5.5. Foreign Trade.
As we mentioned in Introduction, the main purpose of writing the guidebook is to gain practical
knowledge on how to make profits in Forex. To that end, we will explore two themes: an impact
of trade imbalance on FX rates and how to interpret economic data related to trade. Intuitively,
trade should impact FX rates because they are intertwined. Two accounting statements are
important to FX traders, balance of trade (TB) and current account (CA).
Balance of trade is an accounting statement of a country’s net (export minus import) position
with another country, or countries:
TB = (E – I)g + (E – I)s (1)
(E – I)g = Export minus import of goods
(E – I)s = Export minus import of services
A current account sums all currency flows into and out of a country in a form of goods, services,
income, and unilateral transfers. The formula for the balance of current account is as follows:
CA = TB + NI + NCT (2)
NI = Net income from salaries, securities investments, direct investments, etc.
NTC = Net current transfers: donations, aids and grants, official assistance, etc.
Negative trade balance should cause the domestic currency to become weaker – so says the
common wisdom. The premise is applicable to goods that are substitutes such as a machine
with the same features made in the US, Germany, or Japan. But when there are structural
causes, the mechanism of correcting imbalances via FX rates does not work well, unless the
changes are drastic. A trade deficit causes domestic currency to weaken, since more of the
country's financial resources flow out of the country than other nations' flow in.
As of mid-2008 the following matters pertaining to trade were worrisome, at least for some
economists, huge trade surplus of China and large US trade deficit. The US trade deficit has
started to accelerate in 2003. And many institutions and think tanks recommended remedying
these unwelcome developments employing FX rate corrections.
All major currencies do float freely depending on interrelations of forces in capital markets. How
then technically a country can force to strengthen or weaken its domestic currency? The only
workable tool to achieve a desired direction of FX rate is by a concerted participation of central
banks. Tariffs and the like are not an option at the current trend to globalization. And
interventions of just one central bank to defend its domestic currency is usually ephemeral.
In 1985, France, Germany, UK, Japan, and US signed the so called Plaza Accord aimed to
depreciate the US dollar in relation to the Japanese yen and German Deutsche Mark and in the
process reduce the US current account deficit. The interventions of the central banks forced the
USD/JPY pair to depreciate about 50% over the period of two years.
In fact, the USD has depreciated so much that in 1987 the G-7 countries signed another
agreement to stabilize FX rates - the Louvre Accord. A concerted action of the central banks is
thus a viable tool to influence a long-term direction of FX rates. However, the central banks did
not make concerted efforts to influence currency rates in the past decade. We can infer that the
depreciation of the USD is a result purely of market forces. Statements from many US
policymakers that “we support a strong dollar” are, to put it mildly, meaningless. The opposite
however is true if the same statement were uttered by a chairman of the Fed.
The US Fed, the Bank of England, and the European Central Bank treat FX rates as a very
marginal input to their decision-making process in conducting monetary policy. For smaller
open economies (e.g., New Zealand, Australia, and Switzerland) and countries that domestic
economic growth (many Asian countries) relies heavily on export, the FX rates are on the table
when deliberating optimal monetary policy. But targeted inflation regimes adopted by many
countries dominate rationale for changing interest rates. One of the best ways to learn about
most important economic factors that are on the minds of central bankers is to read minutes of
Table 5.10. Change of FX rates from 01/01/2003 to peak of 2008
EUR/USD USD/JPY GBP/USD USD/CAD USD/CHF AUD/USD NZD/USD EUR/JPY USD/CNY USD/PLN USD/MXN
55% -12% 32% -38% -29% 71% 54% 37% -17% -45% ~0%
The beginning of the subprime in mid-2008 crisis was characterized by a very sharp reversal of
the above trends as the world flocked to a safe haven USD. After the situation with functioning
of the global financial system normalized, the USD deprecated against most of the currencies.
As of April 2010, we have a few mini trends; main being the appreciation of the USD.
Table 5.11.gives a perspective on trade changes for the US. A few observations are in order.
China and imports of petroleum products (crude oil for all practical purposes) are two items that
vividly stick out as most influential. For example in 2007, crude oil and net trade balance of
goods with China counted for almost 72% of Total Trade Balance, (-330,978 –
256,611)/819,373. The last column shows the difference between years 2007 and 1999. Again
and not surprisingly, crude oil and imports of goods from China are dominant causes of US
trade deficit and the current account deficit with the rest of the world.
Table 5.11. US Trade Balance with selected countries, imports of petroleum products,
and total current account (millions of USD).
1999 2000 2001 2002 2003 2004 2005 2006 2007 07 - 99
Petro import 67807 120279 103587 103491 133079 180459 251856 302430 330978 263171
EU -46057 -57717 -64284 -85423 -98011 -110979 -125512 -120212 -113936 -67879
Mexico -23816 -25657 -31098 -38459 -42471 -47399 -52770 -67302 -77589 -53773
China -68793 -83971 -83295 -103276 -124384 -162335 -202085 -233087 -256611 -187818
Japan -74966 -83238 -70806 -71947 -68012 -77806 -85110 -90967 -85139 -10173
Canada -35039 -55207 -55984 -51309 -55025 -69890 -81888 -75083 -70611 -35572
US, total balance -347819 -454690 -429519 -484955 -550892 -669578 -787149 -838270 -819373 -471554
US, total CA -301630 -417426 -384699 -461275 -523400 -624993 -728993 -788116 -731214 -429584
Source: Bureau of Economic Analysis
Let us take crude oil first. Major causes of recent jump in prices for crudes are accelerated
global (mainly China) demand, increased costs of new exploration, and weak USD. The
question is what comes first in causation, crude oil or USD? There is a weak correlation (less
than -0.2) between spot prices of crudes and trade weighted exchange index for USD. There
are times when clearly there is a strong reaction to oil prices when concurrently the USD
depreciated. But many times this inverse relationship between crude oil and currencies does
not hold. The bottom line is this: betting on a direction of FX rates due to price movement of
crude oil is not a reliable strategy, though there could be some patterns for large price changes.
Even for the Canadian dollar – Canada is a large exporter of energy products – correlations are
around -0.2 between the USD/CAD pair and spot prices of crude oil.
Fixing trade deficit stemming from imports of crude oil by depreciating USD is not the long term
solution. Everybody knows what the remedies are but US policymakers ignored the issue in the
past decade and miscalculated the impact of the growth of global economies. That is,
implementation of new energy conservation codes (e.g., in buildings, CAFE) has been too small
compared to accelerated growth of global energy consumption. Energy conservation codes
should be more aggressive.
One of the tools the US has at her disposal in a fight against huge trade deficit with China is
appreciation of the Chinese renminbi (CNY). Table 5.10. shows that in the five and a half years
period since January 1, 2003, the USD depreciated only 17% against the CNY. Such a pace of
appreciation of the renminbi warrants continual growth of trade deficit with China for decades.
China’s cheap labor, strong work ethics, capitalistic attitude, and a bevy of citizens will continue
to attract foreign investors and importers.
The USD/CNY pair is not determined by market forces but is controlled by Chinese officials. In
addition China has been accumulating huge foreign reserves, mainly the USD. On one hand,
purchase of the USD helps the US to finance spending since US citizens do not save enough.
But demand for the currency makes the USD stronger – against the renminbi.
It is noteworthy to point that the stated monetary policy objective by the People's Bank of China
is to maintain the stability of the value of the currency and thereby promote economic
growth. China can alleviate trade imbalances by promoting more aggressively domestic growth
instead of exports. Table 5.12. confirms soaring growth of current accounts and foreign
exchange reserves in past few years. It almost begs to ask – how much more can China grow
without a pause? The ratio of CA to GDP exceeds 10%.
Table 5.12. China: Current Account, growth of GDP,
and Foreign Exchange Reserves.
CA, USD bn gGDP, % FXR, USD bn
2000 20.5 8 165.6
2001 17.4 8.3 212.2
2002 35.4 9.1 286.4
2003 45.9 10 403.3
2004 68.7 10.1 609.9
2005 160.8 9.9 818.9
2006 249.9 11.1 1,066.30
2007 371.8 11.4 1,528.20
Source: State Administration of Foreign Exchange, People's Republic of China.
The economists strongly disagree about the impact of trade and current account deficits. That
is the sufficient reason for us, at least the author, to ignore foreign trade in trading decisions;
unless, developments in foreign trade call for monetary policy interventions. Some are
convinced that trade deficit contributes to the growth of unemployment and loss of
competitiveness. Others argue that statistical data point to positive relationship between
growing trade deficit and domestic GDP. The ratio of trade deficit to GDP is a most often
quoted benchmark for appraising how healthy or ill the situation is. However, there are
disagreements on thresholds of the ratio. For some the ratio of -3.5% is worrisome and -7%
alarming; but many deem -12% acceptable.
In recapitulation, trade imbalance is important to prediction of FX rates movements but
indirectly; unless values are extreme by historical precedence then the influence is direct. But
typically inquiries should focus on how trade balance impacts domestic economy and monetary
policy. It’s beneficial to know key trading partners, main trade products/services, and
contribution of trade to GDP.
(b) Great Britain
Per Table 5.13., Great Britain have had consistently current account deficit since 1984.
Negative balance of Goods counterweights positive balances from Services and Income, which
have been consistently positive. Those are most outstanding trade patterns that strike out of
Table 5.13. UK: Yearly Current Accounts.
CA Goods Services Income
1980 1,740 1,329 3,829 -1,765
1981 4,846 3,238 3,951 -1,124
1982 2,233 1,879 3,198 -1,368
1983 1,258 -1,618 4,076 191
1984 -1,294 -5,409 4,491 1,190
1985 -570 -3,416 6,767 -997
1986 -3,614 -9,617 6,403 1,694
1987 -7,538 -11,698 6,813 917
1988 -19,850 -21,553 4,450 753
1989 -26,321 -24,724 3,643 -792
1990 -22,281 -18,707 4,337 -2,979
1991 -10,659 -10,223 4,102 -3,307
1992 -12,854 -13,050 5,602 128
1993 -11,759 -13,066 6,741 -191
1994 -6,638 -11,126 6,509 3,348
1995 -8,476 -12,023 8,957 2,164
1996 -6,717 -13,722 11,204 556
1997 -840 -12,342 14,106 3,314
1998 -3,195 -21,813 14,672 12,320
1999 -21,717 -29,051 13,597 1,270
2000 -24,833 -32,976 13,615 4,540
2001 -21,884 -41,212 14,423 11,664
2002 -16,513 -47,705 16,830 23,443
2003 -14,921 -48,607 19,162 24,646
2004 -19,328 -60,893 25,918 26,596
2005 -30,985 -68,789 24,611 25,204
2006 -50,725 -77,555 31,023 7,760
2007 -59,675 -89,515 38,331 5,302
The UK has been in recent years a net exporter of crude oil, with marginal impact on overall
trade balance. But taking into account all fuels, the UK is a net importer. Per below table,
Balance for petroleum and its products (GBP mil.):
Export Import Balance
2006 23,274 26,706 -3,432
2007 22,764 26,689 -3,925
On balance, raising prices of crude oil have slight negative impact on the UK economy and
The contribution of products is balanced across all industries. There is no one industry that
dominates trade, in contrast to, say, Switzerland. Machinery and transport equipment (vehicles)
on aggregate is the largest component of imports and exports, with a negative balance in the
range of 30 billions of GBP in past two years.
Regarding major trading partners, the pattern is obvious, E27 is a largest trading partner and
the US is second distant. Trade with the US is roughly five times smaller than with Europe. But
the difference is that the trade balance with the US is positive and with EU27 very negative.
China’s impact has not been as drastic as on the US but it’s continually growing.
Net trade balance (GBP mil.):
EU27 -32,087 -41,824
China -12,027 -14,824
USA 6,379 6,229
The ratio of CA-to-GDP peaked in 2007 with the value of -4.7%, a level that is not alarming but
worrisome. Long term traders could have used it (as one of the parameters) to making an
educated bet on a weakening of the GBP in the coming months. What can we take from UK
foreign trade? Europe and the US are two most important spots to watch for impact on the UK
Situated at the heart of Europe, Switzerland’s well being is obviously heavily depended on the
economic situation of Europe. Geographical proximity and economic interrelations make strong
correlations between the euro (EUR), the British pound (GBP), and the Swiss franc (CHF).
