3
4
5
average 3-month return of global equities vs cash (in %)
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 5 / 1999 – 9 / 2014
(monthly data). Note: Comparison of 3-month changes of Global Macro Breadth Growth Index and contemporaneous
global equity returns (USD hedged vs cash).
8
6
As average returns might be distorted by
outliers, we employ two additional measures
– a hit ratio and an information ratio – to
gauge the link between macro data and asset
returns. The hit ratio is a measure of success,
which solely focuses on the directional
quality of a trading strategy. In a nutshell, it
answers the question as to what percentage
of monthly trading signals is profitable or not,
disregarding the amount of alpha created. For
example, a hit ratio of 60 % means, that for 6
out of 10 observations, the active return of the
trading strategy is positive, whereas a success
rate of 50 % is deemed neutral.
the signal quality was almost identical in
different cyclical states of the economy.
Accordingly, the “perfect foresight” trading
rule, which overweights (underweights)
global equities in times of improving
(deteriorating) economic data flow has
achieved an information ratio of
1.69 since 1999 (see Chart 5).
All results confirm our assumption that
cyclical swings in macroeconomic data are
highly correlated with concurrent equity
returns.
Macro data flow vs asset returns:
global sovereign bonds
As can be seen in Chart 4, the
contemporaneous trading signal based on
our MBI had a success rate of almost 70 % on
average for global equities. Encouragingly,
Comparing changes in our Global Macro
Breadth Index with corresponding
Global Macro Breadth Index (growth)
Chart 4: “Perfect foresight” trading rule based on global MBI with ...
average
69.7 %
increase
68.8 %
decrease
70.7 %
0
10
20
30
40
50
60
70
80
skill (hit ratio)
Chart 5: ... solid hit ratio and information ratio for global equities
700
600
performance
500
Information ratio: 1.69
400
300
200
100
0
1999
2002
2005
2008
2011
2014
trading rule
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 5 / 1999 – 9 / 2014
(monthly data). Note: Comparison of 3-month changes of Global Macro Breadth Growth Index and contemporaneous
global equity returns (USD hedged vs cash). Perfect foresight trading rule is long (short) equities vs cash during periods
when the Macro Breadth Index rises (falls). Monthly signals remain in place for 3 months respectively.
9
“It’s the economy, stupid!”
global government bond returns (USD
hedged) underpins our previous findings.
Sovereign returns have been clearly below
(above) average in periods of improving
(deteriorating) economic conditions,
represented by an increasing (decreasing)
MBI (see Charts 6 and 7). As in the case of
global equities, economic momentum counts.
With the MBI falling (rising) at a faster pace,
sovereign returns were even more positive
(negative). Results for global government
bonds are confirmed on the country level, with
US Treasuries and German Bundesanleihen
exhibiting similar responses to swings in the
respective MBIs.
been close to 1.7 since 1999 (see Chart 9),
the results have been somewhat weaker for
the period after the Great Financial Crisis
(GFC). The non-conventional monetary policy
instruments launched by several central banks
in the industrialized world in recent years have
probably blurred the cyclical economic signals
of our global MBIs to some extent.
Interestingly, the global results are not fully
backed by our country analysis. US Treasuries,
which should have been vulnerable to
distortions by the large-scale asset purchases
of the Federal Reserve, showed no different
response to the economic data flow in
the post-GFC times of quantitative easing.
Monetary policy in the United States seems
rather to have magnified than to have
mitigated the usual cyclical relationship
between economic data and bond returns in
recent years.
The hit ratio of the “perfect foresight” trading
rule for global sovereign bonds was almost
equal in different economic regimes with
an average around 66 % (see Chart 8). While
the information ratio of the strategy has
Chart 6: Global government bond returns also linked to the direction ...
Global Macro Breadth Index (growth)
average
0.61
increase
0.03
decrease
1.24
0
0.25
0.5
0.75
1
1.25
1.5
1.75
2
average 3-month return of global sovereigns vs cash (in %)
Global Macro Breadth Index (growth)
Chart 7: ... and momentum of the global macro data flow
average [185]
0.61
unchanged [0]
0
increase (faster) [51]
–0.26
increase (slower) [46]
0.35
decrease (slower) [39]
0.87
decrease (faster) [49]
1.54
–2
–1.5
–1
–0.5
0
0.5
1
1.5
average 3-month return of global sovereigns vs cash (in %)
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 5 / 1999 – 9 / 2014
(monthly data). Note: Comparison of 3-month changes of Global Macro Breadth Growth Index and contemporaneous
global government bond returns (USD hedged vs cash).
