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Exchange rate modelling techniques have come a long way since
the demise of the Bretton Woods system. Purchasing Power Parity
(PPP), Behavioural Equilibrium Exchange Rate (BEER) and
Macroeconomic Balance (MB) models are all reputable methods of
estimating "fair value" or "equilibrium" rates of exchange between
currencies.
However, a commonality the three share is their focus on
long-term equilibrium estimation. This means these models are often
ignorant of short-term shifts in fundamentals which can affect
exchange rate valuations and suggest currencies are out of sync
with current financial and economic fundamentals.
While this does make modelling in the short-term easier to
criticise, it also creates a compelling reason why short-term
equilibrium estimation can be a useful benchmark to measure these
movements against. Short-term fluctuations can have important
implications for businesses who trade goods and services across
borders, tactical asset allocation decisions for international
investors bearing currency risk, as well as policymakers in
countries where the domestic economy has a high degree of
sensitivity to changes in the exchange rate, such as those in
emerging markets.
Capturing changes in economic fundamentals using PMI
data
New research by IHS Markit aims to demonstrate how timely PMI
survey data can enhance short-term equilibrium exchange rate
estimation by quantifying changes in macroeconomic trends between
countries as they happen, and then
feeding these into short-term equilibrium exchange rate
estimations.
While changes in the financial landscape can be easily monitored
in real time given the rich availability
of financial markets data, monitoring momentum shifts in the
economic environment as they happen are
more difficult given the lack of equally-as-timely macroeconomic
data.
This doesn't mean this important area should be neglected, and
we find that PMI data play a statistically significant role in
capturing changes in the economic fundamentals that can affect
short-term exchange rate valuations.
We introduce our short-term equilibrium exchange rate model,
which provides estimates of a currency pair's "fair value", based
on the short-term changes in economic
and financial market fundamentals in one country,
relative to another.
Methodology
Many existing short-term FX valuation models tend to lean more
on financial market data because its timeliness makes capturing
fundamental changes in the investment environment between two
countries a simpler task. This means that potentially valuable
signals from economic data tend to be excluded from equilibrium
estimations.
The ideal candidate for measuring short-term economic changes in
one country relative to another would need to be reflective of the
broad macroeconomy, be timely and be comparable between the two
countries in question. Given PMI data satisfy these three criteria,
we input them into our model as a way of capturing relative
economic momentum shifts. PMI data is also unrevised and less
volatile than comparable official data series, making it especially
useful in this scenario.
As briefly touched on above, we are estimating the "fair value"
of a currency pair, so we need to look at the economic and
financial market fundamentals of one country (the base currency)
relative to the other (counter/quote currency), as there are forces
on either side affecting the rate of exchange.
For example, if we are computing a short-term "fair value"
estimate of EUR/USD (as in our case study), all our variables will
be for the eurozone, relative to the US.
Short-term equilibrium model: EUR/USD case
study
We apply ordinary least squares to the following theoretical
framework:
Where yt is our currency pair, x1t is our
variable which captures the relative change in economic
fundamentals, and x2t is our variable which captures the
relative change in financial market fundamentals.
Economic fundamentals
To measure short-term changes in economic fundamentals in one
country relative to another, we look at cross-country differences
in PMIs. The comparability of PMIs across countries, their proven
record of capturing broad and underlying
macroeconomic trends, and their timeliness makes them highly
appealing for an exercise such as this.
We use two variables to capture economic fundamentals -
Manufacturing Output and Manufacturing Input Price PMIs - as
changes in growth and inflation will have the strongest impact on
rates of return, which are a key driver of the value of an exchange
rate in the short-term. Also, the manufacturing sector tends to
display more cyclicality than other parts of the economy in the
short-run, and provides greater exposure to changes in
international trade, which are likely to alter exchange rate
valuations.
First, we take differences between country PMIs as this enables
us to observe how economic growth and inflation conditions are
evolving in one country relative to the other. Secondly, we then
apply an equally-weighted sum1 of these differences on a rolling
six-month basis as a method to measure relative growth and
inflation momentum.
We demonstrate the above using our EUR/USD case study.
Differentials are calculated as PMI data for the eurozone less the
equivalent PMI data for the US (i.e. Growth differential = Eurozone
Manufacturing Output PMI - US Manufacturing Output PMI).