Deviations that are not explained by fundamentals can be exploited in profitable trading.
Table 5.14. Switzerland: net current account items.
Labor & investment
CA Goods Tourism Finance Labor Invest.
1985 01 3.4618 -2.7185 3.3886 0.8890 0.9681 3.1171 -0.8170 3.9341
1990 01 3.0829 -3.2484 4.1458 0.9159 1.2640 2.8975 -1.6928 4.5903
2001 01 7.2002 -3.6099 6.8319 1.2350 2.9802 5.8968 -2.1768 8.0737
2001 04 9.5232 -1.1551 6.2131 0.4843 2.9670 6.4084 -2.2529 8.6613
2001 07 5.7557 -0.7437 5.5628 0.5855 2.7982 3.6577 -2.3126 5.9703
2001 10 10.7795 0.8587 5.3655 0.4528 3.0298 7.2396 -2.3391 9.5787
2002 01 7.3582 0.2583 6.5730 1.3042 2.8009 2.6154 -2.2719 4.8872
2002 04 7.1480 0.7557 6.0034 0.4791 2.5361 3.1378 -2.3082 5.4459
2002 07 10.3219 2.0021 5.6095 0.4241 2.4654 4.3570 -2.3208 6.6778
2002 10 11.4003 2.0690 5.8413 0.5325 2.5907 6.2241 -2.3443 8.5684
2003 01 12.7291 -0.3971 6.5833 1.4035 2.3985 7.8580 -2.4067 10.2647
2003 04 13.7757 1.8461 5.8440 0.3304 2.4885 8.5015 -2.4100 10.9115
2003 07 12.3878 1.3260 5.7451 0.1956 2.5777 7.9168 -2.4797 10.3964
2003 10 17.3810 1.5434 6.4548 0.4159 2.9183 10.5075 -2.4189 12.9264
2004 01 16.5132 1.8925 7.0726 1.2851 2.7798 9.8050 -2.4895 12.2946
2004 04 14.5503 2.1579 6.1380 0.2503 2.6051 8.0857 -2.5639 10.6497
2004 07 13.2766 1.0577 5.6934 -0.0134 2.4648 8.5004 -2.5498 11.0502
2004 10 13.9856 1.5968 6.7383 0.3398 2.7871 7.4831 -2.5133 9.9965
2005 01 15.5992 -0.0547 7.2542 1.3166 2.6453 11.2082 -2.6346 13.8428
2005 04 18.8696 2.1549 6.4085 0.1407 2.7414 12.6649 -2.6026 15.2674
2005 07 13.5418 0.6172 6.9001 -0.1390 2.9821 9.8868 -2.6050 12.4918
2005 10 15.4828 0.2869 7.7449 0.1750 3.3309 13.4136 -2.6043 16.0179
2006 01 18.9316 0.4315 9.3679 1.2922 3.3075 11.9065 -2.6810 14.5875
2006 04 16.6299 1.0580 7.2845 -0.0818 3.0778 11.2289 -2.7149 13.9437
2006 07 16.9500 2.9029 6.9217 -0.2709 3.0668 10.0823 -2.8100 12.8923
2006 10 19.1622 0.7101 9.6009 0.0109 3.6016 13.0896 -2.8182 15.9078
2007 01 20.7104 2.3889 9.8892 1.3760 3.7319 10.5420 -2.9269 13.4690
2007 04 24.7138 2.6000 9.6606 -0.0247 4.1103 15.8527 -2.9524 18.8051
2007 07 25.1065 3.0337 9.4684 -0.2033 4.0550 14.2446 -3.0136 17.2582
2007 10 15.1180 1.6955 10.0063 -0.0248 4.3814 8.6682 -3.0438 11.7120
2008 01 12.8596 3.0785 11.6161 1.5012 4.2547 -0.4637 -3.1247 2.6609
Per Table 5.14., the current account of Switzerland has been positive for decades. As oppose
to most other countries where trade balance dominates the current account, for Switzerland
each item is important, goods, services, and income. Tourism and finance (e.g., commission
transactions with foreign clients) are major contributors to services. Though finance and
insurance have been staples of Switzerland’s economy, the country is making deliberate efforts
towards a knowledge-based economy. The impact is reflected in growing contribution of goods
in current account. 45% of the active population is occupied in the science and technology
Per Science and technology (S&T) indicators in Switzerland (Swiss Federal Statistical Office,
Science and Technology, 2008), Switzerland is world-leader in the instrument industry and
comes second (after Sweden) in the pharmaceutical industry. And products from these
industries contribute most to Goods in current account.
As to major trading partners, EU27 counts for almost 2/3 of exports and the US about 10%. So
what to take from a foreign trade to make money in trading? Switzerland and the Swiss frank
are perceived as a stable. Swiss banking sector thrives because of secrecy. Banks and their
staff must keep all data and documents strictly private and confidential. The obligation to
maintain banking secrecy applies to everyone that is exposed to information about the clients.
Article 273 of Swiss Criminal Code punishes responsible person of breaking the law. The
convicted person may face a jail sentence or fine up to CHF 30,000 or both. To be clear,
confidentiality is not absolute and excludes criminals.
Coded Swiss Account is the most popular private account that conceals the identity of the
account holder to the outside world. A wealthy client can choose a pseudonym or a code
number for conducting all financial transactions. The client’s identity is only known to a few high
ranking bank officials. Taxation is another reason for putting money to financial instruments
with a Swiss bank.
Non-residents with a Swiss bank account pay no income taxes and capital gain taxes. Having
one bank account allows a non-resident to connect directly to the financial markets and trade
globally in any world currency. Isn’t it wonderful? Well, the reality after September 11 is much
stricter. Switzerland signed in 2003 a new information-sharing agreement with the US and
since July 1, 2005 the Swiss account holders from the EU countries are subject to tax
withholding. The pressure to alter the Swiss privacy laws has been continually growing
because many European countries still believe that Switzerland is a destination to avoid taxes.
Tax evasion in Switzerland is not considered an offence but a misdemeanor. Not reporting of
one's assets is not sufficient evidence for criminal intent. Those laws are enough conducive to
exploit loopholes and save on taxation.
When privacy laws will no longer be a lure for offshore investors, Switzerland’s economy and
the Swiss franc will be severely damaged – the item any trader should be watchful and aware
of. Demand for the CHF grows at the times of global turmoil since the currency is deemed to be
a save heaven. Appreciation of the CHF will persist till the turmoil subsides. These are the
circumstances for profitable trading.
Nowadays Japan is known around the globe as a country that exports quality cars, electronics,
steel, precision machinery, and a few other goods. Her economic prowess did not happen by
accident but by design and in recent decades.
Table A1 provides a few insights. First, indices hardly moved in the past ten years since 1998.
Appreciations are in the order of 10%. Statistics for 2006-07 indicated economic rebound and
hopes for ending formally the bubble that started, per some economists, in 1987. However, the
indices have been subsiding in 2008 due to slowing global economy. Index of Construction
Activity shows still a struggling industry. Also, weight assigned for construction is only 7%.
Construction is not a place to look, at present, for signs of economic standing of Japan. Tertiary
Industry, on the other hand, counts for over 60% of industrial activity and is the strongest
indicator of the growth of GDP. Industrial Production is also a strong indicator of the health of
Japanese economy because it contributes most to exports (e.g. autos, electronics, etc.). In
addition, industrial and manufacturing activities stimulate services (tertiary).
Table 5.15. Japan: Indices of Industrial Activity.
Index Weight 98 99 00 01 02 03 04 05 06 07 08Q1 08Q2
All Industry 100.0 97.5 97.9 100 99.1 98.7 99.5 101.9 103.8 ... ... - -
Agric., Forestry, Fish.
(AFF) 1.6 98.8 100.1 100 98.0 96.8 92.9 93.6 94.8 ... ... - -
Construction 7.0 102.9 104.2 100 96.0 91.9 87.1 82.2 82.7 81.9 76.7 72.3 62.5
Industrial Production 20.2 94.4 94.6 100 93.2 92.0 95.0 100.2 101.3 106.2 110.0 111.5 107.7
Tertiary Industry 60.4 98.1 98.2 100 101.1 101.0 101.9 104.3 106.6 108.7 110.0 109.9 108.6
Government Services etc. 10.8 96.4 98.0 100 101.1 102.4 103.4 105.7 107.8 107.7 107.4 108.1 107.3
All Industry except AFF 98.4 97.5 97.9 100 99.1 98.7 99.6 102.0 103.9 106.1 107.4 107.4 105.0
Table 5.16. Japan: Trade and Current Account with Asia.
(¥, 100 mil)
Asia China HK
CA Goods Services Income CA CA
1996 60,149 62,338 -9,271 9,955 -19,673 24,039
1997 70,977 69,940 -7,372 13,233 -23,782 31,309
1998 39,957 46,029 -11,300 8,888 -20,867 25,892
1999 28,851 42,726 -11,844 1,394 -21,335 19,750
2000 38,262 48,357 -8,020 1,127 -25,414 24,796
2001 18,894 24,910 -9,518 6,508 -30,010 23,990
2002 43,899 48,552 -9,443 8,193 -24,637 28,661
2003 66,733 64,563 -5,517 9,361 -15,906 31,699
2004 88,623 84,937 -6,636 11,765 -14,850 35,478
2005 84,901 74,044 -2,371 15,156 -25,601 36,958
2006 90,259 71,744 3,896 17,573 -22,020 40,037
2007 117,180 96,447 2,385 21,620 -13,203 39,928
Source: Ministry of Finance
Table 5.17. Japan: Trade and Current Account with North America.
(¥, 100 mil)
North America USA
CA Goods Services Income CA Goods Services Income
1996 35,011 35,306 -24,855 27,051 39,588 40,175 -23,457 25,237
1997 58,134 51,106 -24,487 33,705 61,807 54,923 -22,785 31,759
1998 84,332 70,723 -24,159 40,281 85,927 71,946 -22,417 38,814
1999 85,431 72,842 -21,989 36,412 85,650 73,552 -20,968 34,778
2000 98,378 78,375 -16,381 38,595 98,417 79,322 -15,798 36,941
2001 101,496 72,789 -17,971 48,675 100,170 73,880 -17,875 46,049
2002 105,970 79,568 -14,978 42,339 102,950 78,887 -15,089 40,040
2003 95,981 68,807 -7,879 37,414 92,534 68,608 -9,074 35,297
2004 98,961 71,680 -9,677 38,392 96,915 72,129 -10,586 36,750
2005 113,825 77,765 -10,240 47,928 111,170 77,612 -11,085 46,212
2006 134,914 90,697 -9,915 56,777 130,770 90,008 -10,675 53,954
2007 134,559 86,602 -9,065 59,700 130,730 85,706 -9,575 57,184
Source: Ministry of Finance
Table 5.18.. Japan: Trade and Current Account with EU and UK.
(¥, 100 mil)
CA Goods Services Income CA Goods Services Income
1996 7,841 17,413 -17,750 8,786 -5,703 6,096 -5,515 -5,904
1997 18,496 26,836 -17,044 9,238 -3,094 7,550 -4,781 -5,497
1998 41,695 43,384 -10,649 9,736 2,447 10,915 -3,849 -4,247
1999 43,268 37,386 -10,862 17,381 4,897 8,832 -3,745 44
2000 39,178 35,365 -10,464 14,813 1,205 8,319 -3,920 -3,051
2001 29,907 25,896 -9,279 13,924 424 7,159 -3,208 -3,280
2002 26,975 22,560 -11,120 16,136 -314 6,675 -4,456 -2,329
2003 40,235 28,115 -7,862 20,418 1,127 7,585 -3,646 -2,669
2004 50,304 33,128 -7,556 24,896 4,538 7,598 -2,613 -439
2005 57,520 32,439 -1,703 27,364 8,810 8,354 1,882 -1,413
2006 72,347 38,832 -616 34,456 9,151 8,731 1,046 -468
2007 90,835 46,519 31 44,783 12,324 9,309 1,109 1,983
Source: Ministry of Finance
Trade of goods dominates almost completely Canada’s current account. Canada has been
historically enjoying positive CA. Canada’s foreign trade can be summarized in two words,
energy and the USA. Table 5.19.shows in no uncertain terms dominant role of the US on
Canada. Crude oil and natural gas, on the other hand, are major contributors to trade (and
current account) surplus, per Table E. The Canadian dollar is a commodity currency with
energy as a key component, especially at the current levels of prices for crude oils.