10
2
Chart 8: “Perfect foresight” trading rule based on global MBI achieves ...
Global Macro Breadth Index (growth)
average
66.2 %
increase
65.5 %
decrease
67.1 %
0
10
20
30
40
50
60
70
80
skill (hit ratio)
Chart 9: ... favorable results for global sovereign bonds as well
150
140
performance
130
Information ratio: 1.68
120
110
100
90
1999
2002
2005
2008
2011
2014
trading rule
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 5 / 1999 – 9 / 2014
(monthly data). Note: Comparison of 3-month changes of Global Macro Breadth Growth Index and contemporaneous
global sovereign bond returns (USD hedged vs cash). Perfect foresight trading rule is short (long) sovereigns vs cash
during periods when the Macro Breadth Index rises (falls). Monthly signals remain in place for 3 months respectively.
11
“It’s the economy, stupid!”
Signal quality of different
indicators
in the US and even above 72 % (2.06) in the
Eurozone (see Charts 10 and 11).
So far, we have confined the economic input
of our analysis to the Macro Breadth Growth
Index, a sub-index of our aggregate MBI
comprising macro activity and sentiment
indicators. Subsequently, we want to expand
the approach by comparing the signal quality
of several other economic variables, including
economic surprise indices, consensus growth
expectations and individual bellwether
indicators such as OECD leading indicators
or purchasing manager indices (PMIs).
Furthermore, we have increased the number
of asset classes involved to ensure a more
comprehensive view of domestic financial
market returns. Apart from equity and
sovereign bonds, we have also included
investment grade (IG) corporate bonds and
high yield.
Interestingly, all indicators under investigation
have hit ratios in excess of 50 %, with
economic surprise indices surpassing
65 % in both regions. Even consensus GDP
expectations, which tend to lag behind the
actual macro data flow, exhibited a fairly
high correlation with asset returns, achieving
success rates of 58 % in the US and 62 % in
the Eurozone. Although single economic
indicators trailed our MBIs, they nevertheless
showed fairly robust results. In the US,
the Conference Board leading indicator
reached a hit ratio of more than 62 %, while
in the Eurozone the European Commission
economic sentiment and the Ifo expectation
index had success rates of 68 % and 66 %
respectively.
The outcome of the broader analysis confirms
our previous findings for individual asset
classes. “Perfect foresight” trading rules based
on the different versions of our Macro Breadth
Index yield the best results, with average hit
ratios (information ratios) of up to 69 % (2.02)
In a nutshell, broader-based concepts such as
our Macro Breadth Indices tend to dominate
individual economic indicators when
explaining contemporaneous cyclical swings
of financial market returns. As a result, it is
important for asset allocators to capture the
whole economic picture, not just fragments!
Chart 10: Trading rule (“perfect foresight”) – US macro indicators
average hit ratio (light blue)
50 %
55 %
60 %
65 %
70 %
75 %
0
0.5
1.0
1.5
2.0
2.5
US MBI sentiment
US MBI growth
US Eco surprise
US MBI aggregate
CB US leading indicators
US consensus GDP
ISM manufacturing
OECD US leading indicator
average information ratio (dark blue)
12
Chart 11: Trading rule (“perfect foresight”) – Eurozone macro indicators
average hit ratio (light blue)
50 %
55 %
60 %
65 %
70 %
75 %
0
0.5
1.0
1.5
2.0
2.5
Euro MBI aggregate
Euro MBI sentiment
Euro MBI growth
EC economic sentiment
Ifo expectations
Euro PMI composite
Euro Eco surprise
Euro consensus GDP
OECD Euro leading indicator
average information ratio (dark blue)
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream, Consensus Economics, UBS.
Period: 3 / 2001 – 9 / 2014 [US], 5 / 2005 – 9 / 2014 [Eurozone] (monthly data). Note: Comparison of 3-month changes of
respective indicator and contemporaneous asset returns. Average hit / information ratio based on following asset classes:
equities vs cash, sovereigns vs cash, equities vs sovereigns, high yield vs sovereigns and IG corporates vs sovereigns.
Macro data flow, surprises and
consensus forecasts vs asset
returns: adding additional layers of
economic information pays off
After demonstrating that the broad
underlying trend of economic data is the
single most important cyclical macro factor
for explaining asset returns, we will now turn
to the question of whether adding additional
layers of information helps to increase the
explanatory power of our approach even
further.