As evident in chart 1, when the six-month sum of the
differentials increase, EUR/USD should trend higher as momentum in
growth and inflation favour a higher EUR. Equally, when the
six-month sum series decline, EUR/USD should trend lower as growth
and inflation in the US surpasses that in the eurozone. Consistent
outperformance of these metrics in one relative to the other will
see the differential sum series rise higher in a cumulative
fashion, therefore being a good means of capturing where momentum
in growth and inflation lies. Furthermore, the growth
and inflation differential sums both exhibit clear trends over the
short term, validating their use in short-term
exchange rate valuation.
The intuition behind this is as follows: a sustained period of
faster growth will likely encourage inflows into the respective
currency as investors capitalise on the greater rates of return
available in the short run, therefore shifting the currency into a
new short-term equilibrium. However, sustained periods of strong
growth will tend to stoke inflationary pressures, which are likely
to put pressure on short-term interest rates, which will also
attract foreign investors. Overlaying EUR/USD on our output and
inflation momentum series show clear instances where the currency
pair is reacting to changes in these short-term economic
fundamentals.
Financial market fundamentals
We focus on equity and sovereign bond market fundamentals in
determining our short-term equilibrium in EUR/USD. For equities,
relative performance in equity markets is captured with a variable
we create by comparing total returns of the STOXX Europe 600
against total returns of the S&P 500 over the past six months.
For sovereign bond market fundamentals, we take yield spreads
between 10-year German Bunds and 10-year US Treasuries.
As a caveat, this is not an exhaustive list of financial
market variables to find short-term "fair value" and we urge those
who wish to experiment to test with other variables they deem
appropriate.
For EUR/USD, we also added 10-year Italian BTP yields to proxy
for the effects quantitative easing has had on the EUR since
2014.
Results
The results of our estimation are shown on chart 2 above and are
compared against the EUR/USD exchange rate.
Our findings suggest that over the sample period (January 2004 -
September 2021), independent variables in our short-term
equilibrium model explain approximately 70% of the variation in
EUR/USD. This means that since 2004, EUR/USD is well correlated
with its short-term equilibrium. We also find that our PMI-based
explanatory variables are statistically significant at the 1%
threshold, and the inclusion of these improves the adjusted
R-squared by around 6 percentage points, suggesting PMIs do a good
job at capturing the economic drivers of EUR/USD.
The model also identifies periods in which EUR/USD is either
over- or under-valued, according to its economic and financial
market fundamentals (see chart 3). Considerable under-valuation was
seen leading up to 2004, and to a lesser degree in 2009 and between
2015 and 2017. Likewise, the chart highlights periods of
overvaluation, such as in 2007 to 2008, parts of 2009 and for a
large part between 2013 and 2014.
On average, and in absolute terms, we observe EUR/USD being one
standard deviation away from its fair value. As can be seen in
chart 4, when EUR/USD is greater than one standard deviation away
from its short-term fair value, sharp movements in the currency
pair tend to follow.
Monitoring these developments can therefore provide fruitful
opportunities for businesses, international investors and
policymakers to identify periods of above-average misvaluation and
adjust accordingly.
EUR/USD converging on short-term fair value
Turning our attention to what the short-term equilibrium model
suggests about the current EUR/USD level - we find the currency
pair to be trading around 1% above it's short-term "fair value".
This is the closest EUR/USD has been to its short-term equilibrium
level this year and follows a sustained period of EUR depreciation
that had been anticipated by our model, which has closed the
valuation gap.
At the time of writing, EUR/USD is trading close to 1.16, which
compares to our current short-term fair value estimate of 1.15. The
short-term equilibrium model has valued EUR/USD at around the 1.15
mark since June, when EUR/USD was trading as high as 1.22.
Summary
We introduce a method for enhancing short-term equilibrium
exchange rate estimation by adding in PMI-based variables to
capture shifts in economic fundamentals between countries.
The PMI's ability to capture broad underlying macroeconomic
trends, its timeliness, and comparability between countries makes
it an ideal candidate to measure relative changes in economic
conditions.
Our initial research serves as a promising foundation for
further investigation using PMI data for short-term equilibrium
exchange rate estimation.
1 We also applied linear time-decay to the differences, giving
the latest observation a higher weight than the sixth, but found
this did not cause any material difference in equilibrium
estimates. Other analysts may wish to experiment with different
weighting techniques
Purchasing Managers' Index™ (PMI™) data are compiled by IHS Markit for more than 40 economies worldwide. The monthly data are derived from surveys of senior executives at private sector companies, and are available only via subscription. The PMI dataset features a headline number, which indicates the overall health of an economy, and sub-indices, which provide insights into other key economic drivers such as GDP, inflation, exports, capacity utilization, employment and inventories. The PMI data are used by financial and corporate professionals to better understand where economies and markets are headed, and to uncover opportunities.
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