The Canadian dollar has a high degree of predictability because just two factors dominate the
influence, though there are many more. There is often a gap in response of the CAD to
fundamental factors coming from the US. The CAD will eventually yield to the pressures; and
those are the circumstances where a trader can handsomely benefit from appreciating
fundamental forces. Rising prices of crude oil causes the CAD to appreciate from two fronts,
rising GDP on increased export and elevating inflation from energy products. Canadians spend
a big chunk of income on energy because of cold weather and long transportation distances.
Impact of macroeconomic indicators depends on a relative change in both countries. That is, if
Canadian indicators point to a faster economic growth than US indicators, the USD/CAD is likely
to appreciate. But persistent economic slowdown in the US will negatively impact Canadian
economy (the response gap). And those developments should weaker the CAD, usually in a
trendy pattern that we can ride on for making profits.
Table 5.19. Canada: net trade of goods with major trading partners.
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
USA 66330 92502 129629 133461 126869 122878 139157 150607 141611 135473
Japan -5380 -6466 -7328 -6301 -7068 -5627 -4954 -5630 -5910 -6235
Mexico -6215 -7924 -10026 -9368 -10324 -9979 -10339 -11229 -11635 -12208
China -5153 -6287 -7596 -8460 -11872 -13773 -17334 -22411 -26830 -28999
TOTAL 20058 35012 56223 60975 47425 44930 56404 55398 43621 43637
Source: Industry Canada
Table 5.20. Canada: net balance of major trading goods.
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
oil) 18,059 20,801 37,356 39,805 34,246 41,371 44,371 55,544 54,426 58,875
NATURAL GAS in
gaseous state 8,868 10,865 20,327 25,317 17,661 24,262 24,474 32,334 25,447 25,299
WOOD ARTICLES 15,102 18,319 16,748 16,044 15,563 14,299 18,316 16,645 13,735 9,937
BASE METALS 2,819 2,149 806 3,421 3,655 3,579 4,830 4,120 9,338 16,461
VESSELS 18,478 30,155 28,503 28,027 22,475 18,734 19,807 15,119 9,048 2,649
sub-total 63,327 82,288 103,740 112,614 93,599 102,244 111,799 123,763 111,994 113,220
BALANCE 20,058 35,012 56,223 60,975 47,425 44,930 56,404 55,398 43,621 43,637
Source: Industry Canada
A note to readers, we gathered data from Industry Canada (www.ic.gc.ca/epic/site/tdo-
dcd.nsf/en/Home) and would like to alert that they differ from Statistics Canada.
Australia’s current account has been negative since 1975. The ratio of CA to GDP has elevated
above 4% since 2002 and picked in December 2007 at 7.4%. At the same time economy
Australia’s economy enjoyed healthy growth and reduction of unemployment. Australia is a
prime example for those economists who propound that trade deficit is not harmful to the
economy and well being of its citizens.
Table 5.21. compiles quarterly growths of GDP, current account, trade balance, net income
against changes in AUD/USD.
Table 5.21. Australia – Growth rates of: GDP, AUD/USD,
Current Account, Trade Balance, and Net Income.
gGDP AUD/$ gCA gTB gI
Dec-1989 0.7% 0.9% 16.8% 40.0% -7.0%
Mar-1990 0.3% -2.2% -10.9% 18.5% -27.2%
Jun-1990 0.0% 3.5% 36.2% 78.7% 15.7%
Sep-1990 -0.2% 1.2% -31.3% -333.2% -2.5%
Dec-1990 -0.4% -2.7% 8.1% 80.6% -17.9%
Mar-1991 -0.4% 0.0% 13.2% 170.9% 3.3%
Jun-1991 -0.4% -1.0% 25.1% 358.0% 5.2%
Sep-1991 0.0% 2.7% -29.9% -127.2% 7.9%
Dec-1991 0.3% -5.7% 35.3% 244.1% 22.0%
Mar-1992 0.5% 2.0% -22.5% -24.4% -14.9%
Jun-1992 0.7% -2.3% -0.2% 29.9% -3.6%
Sep-1992 1.1% -4.1% -62.0% -512.4% -0.5%
Dec-1992 1.3% -5.8% 36.4% 79.4% 18.2%
Mar-1993 1.0% 5.7% 0.4% 71.9% -5.2%
Jun-1993 0.6% -4.7% 8.3% 58.5% 6.3%
Sep-1993 0.7% -2.5% -55.7% -4866.7% 1.6%
Dec-1993 1.3% 5.3% 37.7% 99.1% -1.7%
Mar-1994 1.7% 2.8% -13.5% -364.7% -9.2%
Jun-1994 1.5% 2.6% -42.3% -115.2% -40.3%
Sep-1994 0.9% 0.5% -78.7% -2051.8% -6.3%
Dec-1994 0.6% 3.6% 26.3% 47.8% 8.6%
Mar-1995 0.7% -3.8% -17.6% -13.0% -18.4%
Jun-1995 0.9% -1.0% 19.3% 4.3% 26.8%
Sep-1995 1.2% 4.0% -20.5% -9.2% -31.9%
Dec-1995 1.1% -2.0% 24.9% 79.8% 0.9%
Mar-1996 1.0% 5.9% 6.7% 136.0% -6.0%
Jun-1996 1.0% 0.5% 25.7% 275.0% 17.4%
Sep-1996 0.8% 0.3% -78.6% -307.5% -26.4%
Dec-1996 0.8% -1.8% 35.0% 97.6% 20.4%
Mar-1997 1.0% 0.1% 8.1% 2760.0% -8.9%
Jun-1997 1.2% -4.7% 49.0% 224.7% 4.0%
Sep-1997 1.3% -3.0% -181.2% -128.5% -9.9%
Dec-1997 1.1% -8.8% 25.9% 91.1% 14.9%
Mar-1998 1.0% -0.7% -59.3% -2921.2% -11.2%
Jun-1998 1.3% -5.3% 20.1% 34.1% 14.0%
Sep-1998 1.4% 0.0% -70.7% -200.1% -23.9%
Dec-1998 1.4% 2.3% 24.6% 33.4% 17.3%
Mar-1999 1.0% 1.6% -13.4% -19.9% -10.9%
Jun-1999 0.8% 2.2% -7.7% -17.5% 1.3%
Sep-1999 0.9% -0.8% -16.7% -43.9% -4.1%
Dec-1999 1.2% 0.8% 33.3% 48.6% 15.3%
Mar-2000 1.2% -9.1% -8.2% 14.8% -19.8%
Jun-2000 0.8% -1.5% -1.5% -9.7% 4.3%
Sep-2000 0.1% -10.1% 14.9% 52.0% -8.0%
Dec-2000 -0.1% 5.2% 27.3% 67.3% 18.4%
Mar-2001 0.3% -9.7% 22.0% 403.0% -17.9%
Jun-2001 0.9% 1.5% 24.2% 85.3% -1.2%
Sep-2001 1.2% -0.9% -39.9% -40.1% -5.6%
Dec-2001 1.2% 2.5% -18.9% -102.1% 14.6%
Mar-2002 1.2% 3.5% 4.1% 2728.6% -13.3%
Jun-2002 1.0% 3.5% -48.3% -240.2% -4.0%
Sep-2002 0.8% -0.7% -44.1% -205.7% -15.3%
Dec-2002 0.5% 5.9% -2.1% -35.9% 16.9%
Mar-2003 0.4% 4.6% 1.1% 25.7% -19.6%
Jun-2003 0.8% 8.3% -18.1% -67.1% 9.4%
Sep-2003 1.3% 5.2% -16.4% -20.8% -13.8%
Dec-2003 1.4% 11.1% 10.7% 12.7% 8.4%
Mar-2004 1.1% -3.6% -0.7% 13.6% -14.2%
Jun-2004 0.7% -3.8% 3.7% 4.8% 4.4%
Sep-2004 0.4% 2.5% -40.8% -53.5% -34.3%
Dec-2004 0.5% 4.5% 0.9% -2.6% 4.1%
Mar-2005 0.7% 0.9% 9.5% 30.2% -9.0%
Jun-2005 0.9% -2.8% 18.8% 36.9% 9.4%
Sep-2005 0.9% 0.1% -34.1% -45.7% -31.2%
Dec-2005 0.6% -0.4% 8.0% 17.7% 3.8%
Mar-2006 0.5% -1.8% 4.5% 10.1% 2.4%
Jun-2006 0.6% 2.2% 7.6% 26.0% 2.3%
Sep-2006 0.8% 0.2% -20.5% 16.2% -33.6%
Dec-2006 1.0% 3.7% -1.9% -59.9% 7.7%
Mar-2007 1.2% 5.7% -2.1% 1.5% -2.8%
Jun-2007 1.2% 4.9% 6.6% 3.3% 9.1%
Sep-2007 1.0% 3.7% -26.1% -57.0% -19.9%
Dec-2007 0.8% -1.9% -6.5% -40.0% 7.4%
Mar-2008 0.7% 5.5% 1.4% -4.9% 5.3%
Source: US Federal Reserve, Australian Bureau of Statistics, author
Analysis of data in Table 5.21. prompts to the following conclusions:
change of trade balance is very erratic and correlations between the AUD/USD are
insignificant (smaller than 0.15) for the entire sample and sub-sample
concurrent correlations between the AUD/USD and growth of GDP are significant for the
period from 2000 thru 2008 (0.35) and insignificant for the entire sample (0.10)
differenced (-1) correlations between the AUD/USD and current accounts are significant
for the period from 2000 thru 2008 (-0.35) and insignificant and reversed for the entire
sample (0.10); concurrent correlations are insignificant because date of release of data for
CA lags 2 months; that’s why differenced correlation is used.
correlations between net income and the AUD/USD is insignificant. We used it because
NI has been in recent years a greater contributor to Australian current account deficit
(circa 60% in March 2008), which is totally different from the USA. Australian high yield
attracts foreign investors in fixed income products.
In summary, the above analysis confirms our earlier conclusion about mixed results from betting
on the direction of the currency implied by statistics from foreign trade. However, knowing the
big picture of foreign trade adds to more accurate interpretation of economic forces impacting
FX rates. To that end, let us show statistics about major trading partners and products.
Knowing how the economy of major trading partner(s) is expected to grow is a harbinger for a
shift or continuation of a trend for FX rates. The driver for FX rates movement is not so much
trade surplus or deficit but rather the growth of economies of trading partners. China is pivotal
to Australia, in that regard.
Table 5.22. Australia: major export goods (FOB, AUD mil.)
Food and Metalliferous Coal, coke prod. and (excl.
live ores and and related gold TOTAL Per cent of
animals metal scrap briquettes materials ores) IMPORT TOTAL
Jan-1990 768 470 474 175 233 3684 57.5%
Jan-2007 1282 2616 2009 786 812 12625 59.4%
Feb-2007 1457 2827 1601 779 951 13253 57.5%
Mar-2007 1577 2551 1846 890 793 13929 55.0%
Apr-2007 1397 2995 1759 912 916 13878 57.5%
May-2007 1480 3033 1793 778 1026 14700 55.2%
Jun-2007 1330 2857 1643 905 1111 13861 56.6%
Jul-2007 1444 3124 1587 972 1005 14405 56.5%
Aug-2007 1438 3113 1765 1120 1104 14643 58.3%
Sep-2007 1516 3006 1753 815 796 13740 57.4%
Oct-2007 1406 2788 1632 1120 929 13689 57.5%
Nov-2007 1455 3002 1619 1094 1054 14081 58.4%
Dec-2007 1647 3694 1868 1040 864 15582 58.5%
Jan-2008 1373 3252 1777 1103 1183 13382 64.9%
Feb-2008 1627 2686 1411 1074 1145 13574 58.5%
Mar-2008 1753 3559 1856 1137 964 15401 60.2%
Apr-2008 1881 3551 2296 1132 1242 16214 62.3%
May-2008 2052 3928 2765 1263 886 17293 63.0%
Jun-2008 1717 4113 3588 1259 865 17574 65.7%
Source: Australian Bureau of Statistics and author
Coal, iron ore, food & live animals, crude oil, and gold are major Australia’s export goods.