In a first step, we combine the actual data
flow with related economic surprises.
Obviously, it should make a difference
whether an improving macro data trend is
surprising analysts on the upside or instead
undershoots buoyant expectations. This
assumption is confirmed by the figures in
Chart 12. The average three-month returns of
global equities have been significantly higher
than those of government bonds during
episodes of an improving macro data flow,
which also presents surprises on the upside,
compared to periods of improving macro data
alone (5.44 % vs 4.71 %).
Adding changes in consensus GDP
expectations, as measured by our Consensus
Breadth Index, on top of this leads to even
more favourable results (6.35 %). Clearly,
periods in which the broad macro data
flow improves and presents surprises on
the upside, accompanied by upgrades of
consensus growth expectations, constitute a
sweet spot not only for equities, but also for
risky assets in general. On the other hand,
these episodes coincide with below-average
returns for “riskless” government bonds. The
opposite holds true for periods of weaker
economic data, negative surprises and
receding consensus GDP expectations.
It is important to use all available sources
of information when assessing the
macroeconomic impact on financial markets.
Despite a lower marginal explanatory
power, it still makes sense to add changes
in economic surprise indices and consensus
GDP forecasts to the analysis in most
instances.
As can be seen for US and Eurozone equities
and sovereign bonds, this holds also true on a
country level (see Appendix).
13
“It’s the economy, stupid!”
Chart 12: Combining data trend with economic surprises and consensus GDP expectations
adds value
average
0.35
Indicator(s)
4.71
increase
5.44
6.35
–5.14
decrease
–7.59
–7.63
–8
–7
–6
–5
–4
–3
–2
–1
0
1
2
3
4
5
6
7
average 3-month return of global equities vs sovereigns (USD hedged %)
Global Macro Breadth Sentiment Index
Global Macro Breadth Sentiment Index + Global Economic Surprise Index
Global Macro Breadth Sentiment Index + Global Economic Surprise Index + Global
Consensus Breadth Index
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream, Consensus Economics, UBS.
Period: 5 / 2005 – 9 / 2014 (monthly data). Note: Comparison of 3-month changes of Global Macro Breadth Growth
Index / global economic surprises (growth data) / Consensus Breadth Index and contemporaneous global equity vs
sovereign returns (USD hedged).
Can we exploit any leading
properties of macroeconomic
indicators for asset allocation?
Our analysis offers strong evidence of a
contemporaneous relationship between
cyclical swings in economic variables and
financial markets. But to make our approach
systematically exploitable in an asset
allocation framework, it would be even more
helpful to unveil any leading properties of
macro indicators with regard to financial
market returns.
While applying our Global Macro Breadth
Index with a one-month lead time still
yields reasonable results, this approach
14
is nevertheless inferior to the coincident
relationship. For global equities vs sovereign
bonds, state-contingent average returns are
not as pronounced in the forward-looking
version as in the contemporaneous one
(see Chart 13), and the average hit ratio of
the trading rule drops from 66.8 % to 58.4 %
(see Chart 14). These findings are, by and
large, confirmed by the results for other asset
classes. Nevertheless, despite the prevailing
real-time impact of economic data on asset
returns, the short-term cyclicality of macro
indicators seems to reverberate in financial
markets. Against this backdrop, parts of
our toolbox may be successfully used as a
leading indicator for macro-based investment
strategies.
Global Macro Breadth Index (sentiment)
Chart 13: Global Macro Breadth Index – coincident vs 1-month lead (I)
average
0.33
2.10
increase
1.36
–1.60
decrease
–0.85
–2
–1
0
1
2
3
average 1-month return of global equities vs sovereigns [USD hedged] (%)
Global Macro Breadth Sentiment Index (coincident)
Global Macro Breadth Sentiment Index (1-month lead)
Global Macro Breadth Index (sentiment)
Chart 14: Global Macro Breadth Index – coincident vs 1-month lead (II)
66.8 %
average
58.4 %
66.1 %
58 %
increase
67.6 %
decrease
58.9 %
0
10
20
30
40
50
60
70
80
skill (hit ratio)
Global Macro Breadth Sentiment Index (coincident)
Global Macro Breadth Sentiment Index (1-month lead)
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 5 / 1999 – 9 / 2014
(monthly data). Note: Comparison of monthly changes of Global Macro Breadth Sentiment Index and global equity vs
sovereign bond returns (USD hedged vs cash). Perfect foresight trading rule is long (short) equities vs sovereigns during
periods, when the Macro Breadth Index rises (falls). Monthly signals remain in place for 1 month respectively.