Those five items have historically contributed at least 50% to total exports; and at present
almost 2/3. Compared to 1990, exports of energy and ores magnified about eight times, gold
slightly less than four times, and food by circa 2.5 times. Equipped with these statistics, we can
utilize it to cause-and-effect analysis. A first noticeable feature is that the major goods are raw
materials and food. In these circumstances, price appreciation of raw materials benefits
Australia. However, if we dig deeper and juxtapose exports with imports, Australia is a net
importer of crude oil. Second, import of gold is also substantial. Consequently, Australia is a
net exporter of food, coal, and ores and benefits if prices for these goods appreciate (AUD
strengthens, ceteris paribus).
Table 5.23. Australia: major export countries and regions (custom value, AUD mil.)
China India Japan Korea NZ Taiwan Thailand UK USA EU 27 % Total
Jan-1990 69 57 879 164 147 101 46 150 351 658 71.2%
Jan-2007 1763 913 2673 1150 614 430 348 320 610 1251 79.8%
Feb-2007 1816 627 2548 1121 725 429 262 734 789 1676 80.9%
Mar-2007 1790 582 2618 1155 788 522 423 463 865 1653 78.0%
Apr-2007 2149 922 2655 980 756 610 308 545 671 1559 80.4%
May-2007 2161 1090 2692 1066 814 509 484 349 944 1499 79.0%
Jun-2007 1884 964 2590 1012 800 510 427 323 868 1350 77.4%
Jul-2007 2012 821 2822 1053 826 528 391 431 831 1522 78.0%
Aug-2007 1770 939 2822 1179 874 542 390 309 857 1324 75.2%
Sep-2007 1837 566 2407 1185 826 455 359 869 798 1852 81.2%
Oct-2007 1932 549 2592 989 843 412 367 978 810 1933 83.3%
Nov-2007 2120 558 2597 1329 866 398 287 1054 944 2022 86.5%
Dec-2007 2558 763 2916 1251 742 603 370 638 1045 1561 79.9%
Jan-2008 2213 796 2450 988 649 392 290 885 675 1653 82.1%
Feb-2008 1695 750 2544 1111 688 505 252 771 844 1628 79.5%
Mar-2008 2575 862 2932 1075 770 634 427 627 884 1593 80.4%
Apr-2008 2454 947 3140 1221 734 654 507 550 848 1619 78.2%
May-2008 2666 908 3389 1159 817 641 443 546 1186 1770 78.2%
Jun-2008 2737 842 3953 1614 805 643 569 657 865 1865 82.8%
Source: Australian Bureau of Statistics and author
APEC (Asia-Pacific Economic Cooperation) countries count for about 80% of Australia’s export.
But in reality we have to take a global view because APEC countries are big exporters to the US
and EU27. The nexus of influence is complex but can be reduced to a statement that an
economic slowdown in any part of the globe affects Australia’s economy negatively (AUD
weakens, ceteris paribus).
Analysis of foreign trade is most beneficial for gaining an educating view on mid-term trend.
Data for trade balances often lags two months and is often overshadowed by other, usually,
(g) New Zealand
Let us face the facts and be realistic here. New Zealand is a tiny country with a population
below 4.3 million and economy ranked around 50 in terms of GDP. The NZD is in the majors
only by tradition not by merits. A statement on Statistic New Zealand’s website
(www.stats.govt.nz/products-and-services/Articles/Australia-Trade-Nov02.htm) best summarizes
foreign trade matters:
Australia is currently New Zealand’s main trading partner in terms of imports and exports of
goods and services. Australia is also the key destination and source when it comes to direct
investment. Japan, the United States of America (USA), the European Union (EU) and the
Association of South East Asian Nations (ASEAN) are also important economic partners for
Characteristics of New Zealand foreign trade resemble in many ways that of Australia. The ratio
of current account to GDP picked in March 2006 with the value of 9.3%. Current accounts have
been negative for over a decade. Like for Australia, negative Net Income is also a major
contributor to CA deficit.
Major exporters: importers:
Australia counts for over 20% of imports and exports. No wonder that the AUD and NZD are
strongly correlated. Trading the NZD/USD without giving consideration to the AUD/USD pair is
Dairy and meat are most important export goods, followed by wood and aluminum. Mineral
fuels (crude oil), machinery, vehicles, electrical machinery, and plastics contribute most to
imports. The weather conditions can be very influential to the value of NZD (that also goes for
the AUD) because agricultural products are important components of trade.
Table 5.24. Trade balance for selected countries.
2006 2007 2008 2009 Change, bil. USD
Australia -41.06 -57.42 -45.58 -40.35 0.71
Austria 9.11 13.17 13.22 2.35 -6.76
Belgium 7.93 7.29 -14.8 2.52 -5.41
Canada 17.92 14.53 7.6 -36.19 -54.11
Czech -3.42 -5.57 -1.34 -1.94 1.48
Denmark 8.18 4.59 7.45 12.37 4.19
Finland 9.48 10.34 8.14 3.29 -6.19
France -11.55 -25.84 -64.35 -56.46 -44.91
Germany 188.41 253.44 244.11 165.42 -22.99
Greece -29.72 -44.93 -50.91 -37.17 -7.45
Hungary -8.05 -9.04 -10.91 0.22 8.27
Iceland -4.09 -3.29 -3.62 -0.42 3.67
Ireland -7.86 -13.84 -14.21 -6.48 1.38
Italy -48.13 -51.63 -78.36 -69.53 -21.40
Japan 168.41 211.37 158.42 141.01 -27.40
Korea 5.39 5.88 -5.78 42.67 37.28
Luxembourg 4.41 4.98 3.07 2.96 -1.45
Mexico -4.45 -8.4 -15.89 -5.24 -0.79
Netherlands 63.31 67.5 41.7 42.6 -20.71
New Zealand -9.11 -10.47 -11.2 -3.42 5.69
Norway 58.38 54.71 83.71 12.58 -45.80
Poland -9.39 -20.25 -26.91 -7.21 2.18
Portugal -19.37 -20.88 -29.18 -23.4 -4.03
Slovakia -4.39 -4 -6.19 -0.66 3.73
Spain -110.85 -144.1 -154.94 -79.4 31.45
Sweden 31.26 38.06 45.45 29.43 -1.83
Switzerland 59.52 39.03 10.23 41.12 -18.40
Turkey -32.22 -38.27 -41.53 -13.61 18.61
UK -80.68 -75.46 -40.24 -28.74 51.94
US -803.55 -726.57 -706.07 -419.87 383.68
Euro zone -12.81 14.58 -209.47 -79.29 -66.48
OECD-Total -596.18 -535.06 -698.91 -160.07 436.11
Brazil 13.62 1.55 -28.19 1.97 -11.65
China 253.27 371.83 426.11 162.86 -90.41
India -9.51 -10.69 -37.23 4.22 13.73
Indonesia 10.86 10.49 0.13 2.02 -8.84
Russia 94.69 77.77 103.72 48.97 -45.72
South Africa -16.12 -20.78 -20.98 -4.09 12.03
Source: OECD, author
Table 5.24. shows that the U.S. was the greatest beneficiary of correction of trade imbalance in
2009 compared to 2006; the ironic benefit of recent financial crisis.
5.6. Compilation of releases
In proceeding sections we described many macroeconomic statistics that influence FX rates.
It’s time to put all important releases for a given country together. Analysis is arranged along
four major categories GDP, inflation, employment, and forecasts. A particular release is put into
one of the four categories, though some releases contain multiple statistics.
In Event Studies is a detailed description how to proceed with releases. Key questions to ask:
1. Are expectations better or worse from the previous period? We can trade on expectations.
2. What does the level of expectations indicate? Conditions may improve or deteriorate but still
be at a mid –term trend. Reaction thus in those circumstances be corrective. Most volatile are
situations when the release changes the current believes market participants formed.
Reasoning is simple here: from better to worse or from worse to better.
3. How big is the difference between the actual figure and the expectations? Principally, we
have to evaluate an element of surprise against how much is already priced into FX rates.
Trading within first five minutes the statistics are released is, by and large, a haphazard
endeavor. FX rates often move in a direction opposed to the common wisdom indicated by
rational reasoning of cause-and-effect. Reaction to a headline figure can be reversed after a
careful reading of the entire release (1-3 minutes). Much more is described in Event Studies.
Let us stress a few main points. Trading on expectations before the time statistics is released
is, by and large, the safest way to make profit. We have to be aware of other events at or near
the time of the release. We have to truly know fundamentals to fully utilize information
contained in releases. The reality is that FX rates move largely because of macroeconomic
factors. Big players trade currencies based on macroeconomic fundamentals – why not us?
GDP http://www.bea.gov/national/index.htm#gdp –releases, forecasts: www.federalreserves.gov. www.oecd.org,
Chicago PMI: www.kingbiz.com/library.asp
ISM Manufacturing www.ism.ws/ISMReport/index.cfm >> Latest Manufacturing
ISM Non-manufacturing www.ism.ws/ISMReport/index.cfm >> Latest Non-Manufacturing
Advance Retail Trade www.census.gov/marts/www/marts.html
Personal income & outlays www.bea.gov/newsreleases/national/pi/pinewsrelease.htm
Housing: Permits, New Home Sales www.census.gov/const/www/newresconstindex.html
Industrial Production & Capacity Utilization http://federalreserve.gov/releases/g17/current
Durable Goods Orders www.census.gov/ftp/pub/indicator/www/m3/index.htm
Beige Book (GDP and inflation) www.federalreserve.gov/FOMC/BeigeBook
Average workweek (inflation, GDP)
U of M Consumer Confidence www.sca.isr.umich.edu/
Testimonies before US Congress www.federalreserve.gov
ISM Semiannual Economic Forecast www.ism.ws
Empire State Manufacturing Survey www.newyorkfed.org/survey/empire/empiresurvey_overview.html
Interest Rates www.federalreserve.gov/FOMC
Real growth of GDP.
It measures the health of the economy. There is a direct and strong relationship between the
currency and GDP. Improving GDP strengthens domestic currency. Bureau of Economic
Analysis releases GDP data three times: advance (about four weeks after the quarter’s end)
preliminary (about eights weeks), and final (about twelve weeks after the quarter’s end). Most
volatile is an advance release because of greater uncertainty and it’s the soonest. Though the
participants in capital markets have already a good picture of the economy in past three months
from a slew of monthly releases, confirmation of expectation of the growth of GDP is of utmost
importance and a market shaker.
Below chart shows percentage change in GDP from a year ago. This is different from
annualized quarterly change in real GDP – the common number market is looking for in the
Let us introduce to the following concept: assign a rank to a value of a macroeconomic data
from 1 to 10. For the period from mid 1980s till present, minimum rate of growth of GDP was
1.0% and maximum 8.5%.
1 2 3 4 5 6 7 8 9 10
-0.05 0.90 1.85 2.79 3.74 4.69 5.64 6.59 7.54 8.49
For example, an annual change of 1.5% would be ranked 3. Ranking gives us a sense of
relative standing of the data. It gives us an answer to: Is the 1.5% growth average, anemic or
strong? 1.5% could be below average for the US but respectable for the EZ.
Critical to a proper interpretation is an assignment of maximum and minimum values from the
range. One may argue, rightfully so, that 8.5% is too high for the environment of past decade.
Years from 1980-82 were abnormal that policymakers fight to avoid. Policymakers desire to
have a steady growth GDP, ideally without overheating and of course inflation. Ranking for the
maximum of 5% would look as follows:
1 2 3 4 5 6 7 8 9 10
-0.05 0.25 0.80 1.40 2.00 2.60 3.20 3.80 4.40 5.00
A growth above 2% would be deemed above average. Median for the period in our case was
3.2%. But that what it was. Intuitively, ranks smaller than 5 indicate below average standing,
ranks 5-6 oscillate around the average, and 7 thru10 points to robust growth. Position traders
can take expectations of GDP in each currency pair and quantify possible trend, E[GDPEZ] -
A lot is already priced in the value of the USD based on expectations of GDP at the time of the
release. So what really counts is how much expectations match the actual number relative to
already priced rates. Sometimes traders wait for the number to be confirmed and rates do not
change so much prior to the release. At other times, rate movements can be exaggerated.
Also traders think what lies ahead not what is behind (past GDP).
The figure is commonly reported in headlines as an annualized percentage, based on quarterly
data. Current dollars are nominal dollars. These are actual amounts unadjusted for inflation.
Real GDP is presented in chained dollars and adjusted for many aspects of inflation such as a
representative basket of goods and quality of goods.
Time: 8:30 am EST
FX: playing GDP before the time of release based on expectations yields most reliable
strategies and profits.
Below description is taken from Briefing.com. Chicago PMI Monthly measure of the business
conditions based on surveys of purchasing managers across Illinois, Indiana and Michigan.
Released on the last business day of the reporting month, the report's significance has recently
declined, with its only significance being that it precedes the more anticipated ISM report.
Subsequently, it is used to predict the ISM report as the Chicago survey retains a high correlation
with the broader economic release.
Referring to a benchmark of 50, the report is considered to reflect expansion when printing a reading
of 50 or higher. Conversely, a reading of 49 and lower would be indicative of contraction.
The ISM-Chicago Business Survey provides a proven ‘first look’ at business, government and NGO economic activity
in the USA. Released monthly, generally on the last working day, the ISM-Chicago Business Survey characterizes
expanding or contracting USA economic activity.
The survey panel is focused on Purchasing / Supply professionals, primarily drawn from the membership of the
Institute for Supply Management - Chicago. The survey of Business Activities and Business Policy includes global
non-manufacturing as well as manufacturing activities of the responding companies.
The ISM-Chicago Monthly Business Survey consists of seven Business Activity series (+, same, –; raw and
seasonally adjusted indexes):
Since the early 70’s, the Buying Policy series provide a monthly measure of lead times for three major categories of
products. Average days required to source Production Materials, MRO Supplies, and Capital Equipment provide
unique insight into economic activity:
Each series represents the level of activity (for the proportion of the survey responding) compared to the prior month.
As such, this survey provides measure of the pervasiveness of changes in economic activity, but does not provide an
estimate of the magnitude of either advances or declines. The composite Business Barometer provides an overall
gauge of business activity.
The Chicago Business Barometer is computed from five weighted raw indexes (see series and weights below) and
then seasonally adjusted to support month-to-month comparisons:
New Orders 0.35
Order Backlog 0.15
Supplier Deliveries 0.15
Category DEC Nov Oct Sep Aug
Chicago PMI 34.1 33.8 37.8 56.7 57.9
New Orders 29.4 27.2 32.5 53.9 60.2
Production 31.7 34.3 30.9 71.4 63.4
Employment 39.6 33.4 41.5 49.1 39.2
Prices Paid 30.5 50.7 53.7 80.7 80.6
The Chicago PMI has little overal economic value, and is only watched by the financial markets because it is
usually released one day in advance of the similar national ISM manufacturing survey. A significant move in
this regional survey will therefore sometimes be seen as having predictive value for the ISM index.
Time: 10:00 AM (EST); monthly, on the final business day of the reporting month
FX: Chicago PMI is strongly correlated to the national ISM and is released a day before. We
can thus compare actual Chicago PMI with expected national ISM and form an educated guess.
Chicago PMI is not a strong market mover on its own. On the day of the release, my suggestion
is to incorporate it with other developments in the markets. The European session is a starting
point to juxtapose Chicago PMI against ISM. Betting on expectations of ISM if there is a
divergence between these two indices should be avoided. Another words, do nothing.
However, when Chicago PMI reinforces expectations of IMS, we can bet on directional
movements, per recommendations in a section describing ISM.
The Institute for Supply Management ISM Manufacturing Report on Business is considered
by many economists to be the most reliable near-term economic barometer available. ISM
Manufacturing assesses the state of US industry by surveying executives on expectations for
future production, new orders, inventories, employment and deliveries. Though manufacturing
accounts for a relatively small portion of GDP, fluctuations in manufacturing tend to bear the
most responsibility for changes in GDP. Consequently, developments in manufacturing often
front run trends in the overall economy, making the ISM Manufacturing figure a leading indicator
of economic turnarounds. A pickup in demand for manufactured products after a period of
recession, reflected by a higher ISM figure, strongly suggests a reversal upward. Conversely a
slowdown in manufacturing orders and production during a boom suggests a slowing of the
Below is a typical content of the survey:
MANUFACTURING AT A GLANCE
Series Series Percentage Rate
Index Index Point of Trend*
Index December November Change Direction Change (Months)
PMI 32.4 36.2 -3.8 Contracting Faster 5
New Orders 22.7 27.9 -5.2 Contracting Faster 13
Production 25.5 31.5 -6.0 Contracting Faster 4
Employment 29.9 34.2 -4.3 Contracting Faster 5
Supplier Deliveries 44.9 48.4 -3.5 Faster Faster 3
Inventories 38.8 39.1 -0.3 Contracting Faster 6
Customers' Inventories 57.0 55.0 +2.0 Too High Faster 5
Prices 18.0 25.5 -7.5 Decreasing Faster 3
Backlog of Orders 23.0 27.0 -4.0 Contracting Faster 8
Exports 35.5 41.0 -5.5 Contracting Faster 3
Imports 39.0 37.5 +1.5 Contracting Slower 11
OVERALL ECONOMY Contracting Faster 3
Manufacturing Sector Contracting Faster 5
Source: The Institute for Supply Management
The headline figure is expressed as a diffusion index based on survey responses. For each
category (production, new orders etc.), the index is calculated by adding the percentage of
executive responding "higher" with half the percentage of "no change" responses, and
subtracting the percentage of "lower" responses.
In February 1992, the PMI was developed by the U.S. Department of Commerce (DOC) and
ISM. The index, based on analytical work by the DOC, adjusts five components of the Institute's
monthly survey — new orders, production, employment, supplier deliveries and inventories —
for normal seasonal variations, applies equal weights to each and then calculates them into a
single monthly index number. Values over 50 generally indicate an expansion, while values
below 50 indicate contraction.
The survey contains, besides the headline figure, many valuable pieces of information. Price,
Employment, and New Orders are among most analyzed. They indicate the most likely
direction of near-term inflation (via Prices) and economic growth (via New Orders, Supplier
Deliveries). It is critical to read the report in its entity immediately it becomes available to get
insights beyond the PMI Index. The overall index may, say, improve, but there could be
divergence between inflationary pressure and growth of economy (the index has about 60%
explanatory power in predicting variations in GDP).
Time: 10:00 AM EST; monthly, first business day after reporting month
Web: http://www.ism.ws/ISMReport/index.cfm & Latest Manufacturing ROB
FX: The release is a market shaker for two reasons. First, it is robust in terms of predicting the
near-term growth of economy and provides direction on inflation. Second, the release is the
timeliest out of all major releases. We can make bets on expectations of the release – as
described in Event Studies. Again, it is critical to read the survey immediately after it is
Since 1980, the index peaked at 69.9 in December 1983 and dived to 29.4 in May 1980. And
as of February 2009, the index has been at the bottom range indicating severe recession. Most
reasonable trades that are triggered by US releases are bets on currencies of the countries that
rely on export, Japan, Canada, Australia, and New Zealand. Growing US economy implies
growing export of these countries and strengthening of their currencies.
The Non-Manufacturing ISM Report on Business is released on the third business day of
each month, and is based on data compiled from monthly surveys sent to more than 375
purchasing executives working in the non-manufacturing industries across the country. Each
month, these survey responses reflect change, if any, in the current month's report compared to
the previous month. The report covers Business Activity, New Orders, Backlog of Orders, New
Export Orders, Inventory Change, Inventory Sentiment, Imports, Prices, Employment and
Beginning with the January 2008 Non-Manufacturing Report on Business, a composite index
is calculated as an indicator of the overall economic condition for the non-manufacturing sector.
The NMI is a composite index based on the diffusion indexes for four of the indicators with equal
weights: Business Activity (seasonally adjusted), New Orders (seasonally adjusted),
Employment (seasonally adjusted) and Supplier Deliveries.
Below is a snapshot of historical data for major components of the NMI and the total index.
NMI (Non-Manufacturing Index) Summary
The NMI was released for the first time beginning with the data for Jan. 2008
BUSINESS ACT. NEW ORDERS EMPLOYMENT SUPPLIER DEL. NMI
H S L I H S L I H S L I H S L I Index
Jan-08 18 40 42 41.9 18 46 36 43.5 6 70 24 43.9 8 82 10 49.0 44.6
Feb-08 26 47 27 50.8 24 50 26 49.6 14 63 23 46.9 7 86 7 50.0 49.3
Mar-08 30 50 20 52.2 25 52 23 50.2 14 66 20 46.9 7 84 9 49.0 49.6
Apr-08 29 53 18 50.9 26 57 17 50.1 22 61 17 50.8 17 78 5 56.0 52.0
May-08 32 50 18 53.6 29 56 15 53.6 18 68 14 48.7 10 82 8 51.0 51.7
Jun-08 28 52 20 49.9 24 55 21 48.6 13 68 19 43.8 8 85 7 50.5 48.2
Jul-08 24 51 25 49.6 20 56 24 47.9 19 60 21 47.1 15 77 8 53.5 49.5
Aug-08 23 53 24 51.6 24 51 25 49.7 13 62 25 45.4 16 79 5 55.5 50.6
Sep-08 23 53 24 52.1 20 57 23 50.8 13 60 27 44.2 11 85 4 53.5 50.2
Oct-08 20 47 33 44.2 18 50 32 44.0 9 61 30 41.5 6 84 10 48.0 44.4
Nov-08 9 48 43 33.0 9 52 39 35.4 5 52 43 31.3 6 87 7 49.5 37.3
Dec-08 17 40 43 39.6 17 40 43 39.9 9 51 40 34.7 8 80 12 48.0 40.6
H: Higher; S: Same; L: Lower; I: Index
Source: The Institute for Supply Management
Time: 10:00 AM EST; monthly, third business day after reporting month
Web: http://www.ism.ws/ISMReport/index.cfm & Latest Non-manufacturing ROB
There are 10 separate indexes reported, but Business Activity is considered the most important.
The other nine indexes are: New Orders, Supplier Deliveries, Employment, Inventories, Prices,
Backlog of Orders, New Export Orders, Imports, and Inventory Sentiment.
FX: Reaction of markets to this survey is less volatile because it is released two days after the
manufacturing survey. However, this is a very insightful survey because services constitute a
much greater portion in GDP than manufacturing. It is useful to juxtapose the Non-
manufacturing survey with the Manufacturing survey to see divergence or congruence. Betting
on this release should be selective because (a) it’s not so much volatile and (b) numbers are
likely to be already priced into FX rates after the Manufacturing release.
Advance Retail Trade
Formal name of the release is Advance Monthly Sale for Retail Trade and Food Services.
The purpose of this voluntary survey is to provide an early indication of monthly sales of retail
and food service companies. Retail sales count for about one-third of total consumer
consumption. This is a harbinger of the health of economy since consumer consumption is a
major component of GDP. Consequently, the release shakes capital markets.
Numbers are volatile on a monthly basis because of seasonality and often markedly revised.
Averaging provides more reliable conclusions. Data is adjusted for seasonality but not price.
Capital markets put more weight to the survey that excludes very volatile sales of autos. Let us
examine major component of the survey.
Retail & Auto & Bldg. & Auto & Bldg.