But from an asset allocation standpoint, the
most promising cyclical approach would be
to anticipate the actual data flow and look
for potential vulnerabilities of consensus
expectations for short-term economic
indicators and medium-term GDP growth.
As a result, macro number crunching, if
done smartly, could be rewarded with
superior active returns. Relying instead on
proprietary medium-term forecasts for GDP
or CPI as economic input for asset allocation
is an exercise in futility. It is the consensus
perception of the current economic
environment, based on the macro data flow
and related surprises, that drives financial
markets – not our own forecasts for growth
and inflation!
Comparing the results of the forward-looking
trading rule over a range of different macro
indicators on a country level reveals further
interesting facts.
In the US, our Macro Breadth Index and
related sub-indices outperformed individual
economic indicators, delivering average
hit ratios (information ratios) of up to
55 % (0.57) for all asset classes involved.
Economic surprise indices, on the other hand,
had no exploitable leading properties for
asset returns. In contrast, forward-looking
trading rules based on these indicators even
produced negative hit and information ratios.
The same applies for the OECD US leading
indicator.
15
“It’s the economy, stupid!”
Findings for the Eurozone are somewhat
more ambiguous. While our MBIs
produced average hit ratios of around
58 % and information ratios of up to 0.73,
certain leading indicators, such as the Ifo
expectations or the PMI composite index,
achieved similar results. Obviously, those
indicators have a robust track record in
forecasting the broader flow of future
macroeconomic data and are therefore
reasonably closely linked to subsequent asset
returns.
Due to the longer history of the time series,
we are inclined to pay more attention to the
US results.
Chart 15: Trading rule (“1-month lead”) – US macro indicators
hit ratio (light blue)
44 %
47 %
50 %
53 %
56 %
59 %
–0.4
–0.2
0
0.2
0.4
0.6
58 %
60 %
US MBI aggregate
US MBI growth
US MBI sentiment
ISM manufacturing
CB US leading indicators
US consensus GDP
OECD US leading indicator
US Eco surprise
information ratio (dark blue)
Chart 16: Trading rule (“1-month lead”) – Eurozone macro indicators
hit ratio (light blue)
50 %
52 %
54 %
56 %
Ifo expectations
Euro MBI growth
Euro MBI sentiment
Euro PMI composite
Euro MBI aggregate
Euro Eco surprise
EC economic sentiment
OECD Euro leading indicator
Euro consensus GDP
0
0.2
0.4
0.6
0.8
average information ratio (dark blue)
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream, Consensus Economics, UBS. Period:
3 / 2001 – 9 / 2014 [US], 5 / 2005 – 9 / 2014 [Eurozone] (monthly data).Note: Comparison of monthly changes of respective
indicator and 1-month lagged asset returns. Average hit / information ratio based on the following asset classes: equities vs
cash, sovereigns vs cash, equities vs sovereigns, high yield vs sovereigns, IG corporates vs sovereigns.
16
Technical note
All calculations in this research note are based
on the following financial market indices:
Global
Global sovereign bonds (USD hedged): JP
Morgan GBI Broad Index Hedged USD; global
equities (USD hedged): MSCI World Index
Hedged USD (until 12 / 2001) and MSCI World
Index Hedged USD Gross (since 1 / 2002);
United States
US cash: USD LIBOR 1 month; US sovereign
bonds: Bloomberg / EFFAS Bond Index US Govt
All > 1 Year; US investment grade corporate
bonds: BofA Merrill Lynch US Corporate Index;
US high yield: BofA Merrill Lynch US High
Yield Index; US equities: MSCI USA Index USD
Gross
Eurozone
Euro cash: Euribor 1 month; German
Bundesanleihen: Bloomberg / EFFAS Bond
Index Germany Govt All > 1 Year; Euro
investment grade corporate bonds: BofA
Merrill Lynch Euro Corporate Index; Euro
high yield: BofA Merrill Lynch Euro High Yield
Index; Euro equities: MSCI EMU Index Euro
Gross
Back-testings and hypothetical or simulated
performance data have many inherent
limitations only some of which are described
as follows:
(i) They are designed with the benefit of
hindsight, based on historical data, and do
not reflect the impact that certain economic
and market factors might have had on the
decision-making process, if a client’s portfolio
had actually been managed. No back-testings,
hypothetical or simulated performance can
completely account for the impact of financial
risk in actual performance. Therefore, they
will invariably show positive rates of return.