YEAR Food parts mater. Food parts mater.
in $, millions percent change
1992 2,012,525 418,407 130,880
1993 2,156,361 474,239 141,196 7.1% 13.3% 7.9%
1994 2,333,841 543,078 157,307 8.2% 14.5% 11.4%
1995 2,459,093 582,530 165,413 5.4% 7.3% 5.2%
1996 2,603,243 627,261 176,283 5.9% 7.7% 6.6%
1997 2,734,377 656,213 191,342 5.0% 4.6% 8.5%
1998 2,860,333 690,232 202,682 4.6% 5.2% 5.9%
1999 3,091,512 765,536 218,758 8.1% 10.9% 7.9%
2000 3,290,026 796,973 229,996 6.4% 4.1% 5.1%
2001 3,386,036 817,385 239,048 2.9% 2.6% 3.9%
2002 3,467,150 819,709 248,542 2.4% 0.3% 4.0%
2003 3,614,120 840,748 264,705 4.2% 2.6% 6.5%
2004 3,832,862 862,238 297,259 6.1% 2.6% 12.3%
2005 4,078,592 884,770 327,274 6.4% 2.6% 10.1%
2006 4,313,695 901,480 345,834 5.8% 1.9% 5.7%
2007 4,495,885 927,054 337,241 4.2% 2.8% -2.5%
2008 4,476,513 811,236 323,866 -0.4% -12.5% -4.0%
This is the first year since 1992 when retail sales dropped on an annual basis. The auto
industry has suffered immensely in 2008. Sales dropped in nominal dollars by over $110
billions and are on levels that existed eight years ago. Sales in Building Materials also suffered
but decrease is not as much severe as the plight in real estate would indicate. This is because
of impact of remodeling activities. Negative growth in the overall retail sales of -0.4% correlates
with recession the US has been in past months.
Time: 8:30 am EST, circa two weeks after the reporting month's end.
Impact on FX. Growing retail sales strengthen the USD. The safest bet is to buy the USD/JPY
and USD/CAD in these circumstances and sell these pairs when numbers shows deteriorating
conditions. Countries that rely on export to USA.
Personal Income and Outlays
Personal Income and Expenditures.
Personal Income and Expenditures are components of one report Personal Income and Outlays
by Bureau of Economic Analysis. These three elements are not market shakers but are
important to gauging a view on the health of economy.
Personal Income measures the pre-tax income households receive from employment,
investments, and transfer payments. As wages and salaries make up the majority of Personal
Income, the figure can provide insight on the US employment situation. However, because
Personal Income is released after the headline employment figure and earnings figures, its
impact on the market is muted. The figure is still useful in gauging the purchasing ability of
consumers, though, as rising Disposable Personal Income allows for strong consumers
spending and growth of US economy.
Personal Consumption Expenditures (spending) is a comprehensive measure of how much
consumers spend each month, counting expenditures on durable goods, consumer products,
and services. Personal Consumption is a greatest component (about 70%) of GDP. The
impact on GDP is therefore very direct.
PCE is particularly valued for forecasting inflationary pressures as consumption relates to
demand and demand to price levels. The Fed uses a measure of inflation derived from the
PCE as their primary gauge of inflation.
Personal Spending (when reported as a percent of income rather than the headline percent
change) has an inverse relationship to personal saving. Economists watch the growth of
Personal Spending in relation to income and saving to determine if consumers are living beyond
their means, which would influence levels of borrowing and future consumption.
Disposable personal income (DPI) = personal income - personal current taxes
Personal outlays = PCE + personal interest payments + personal current transfer payments
Personal saving = DPI - personal outlays
PCE Deflator is a measure of inflation based on changes in personal consumption. Unlike the
CPI, which is based on a fixed basket of goods, the Personal Consumption Expenditures (PCE)
Deflator finds the average increase in prices for all domestic personal consumption. PCE
Deflator has been shown to be a more comprehensive and consistent gauge of inflation in the
US. The CPI and PCE Deflator do not differ much. The CPI tends to overstate inflation and the
PCE understates it.
Time: 8:30 AM EST; monthly, four-five weeks after the reporting month
FX: PCE Deflator puts most weight on the PERSONAL INCOME AND OUTLAYS report. The
impact on the USD is very robust and direct: growing inflation strengthens the USD across all
pairs. We can count on increased volatility and make bets according to expectations contingent
on how much expectations are already priced in FX rates.
The Building Permits Survey produces estimates of the number of permits issued for new
housing units each month. This is done through a mail survey of a sample of permit offices.
Permit offices not in the monthly sample report annual numbers at the end of each year.
Monthly data for States, Regions, and the U.S. are weighted sample based estimates reflecting
the total building permit universe.
2500 2 to 4
Source: U.S. Census Bureau 1/1/09
Building Permit Survey is the first harbinger in the construction process from which we can infer
the health of real estate market on the national scale. Housing Starts is an additional survey but
it’s lagging. The relationship is rather straightforward. More homes means more spending on
durable goods and growing economy.
The release is seldom a market shaker. Nonetheless, it’s a good inference on contribution of
real estate to the economy in the coming months. Given the current housing crisis, the survey
is very valuable in predicting a turn from inflation toward recovery. The current numbers of
permits point to nothing less but to a dismal situation.
Time: 8:30 am EST, 2-3 weeks after the reporting month
Impact on FX. It’s best to play the release indirectly via impacts on stock market. If futures on
SP500 respond negatively to release, selling the USD/JPY and USD/CAD can be a profitable
trade, contingent on the whole host of other parameters such as rates level and pending
releases of greater importance. It’s beneficial to incorporate this release with other releases to
have better picture of potential impact.
Industrial Production & Capacity Utilization
These two statistics are released at the same time and with the same survey. The industrial
production (IP) index measures the real output of the manufacturing, mining, and electric and
gas utilities industries; the reference period for the index is 2002. Manufacturing consists of
those industries included in the North American Industry Classification System, or NAICS,
definition of manufacturing plus those industries–logging and newspaper, periodical, book and
directory publishing–that have traditionally been considered to be manufacturing and included in
the industrial sector. For the period since 1997, the total IP index has been constructed from
303 individual series based on the 2002 North American Industrial Classification System
(NAICS) codes. These individual series are classified in two ways: (1) market groups, and (2)
industry groups. Market groups consist of products and materials. Total products are the
aggregate of final products, such as consumer goods and equipment, and nonindustrial supplies
(which are inputs to nonindustrial sectors). Materials are inputs in the manufacture of products.
On a monthly basis, the individual indexes of industrial production are constructed from two
main types of source data: (1) output measured in physical units and (2) data on inputs to the
production process, from which output is inferred. Data on physical products, such as tons of
steel or barrels of oil, are obtained from private trade associations and from government
agencies; data of this type are used to estimate monthly IP wherever possible and appropriate.
The aggregation method for the IP index is a version of the Fisher-ideal index formula. (In the IP
index, series that measure the output of an individual industry are combined using weights
derived from their proportion in the total value-added output of all industries. Needless to say,
aggregation of data and estimates present a challenge.
Industrial Production, annual change
For a given industry, the capacity utilization (CU) rate is equal to an output index (seasonally
adjusted) divided by a capacity index. The Federal Reserve Board's capacity indexes attempt
to capture the concept of sustainable maximum output – the greatest level of output a plant can
maintain within the framework of a realistic work schedule, after factoring in normal downtime
and assuming sufficient availability of inputs to operate the capital in place. The Federal
Reserve Board constructs estimates of capacity and capacity utilization for industries in
manufacturing, mining, and electric and gas utilities.
INDUSTRIAL PRODUCTION AND CAPACITY UTILIZATION: SUMMARY
2002=100 Percent change
2008 2008 Dec. '07 t
Industrial production July[r Aug.[r Sept.[r Oct.[r Nov.[r Dec.[p July[r Aug.[r Sept.[r Oct.[r Nov.[r Dec.[p o
] ] ] ] ] ] ] ] ] ] ] ] Dec. '08
Total index 111.2 109.8 105.2 107.1 105.7 103.6 .0 -1.3 -4.2 1.8 -1.3 -2.0 -7.8
Previous estimates 111.3 109.8 105.2 106.8 106.1 .0 -1.3 -4.1 1.5 -.6
Major market groups
Final Products 112.2 110.5 107.4 108.6 108.4 107.3 -.3 -1.6 -2.7 1.1 -.2 -1.0 -5.4
Consumer goods 106.1 103.8 102.3 104.6 103.6 101.8 -.1 -2.1 -1.5 2.3 -1.0 -1.7 -5.2
Business equipment 129.8 129.3 119.9 116.8 120.2 122.4 -.4 -.4 -7.3 -2.6 2.9 1.8 -6.7
Nonindustrial supplies 105.9 105.0 102.4 102.7 100.2 97.7 .1 -.8 -2.5 .4 -2.5 -2.5 -9.2
Construction 102.0 101.0 98.7 97.3 92.8 89.7 .7 -.9 -2.2 -1.4 -4.6 -3.4 -14.0
Materials 112.2 110.9 104.2 107.3 105.2 102.3 .1 -1.2 -6.0 3.0 -2.0 -2.8 -9.6
Major industry groups
Manufacturing (see note below
111.9 110.8 106.4 107.4 105.0 102.5 -.2 -1.0 -3.9 .9 -2.2 -2.3 -9.9
Previous estimates 111.9 110.8 106.3 107.0 105.5 -.1 -1.1 -4.0 .6 -1.4
Mining 105.8 105.2 95.2 102.3 104.5 102.9 1.5 -.5 -9.5 7.4 2.2 -1.6 -1.0
Utilities 108.9 103.9 105.5 107.8 108.8 108.7 -1.0 -4.6 1.6 2.1 1.0 -.1 .4
Percent of capacity growth
Average 1988- 1990- 1994- 2001-
1972- 89 91 95 02 2007 2008 Dec. '07 to
2007 high low high low Dec. Dec. '08
July[r] Aug.[r] Sept.[r] Oct.[r] Nov.[r] Dec.[p]
Total industry 81.0 85.0 78.6 85.1 73.6 81.0 79.4 78.3 75.0 76.3 75.2 73.6 1.5
Previous estimates 79.5 78.3 75.0 76.0 75.4
Manufacturing (see note below) 79.7 85.4 77.1 84.6 71.5 79.2 77.1 76.2 73.1 73.7 71.9 70.2 1.7
Previous estimates 77.1 76.2 73.1 73.4 72.3
Mining 87.5 86.3 83.6 88.7 84.8 90.9 92.1 91.6 82.9 88.9 90.8 89.3 .7
Utilities 86.8 92.7 84.1 93.9 84.6 85.5 84.9 80.9 82.0 83.6 84.3 84.0 2.2
Crude 86.6 88.3 84.4 89.5 81.9 90.2 89.8 89.3 79.3 85.7 85.7 83.9 .5
Primary and semifinished 82.2 86.4 77.8 88.2 74.6 81.0 79.2 77.8 75.3 76.5 74.1 72.1 1.8
Finished 77.7 82.8 77.1 80.4 69.9 77.7 75.7 74.7 73.0 72.4 72.4 71.4 1.8
Source: Federal Reserve
Relationship of the IP and CU on GDP is direct. Growing numbers indicate growing economy.
Graphs are quite reviling, especially for recessionary periods.
Time: 9:15 AM EST; about 15-18 days after the end of reporting month
FX: On the day of the release, these statistics typically are not market shakers, if so mildly.
However, they are quite useful to making inference about GDP and inflation. CU above 82%
exerts inflationary pressure and thus serves as an indicator to Fed’s bias toward raising the fed
rates. Utilization of these releases fit the general procedures of event studies. Key issues are
expectations and how much is already priced into FX rates before the release time.
Durable Goods Orders
Durable goods are those whose intended lifespan is three years or more. They are natural
component of the GDP. The more autos, electronics, appliances are produced, the greater
growth of GDP follows, ceteris paribus.
Durable goods orders is a component of monthly survey M3: Manufacturer’s Shipments,
Inventories, and Orders. Nearly all manufacturers that sale more than $500 MM goods
annually participate in the survey; and a sample of smaller companies.
We have to look at the whole picture, the three components,
and individual series. Shipments represent net sales measured in
dollar value of products sold by manufacturers based on net selling
Manufacturers value, f.o.b. So this is a past data.
Inventory is a total value of inventories at cost at the end of month, regardless of the state of
fabrication. New Orders reflects intentions to buy for immediate or future delivery. The data is
forward looking. That’s why it is most valuable to capital markets.
There are a few scenarios that are dictated by relative relationship between these three
components. The best scenario for growth is when both New Orders and Shipment improved.
Data is highly volatile on a monthly basis. In terms of impact on the GDP, we have to look at
averages from at least three past months. Also, revisions are large. Initial reaction to the
release may therefore not follow thru after a deeper scrutiny.
Individual components of the release also play a big role in interpreting potential lasting impact
on the growth of economy. Big items such as aircrafts and defense can skew the whole picture
and real standing of the manufacturing sectors. It is useful then to analyze components of the
release. Nondefense capital goods, for example, are a very good proxy for producers’ durable
equipment in the itemized components of GDP.
I would avoid holding a position at the instant of the release. It’s too risky. After the release, I
would analyze the whole report instead of just one number to which markets react initially.
Movement of the DJ30 index is a good indicator for the USD/JPY pair. They often parallel each
other. Given that the data is often revised markedly, I would not bet on a strong continual trend
during the session. I’d ponder to make a reverse trade after a substantial move. Next potential
trade is when the FX rates move in the opposite direction as indicated by the release. I would
enter a trade in the direction of fundamentals, contingent on the movement of the rates prior to
the release and support/resistant levels. The only trade I would make in the initial direction of
the reaction is when expectations missed markedly actual numbers. But often rates are
zigzagging sharply minutes after the release. It’s safer to wait for rates to settle and then act
per fundamentals and technical indicators – that’s a general recommendation regardless of the
Below are codes for aggregate series in the release. It is clearer that there is more to the data
than just durable goods. Total Manufacturing includes durable and nondurable goods.
MTM Total Manufacturing
MXT Manufacturing Excluding Transportation
MXD Manufacturing Excluding Defense
MTU Manufacturing with Unfilled Orders
MDM Durable Goods
CMS Construction Materials and Supplies
ITI Information Technology Industries
CRP Computers and Related Products
MVP Motor Vehicles and Parts
TCG Capital Goods
NDE Nondefense Capital Goods
NXA Nondefense Capital Goods Excluding Aircraft
DEF Defense Capital Goods
COG Consumer Goods
CDG Consumer Durable Goods
CNG Consumer Nondurable Goods
DXT Durable Goods Excluding Transportation
DXD Durable Goods Excluding Defense
Analysis of data does not point to seasonality, for the aggregate series like MTM; tough
some industries may be prone to cyclicality. Narrow series can be utilized for analyzing
specific industries like computers or construction materials.
Time: 8:30 am EST around the 26th of the month and is for the prior month.
FX: How to play this release? It takes time to digest data before participants in capital markets
digest the release and decide on longer term implications, up or down. Initial reaction might
thus be premature. A few hours before the release, we can trade on expectations. If the
forecast indicates stronger change and the pairs move excessively in either direction, we can
expect reversal of the pairs. The strategy follows a general framework based on the premise
that the actual release may differ markedly from expectations. The pairs tend to move toward
more neutral levels (e.g., RSI about 50 on 15’ chart) with some bias toward expectations.
Per Federal Reserve,
The Beige Book, more formally called the Summary of Commentary on Current Economic Conditions, is a report
published by the Federal Reserve Board eight times a year. Each is a gathering of "anecdotal information on
current economic conditions" by each Federal Reserve Bank in its district from "Bank and Branch directors and
interviews with key business contacts, economists, market experts, and other."
Below is a release from January 14, 2009:
Overall economic activity continued to weaken across almost all of the Federal Reserve Districts since the previous
reporting period. Most Districts noted reduced or low activity across a wide range of industries, although a few
Districts noted some exceptions in some sectors.
District reports indicate that retail sales were generally weak, particularly during the holiday season. A majority of
Districts noted deep discounting during the holiday sales season. Vehicle sales were also weak or down overall in
the Districts reporting on them. Manufacturing activity decreased in most Districts. Declines were noted in a wide
range of manufacturing industries, with a few exceptions. Services sector activity generally declined across the
Districts, with exceptions in some sectors of the Boston, Richmond, and Chicago Districts. Additionally, several
Districts noted weaker conditions in transportation services and slow or decreased demand in tourism activity.
Conditions in residential real estate markets continued to worsen in most Districts. Reduced home sales, lower
prices, or decreases in construction activity were noted in many Districts. Commercial real estate markets
deteriorated in most Districts, with weakening construction noted in several Districts. Overall lending activity
declined in several Districts, with tight or tightening lending conditions reported in most Districts. Credit quality
remained a concern in several Districts. Agricultural conditions were mixed in response to varying weather
conditions across the Districts. Mining and energy production activity generally declined since the previous report.
Most Districts reported a general weakening of labor market conditions. Lower energy prices were noted in many of
the Districts, and, except for the Richmond District, which mentioned higher prices for raw materials, most
reporting Districts noted declining input prices. Wage pressures remained largely contained, and some Districts
reported pay freezes or reductions in compensation.
Reports of retail sales during the holiday season were generally negative in most Districts. Retail sales during the
holiday season were weak or mostly down in the Boston, New York, Philadelphia, Atlanta, Chicago, St. Louis,
Minneapolis, Kansas City, Dallas, and San Francisco Districts. However, some contacts in the Boston and New
York Districts noted that sales picked up after the holidays. Retail sales in the Cleveland District were flat to down
in November (on a month-over-month basis). Most retailers in the Richmond District had disappointing sales during
the holiday season. Discount stores fared relatively better in the Philadelphia, Cleveland, Atlanta, Chicago, and San
Francisco Districts, although discount stores in the Dallas District reported weak holiday sales. Deep discounting
during the holiday season was reported in the New York, Philadelphia, Atlanta, Chicago, Minneapolis, Kansas City,
Dallas, and San Francisco Districts. Several Districts reported that luxury and big-ticket items (e.g., jewelry,
appliances, and electronics) were weak sellers. Richmond reported that sales of gift cards were weaker than the
previous year. In the New York District, cold-weather apparel was a relatively strong seller. Many retailers in the
Philadelphia, Atlanta, Kansas City, and Dallas Districts expected continued weakness or sluggish sales. However,
expectations were mixed in the Cleveland District, and retailers in the Boston District were watchful.
Each of the ten Districts that reported on vehicle sales indicated that sales during the season were weak or down
overall (Philadelphia, Cleveland, Richmond, Atlanta, Chicago, St. Louis, Minneapolis, Kansas City, Dallas, and
San Francisco). Sales of domestic brands were especially weak in the Richmond and Dallas Districts. Chicago
reported increased demand for light trucks and San Francisco reported a slight increase in sales of larger used
vehicles. Both of these changes were reported to be in response to falling gas prices. In addition, Dallas reported an
increase in sales of used vehicles. Several Districts reported a negative outlook among car dealers.
Manufacturing and Other Business Activity
Manufacturing activity continued to fall in most Districts since the previous report, with declines reported across a
wide range of industries. Cleveland noted a slump in steel shipping and Chicago noted that domestic steel
production slowed. Dallas and Philadelphia indicated that industries related to construction experienced large
drops in orders, and Richmond noted that import activity for construction and household products remains notably
low. San Francisco reported that activity for producers of wood products remains depressed. Kansas City, St. Louis,
Cleveland, and Dallas noted decreases in auto and auto-related manufacturing activity. Cleveland, Dallas, and San
Francisco reported that capacity utilization was below normal levels or declined. Boston, Philadelphia, Cleveland,
Minneapolis, Chicago, and Kansas City mentioned reductions in capital spending or plans to reduce capital
spending in 2009. In contrast, firms in defense and medical-device production in the Minneapolis District reported
increased activity, and San Francisco noted that aerospace manufacturing continued at a high level. Food
manufacturing and processing remained active in the Philadelphia and Dallas Districts and solid in the San
Activity in the services sector declined throughout most Districts. Cleveland, Richmond, Atlanta, St. Louis, Kansas
City, and Dallas reported slowed or declining activity for transportation services, often related to the shipping of
construction and manufactured goods. San Francisco, St. Louis, New York, Chicago, Kansas City, and Minneapolis
reported declines in travel or tourism-related services. Richmond and Atlanta noted that tourism activity was mixed,
and Boston indicated that a majority of consulting and advertising firms reported stable to strong demand. Service
activity at auto dealers continued to be robust in the Chicago District, and it increased in the Dallas District.
Real Estate and Construction
Residential real estate activity continued to weaken in nearly all Districts. Boston, Philadelphia, Cleveland,
Richmond, Atlanta, St. Louis, Kansas City, and Dallas reported that home sales were weak or had declined. San
Francisco reported that despite some pickup in recent months, home sales continued to be quite slow in most parts
of the District. In the New York District, the market for new homes continued to weaken in New Jersey, and the
higher-priced housing markets nearest to New York City were characterized as especially weak. While the
Minneapolis District reported that late December saw an up-tick in residential sale activity in the Minneapolis-St.
Paul area, it was reportedly driven by foreclosures and short sales. Increased home sale cancellations were
common in a few Districts. Contacts in the Dallas District reported that home sale cancellations remained
prevalent, in some cases outpacing sales. Elevated cancellation rates and weak showroom traffic in the Chicago
District led developers to remain cautious about expanding inventory levels, and some building contractors in the
Cleveland District reported increased inventories because of take-backs from home sales that fell through. Boston,
Philadelphia, Atlanta, Kansas City, and San Francisco reported that home prices continued to soften or fall. Median
selling prices declined in and around New York City and were reported to have edged down in the Dallas District.
Richmond, however, reported that home prices remained steady.
Reporting Districts generally saw a decrease in homebuilding. Atlanta reported that homebuilders continued to pull
back on home construction. The Philadelphia and Chicago Districts noted that residential building continued its
decline. Residential construction was down in the St. Louis District, remained weak in Cleveland, and was quiet in
Commercial real estate markets deteriorated in most Districts. Contacts in the Boston District described the
commercial real estate market as grim and depressing, and market conditions continued to deteriorate in Richmond.
In the Minneapolis District, a contact noted that the market remained in a downturn that has now lasted more than
a year. Commercial real estate transactions in the Dallas District have reportedly ground to a halt. Leasing activity
was minimal in the Boston District, continued to fall in the Philadelphia District, and was assessed as ranging from
slowing to frozen in the Richmond District. Contacts in the Chicago District reported increases in sublease space.
Office and industrial leasing is expected to remain steady through the first half of 2009 in the St. Louis District, but
San Francisco reported that conditions in their commercial office market remained exceptionally weak. The New
York District reported that Manhattan's office vacancy rate climbed to its highest level in two years. Contacts in the
Chicago District noted elevated vacancy rates, and contacts in the Kansas City District expected higher vacancy
rates going forward. Contacts in the Atlanta District also anticipate that more commercial space will become
Reports about commercial construction activity also were downbeat. In the Philadelphia District, commercial
construction activity continued to fall. Cleveland reported that construction backlogs have declined for some
contractors. Commercial contractors in the Atlanta and Chicago Districts reported declines in building activity and
noted that more projects were cancelled or postponed. In St. Louis, contacts in commercial and industrial
construction predicted a challenging environment in early 2009. San Francisco reported that commercial
construction activity was very limited. Construction-related manufacturing contacts in the Dallas District reported
that demand from commercial construction is shrinking rapidly.
Banking and Finance
Most Districts that reported on lending activity indicated that it continued to decline or remained weak, and many
Districts reported that credit conditions remained tight or tightened further. Overall lending activity was reported to
have slowed or declined in New York, St. Louis, Kansas City, and Dallas; it remained soft or weak in the Chicago
and San Francisco Districts. Philadelphia reported a slow rise in outstanding loan volume with gains in real estate
loans and consumer credit, but no business-loan growth. Demand for commercial loans was stable to decreasing in
the Cleveland and Richmond Districts. Kansas City reported that demand fell for commercial and industrial loans,
while San Francisco indicated that commercial and industrial loan volumes were at very low levels. In contrast, St.
Louis reported a slight increase in commercial and industrial loans. New York, Cleveland, Richmond, Chicago,
Kansas City, and San Francisco noted an increase in residential mortgage refinancing activity. Demand for
consumer loans declined in the Cleveland, Kansas City, and Dallas Districts. St. Louis reported an increase in loans
Regarding credit conditions, Boston reported that credit availability continues to be a major barrier to commercial
real estate activity, and San Francisco noted that the availability of credit remains quite constrained. The New York
and Atlanta Districts indicated a general tightening of credit standards, while Kansas City noted tighter standards
for commercial real estate and commercial and industrial loans. Credit standards were described as unchanged to
tightening further by Cleveland and Richmond, while Dallas noted that depository institutions maintained tight
credit standards. Chicago reported that credit conditions remained tight. Credit quality declined or remained a
concern in the New York, Philadelphia, Cleveland, Chicago, Kansas City, Dallas, and San Francisco Districts.