(ii) They do not reflect actual transactions and
cannot accurately account for the ability to
withstand losses. Also, because these trades
have not actually been executed, these results
may have under-or over-compensated for the
impact, if any, of certain market factors, such
as lack of liquidity.
(iii) The information is based, in part, on
hypothetical assumptions made for modeling
purposes that may not be realized in the
actual management of portfolios.
No representation or warranty is made as to
the reasonableness of the assumptions made
or that all assumptions used in achieving the
returns have been stated or fully considered.
Assumption changes may have a material
impact on the model returns presented. The
back-testing of performance differs from
actual portfolio performance because the
investment strategy may be adjusted at any
time, for any reason.
Performance is shown for a limited period
of time. Performance over a different
market cycle may not be as favorable as the
performance shown and may result in losses.
17
“It’s the economy, stupid!”
Appendix
Chart 17: Macro data flow vs asset returns – US Equities
Macro Breadth Growth Index vs average returns
US Macro Breadth Index (growth)
average
1.80
increase
4.15
decrease
–1.0
–1
–0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
average 3-month return of US equities vs cash (in %)
Hit ratio
US Macro Breadth Index (growth)
average
63.7 %
increase
62.8 %
decrease
65.0 %
0
10
20
30
40
50
60
70
80
skill (hit ratio)
Trading rule (“perfect foresight”)
1200
1000
performance
800
Information ratio: 1.56
600
400
200
0
1991
1994
1997
2000
2003
2006
2009
trading rule
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 4 / 1992 – 9 / 2014
(monthly data). Note: Comparison of 3-month changes of US Macro Breadth Growth Index and contemporaneous
US equity returns (vs cash). Perfect foresight trading rule is long (short) equities vs cash during periods when the
Macro Breadth Index rises (falls). Monthly signals remain in place for 3 months respectively.
18
2012
Chart 18: Macro data flow vs asset returns – US Treasuries
Macro Breadth Growth Index vs average returns
US Macro Breadth Index (growth)
average
0.68
increase
–0.08
decrease
1.62
–1
–0.5
0
0.5
1
1.5
2
average 3-month return of US Treasuries vs cash (in %)
Hit ratio
US Macro Breadth Index (growth)
average
64.9 %
increase
63.7 %
decrease
66.6 %
0
10
20
30
40
50
60
70
80
skill (hit ratio)
Trading rule (“perfect foresight”)
200
180
performance
160
Information ratio: 1.62
140
120
100
80
1991
1994
1997
2000
2003
2006
2009
2012
trading rule
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 4/1992 – 9/2014
(monthly data). Note: Comparison of 3-month changes of US Macro Breadth Growth Index and contemporaneous
US Treasury returns (vs cash). Perfect foresight trading rule is short (long) Treasuries vs cash during periods when
the Macro Breadth Index rises (falls). Monthly signals remain in place for 3 months respectively.
19
“It’s the economy, stupid!”
Chart 19: Macro data flow vs asset returns – Eurozone equities
Macro Breadth Growth Index vs average returns
Euro Macro Breadth Index (growth)
average
0.71
increase
5.45
decrease
–4.56
–5
–4
–3
–2
–1
0
1
2
3
4
5
6
average 3-month return of Euro equities vs cash (in %)
Hit ratio
Euro Macro Breadth Index (growth)
average
69.5 %
increase
68.5 %
decrease
70.7 %
0
10
20
30
40
50
60
70
80
skill (hit ratio)
Trading rule (“perfect foresight”)
2400
2000
performance
1600
Information ratio: 2.38
1200
800
400
0
1999
2001
2003
2005
2007
2009
2011
2013
trading rule
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 9 / 1999 – 9 / 2014
(monthly data). Note: Comparison of 3-month changes of Eurozone Macro Breadth Growth Index and contemporaneous
Eurozone equity returns (vs cash). Perfect foresight trading rule is long (short) equities vs cash during periods when the
Macro Breadth Index rises (falls). Monthly signals remain in place for 3 months respectively.
20
Chart 20: Macro data flow vs asset returns – German Bundesanleihen
Macro Breadth Growth Index vs average returns
Euro Macro Breadth Index (growth)
average
0.71
increase
0.05
decrease
1.43
–1
–0.5
0
0.5
1
1.5
2
average 3-month return of German Bunds vs cash (in %)
Hit ratio
Euro Macro Breadth Index (growth)
average
64.4 %
increase
64.1 %
decrease
65.0 %
0
10
20
30
40
50
60
70
80
skill (hit ratio)
Trading rule (“perfect foresight”)
150
140
performance
130
Information ratio: 1.38
120
110
100
90
1999
2001
2003
2005
2007
2009
2011
2013
trading rule
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream. Period: 9 / 1999 – 9 / 2014
(monthly data). Note: Comparison of 3-month changes of Eurozone Macro Breadth Growth Index and contemporaneous
German Bund returns (vs cash). Perfect foresight trading rule is short (long) Bunds vs cash during periods when the
Macro Breadth Index rises (falls). Monthly signals remain in place for 3 months respectively.
21
“It’s the economy, stupid!”
Chart 21: Macro data flow, surprises and consensus forecasts vs asset returns
Combined macro signals vs US Treasury returns
average
0.75
Indicator(s)
0.05
increase
–0.11
–0.13
1.55
decrease
1.98
2.12
–1
–0.5
0
0.5
1
1.5
2
2.5
average 3-month return of US Treasuries vs cash (%)
US Macro Breadth Growth Index
US Macro Breadth Growth Index + US Economic Surprise Index
US Macro Breadth Growth Index + US Economic Surprise Index +
Consensus US GDP forecasts
Combined macro signals vs US equity returns
average
1.14
Indicator(s)
4.65
increase
5.97
5.86
–2.78
–3.35
–3.37
decrease
–4
–3
–2
–1
0
1
2
3
4
5
6
average 3-month return of US equities vs cash (%)
US Macro Breadth Growth Index
US Macro Breadth Growth Index + US Economic Surprise Index
US Macro Breadth Growth Index + US Economic Surprise Index +
Consensus US GDP forecasts
Source: Allianz Global Investors Global Economics & Strategy, Bloomberg, Datastream, Consensus Economics, UBS.
Period: 3 / 2001 – 9 / 2014 (monthly data). Note: Comparison of 3-month changes of US Macro Breadth Growth Index / US
economic surprises (growth data) / consensus US GDP forecasts and contemporaneous US equity / US Treasury returns
(vs cash).
22
Notes
23
“It’s the economy, stupid!”
Do you know the other publications of Allianz GI Global Capital Markets &
Thematic Research
Active Management
→→ The Changing Nature of Equity Markets and the Need for
More Active Management
Bonds
→→ The case of emerging market currencies in the long run
→→ Harvesting risk premium in equity investing
→→ China’s long march from Mao to market
→→ Active Management
→→ High-Yield Corporate Bonds
Smart Risk: Risk Management & Multi Asset
→→ Smart Risk with Multi Asset Solutions
→→ US High-Yield Bond Market – large, liquid, attractive
→→ Smart Risk investing in times of financial repression
→→ Corporate Bonds
→→ Strategic Asset Allocation
→→ Convertible Bonds – The best of both worlds?
→→ The new Zoology of Investment Risk Management
→→ Constant Proportion Portfolio Insurance (CPPI)
→→ Dynamic Risk Parity – a smart way to manage risks
→→ Portfolio Health Check®: Preparing for „Financial
Repression“
Financial Repression
→→ Shrinking mountains of debt
→→ International monetary policy in the era of financial
repression: a paradigm shift
→→ Silent deleveraging or debt haircut?
→→ Financial Repression – it is happening already
→→ Financial Repression – a silent way to reduce debt
Strategy and Investment
→→ Equities – the new safe option for portfolios?
→→ Is small beautiful?
→→ Global Emerging Markets – In the Spotlight
→→ Credit Spreads
Demography – Pension
→→ Financial Repression and Regulation: Paradigm Shift for
Insurance Companies & Institutions for Occupational
Retirement Provision
→→ Discount rates low on the reporting date
→→ IFRS Accounting of Pension Obligations
→→ Demographic Turning Point (Part 1)
→→ Pension Systems in a Demographic Transition (Part 2)
→→ Demography as an Investment Opportunity (Part 3)
Behavioral Finance
→→ Reining in Lack of Investor Discipline:
The Ulysses Strategy
→→ Overcoming Investor Paralysis: Invest More Tomorrow
→→ Outsmart Yourself! – Investors are only human too
→→ Two minds at work
→→ Dividendstrategies in times of financial repression
EMU
→→ Macroprudential policy – necessary, but not a panacea
→→ The Banking Union in a Nutshell
All our publications, analysis and studies
can be found on the following webpage:
http://www.allianzglobalinvestors.com
24
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25
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