Default rates on commercial loans are expected to rise in the Boston District. Richmond indicated mixed reports on
Weather conditions since the previous report had mixed effects on agricultural activity. Recent rain eased drought
conditions in most of the Atlanta District, while parts of the Dallas District were still severely dry. Weather
conditions allowed for fieldwork in the Atlanta and Minneapolis Districts but delayed fieldwork in the Richmond
and Chicago Districts. The winter wheat crop in the Kansas City District was in good condition, while winter wheat
development in the Richmond District was hindered by cooler temperatures and rain in recent weeks. The livestock
sector in the Kansas City District and the poultry sector in the Atlanta District reported slowed activity, while
production of red meat and some types of poultry decreased in the St. Louis District. The Atlanta, Kansas City,
Dallas, and San Francisco Districts reported that farm input costs (e.g., fuel and fertilizer) have moderated or
declined recently. Dallas reported that commodity prices have dropped, but Chicago and Kansas City reported that
corn and soybean prices have rebounded slightly.
Natural Resource Industries
Activity in the energy sector declined in several Districts since the previous report, with a number of Districts
linking the decrease to lower energy prices. In the Atlanta and Minneapolis Districts, oil and gas exploration
declined. Kansas City reported a dramatic slowing in energy activity, and Dallas reported a decrease in drilling
activity and a decline in the number of active oil rigs since the previous survey. In contrast, energy production did
not change in the Cleveland District, and coal production in the St. Louis District was higher in December 2008
than in December 2007. Looking ahead, contacts in the Cleveland and Kansas City Districts expect drilling activity
to decline for the first few months of 2009. Regarding capital spending, contacts in the Atlanta District indicate that
oil and gas exploration firms re-evaluated expansion plans in response to lower oil prices and difficulty obtaining
credit. Energy producers in the Kansas City District are cutting capital budgets, but producers in the Cleveland
District expect little change to their capital spending in early 2009. Finally, iron ore production in the Minneapolis
District decreased since the previous report.
Most Districts reported a general weakening of labor market conditions. Most Districts reported that layoffs
continued, and Boston, Cleveland, Richmond, Atlanta, and Dallas noted hiring freezes for select firms. Atlanta,
Chicago, and Dallas reported reduced hours to control costs. Job losses in the manufacturing sector were reported
by contacts in the Cleveland, Richmond, Chicago, St. Louis, Minneapolis, Kansas City, and Dallas Districts. Dallas
noted that layoffs were becoming widespread in the energy industry, and New York noted that a substantial number
of job reductions in the financial sector have yet to show up in payroll statistics. Richmond reported weaker demand
for temporary workers. In contrast, contacts in Chicago indicated that demand for skilled workers remained strong.
Richmond noted that demand was strongest for workers providing professional and support services, workers with
high-level technical skills, and workers proficient in computer software. Chicago noted employment growth in the
education, government, and healthcare fields. St. Louis also noted job growth in some small business support
services firms. Cleveland reported continued hiring in defense-related and healthcare industries.
Consumers saw sizable holiday price cuts in retail stores in a majority of the Districts. Retail contacts in the New
York, Philadelphia, Atlanta, Chicago, Minneapolis, Kansas City, Dallas, and San Francisco Districts reported
heavy holiday discounting. Retailers and restaurant contacts in the Kansas City District lowered prices and
anticipated further declines in the months ahead. Lower energy prices were noted throughout many of the Districts.
Most contacts in the Atlanta District reported reduced input price pressures, and about half of the contacts in
manufacturing and related services in the Boston District reported falling input prices. Boston reported large price
decreases for energy, oil-based materials, paper, and cotton in particular. In the Kansas City District, raw
materials prices fell sharply, and manufacturers in general reported a corresponding decline in finished product
prices. Manufacturers in the Philadelphia District also reported decreases in commodity prices and some reported a
reduction in the prices of their own products as well. Contacts in the Cleveland District observed that the downward
trend in raw materials prices has started to level off and that pricing of manufactured products remained relatively
stable. On the other hand, the Richmond District noted that raw materials prices rose at a slightly quicker pace
since last reported. Contacts in the San Francisco District reported that they expect upward price pressures to
remain very limited during early 2009.
Wage pressures remained largely contained in most Districts. The Cleveland, Chicago, Dallas, and San Francisco
Districts reported little to no wage pressures. Richmond noted that wage gains in the retail sector held up, but
average wage increases slowed for service firms. Wage increases were modest in the Minneapolis District, and
wage pressures diminished in the Kansas City District. A few Districts experienced slowing wage gains in sectors
that had previously seen rapid wage advances, notably the energy sector in the Cleveland District and the
technology sector in the San Francisco District. According to reports from the New York District, year-end bonuses
at financial firms are seen falling 20 to 30 percent from a year ago at some of the smaller firms but more
substantially at the larger establishments. The Boston, Chicago, and San Francisco Districts also noted that some
contacts are enacting or considering pay freezes or reductions in compensation.
FX: we can trade the report after it is released. We have to read the entire report to glean the
overall picture. Prices and Business Activity are most important to forex.
Per Bureau of Labor Statistics, the Consumer Price Index (CPI) is a measure of the average change over
time in the prices paid by urban consumers for a market basket of consumer goods and services.
The CPI reflects spending patterns for each of two population groups: all urban consumers and urban
wage earners and clerical workers. The all urban consumer group represents about 87 percent of the
total U.S. population. It is based on the expenditures of almost all residents of urban or metropolitan
areas, including professionals, the self-employed, the poor, the unemployed, and retired people, as well
as urban wage earners and clerical workers. Not included in the CPI are the spending patterns of people
living in rural nonmetropolitan areas, farm families, people in the Armed Forces, and those in institutions,
such as prisons and mental hospitals.
Consumer inflation for all urban consumers is measured by two indexes, namely, the Consumer Price
Index for All Urban Consumers (CPI-U) and the Chained Consumer Price Index for All Urban Consumers
The CPI frequently is called a cost-of-living index, but it differs in important ways from a complete cost-of-
living measure. BLS has for some time used a cost-of-living framework in making practical decisions
about questions that arise in constructing the CPI. A cost-of-living index is a conceptual measurement
goal, however, and not a straightforward alternative to the CPI. A cost-of-living index would measure
changes over time in the amount that consumers need to spend to reach a certain utility level or standard
of living. Both the CPI and a cost-of-living index would reflect changes in the prices of goods and
services, such as food and clothing, that are directly purchased in the marketplace; but a complete cost-
of-living index would go beyond this role to also take into account changes in other governmental or
environmental factors that affect consumers' well-being. It is very difficult to determine the proper
treatment of public goods, such as safety and education, and other broad concerns, such as health, water
quality, and crime, that would constitute a complete cost-of-living framework.
The CPI market basket is developed from detailed expenditure information provided by families and
individuals on what they actually bought. For the current CPI, this information was collected from the
Consumer Expenditure Surveys for 2005 and 2006. In each of those years, about 7,000 families from
around the country provided information each quarter on their spending habits in the interview survey. To
collect information on frequently purchased items, such as food and personal care products, another
7,000 families in each of these years kept diaries listing everything they bought during a 2-week period.
Over the 2 year period, then, expenditure information came from approximately 28,000 weekly diaries
and 60,000 quarterly interviews used to determine the importance, or weight, of the more than 200 item
categories in the CPI index structure.
The CPI represents all goods and services purchased for consumption by the reference population (U or
W) BLS has classified all expenditure items into more than 200 categories, arranged into eight major
groups. Major groups and examples of categories in each are as follows:
FOOD AND BEVERAGES (breakfast cereal, milk, coffee, chicken, wine, full service meals, snacks)
HOUSING (rent of primary residence, owners' equivalent rent, fuel oil, bedroom furniture)
APPAREL (men's shirts and sweaters, women's dresses, jewelry)
TRANSPORTATION (new vehicles, airline fares, gasoline, motor vehicle insurance)
MEDICAL CARE (prescription drugs and medical supplies, physicians' services, eyeglasses and eye
care, hospital services)
RECREATION (televisions, toys, pets and pet products, sports equipment, admissions);
EDUCATION AND COMMUNICATION (college tuition, postage, telephone services, computer software
OTHER GOODS AND SERVICES (tobacco and smoking products, haircuts and other personal services,
The items that markets are interested are marked in blue: All Items Consumer Price Index for All Urban
Consumers (CPI-U) for the U.S. City Average, 1982-84 = 100; and All items less food and energy, or core
Table A. Percent changes in CPI for All Urban Consumers (CPI-U)
Category Changes from preceding month annual Un-
June July Aug. Sep. Oct. Nov. Dec. ended ended
2008 2008 2008 2008 2008 2008 2008 Dec. 2008 Dec. 2008
All items.......... 1.1 .8 -.1 .0 -1.0 -1.7 -.7 -12.7 .1
Food and beverages .7 .9 .6 .6 .3 .2 .0 1.7 5.8
Housing........... .5 .6 -.1 -.1 .0 -.1 .0 -.7 2.4
Apparel........... .1 1.2 .5 -.1 -1.0 .3 -.9 -6.4 -1.0
Transportation.... 3.8 1.7 -1.5 -.6 -5.4 -9.8 -4.4 -55.6 -13.3
Medical care...... .2 .1 .2 .3 .2 .2 .3 2.8 2.6
Recreation........ .1 .4 .5 .2 .1 .0 -.2 -.4 1.8
communication.. .5 .5 .2 .1 .2 .2 .3 3.0 3.6
Other goods and
services....... .4 .4 .2 .2 .3 .0 .0 .8 3.4
Energy............ 6.6 4.0 -3.1 -1.9 -8.6 -17.0 -8.3 -76.6 -21.3
Food.............. .8 .9 .6 .6 .3 .2 -.1 1.4 5.9
All items less
food and energy .3 .3 .2 .1 -.1 .0 .0 -.3 1.8
Time: 8:30 am EST; about 15-17 days after the end of reporting month
FX: Though the Fed prefers the PCE Deflator, the CPI release is also a market shaker. A
period before the release is on average most desirable to trade on expectations of this release.
Traders put much more weight in the core CPI. If the All Items CPI moves, say, upward, but the
core CPI remains at the same annual level, the impact on movement of FX rates is tamed. We
can actually see reversal after the initial reaction to the All Items CPI. Growing domestic
inflation strengthens domestic currency is THE underlying axiom to be utilized. Follow the
guidance described in Event Studies how to trade this release.
Per Bureau of Labor Statistics, the Producer Price Index is a family of indexes that measures
the average change over time in the selling prices received by domestic producers of goods
and services. PPIs measure price change from the perspective of the seller. This contrasts
with other measures, such as the Consumer Price Index (CPI), that measure price change
from the purchaser's perspective. Sellers' and purchasers' prices may differ due to
government subsidies, sales and excise taxes, and distribution costs.
Over 10,000 PPIs for individual products and groups of products are released each month.
PPIs are available for the products of virtually every industry. The PPIs capture price
movements prior to the retail level. Therefore, they may foreshadow subsequent price
changes for businesses and consumers.
PPIs are used to adjust other economic time series for price changes and to translate those
series into inflation-free dollars. For example, constant-dollar gross domestic product data
are estimated using deflators based on PPI data.
PPI data are commonly used in escalating purchase and sales contracts. These contracts
typically specify dollar amounts to be paid at some point in the future. It is often desirable
to include an escalation clause that accounts for increases in input prices. For example, a
long-term contract for bread may be escalated for changes in wheat prices by applying the
percent change in the PPI for wheat to the contracted price for bread.
While both the PPI and CPI measure price change over time for a fixed set of goods and
services; they differ in two critical areas: (1) the composition of the set of goods and
services, and (2) the types of prices collected for the included goods and services.
The target set of goods and services included in the PPIs is the entire marketed output of
U.S. producers. The set includes both goods and services purchased by other producers as
inputs to their operations or as capital investment, as well as goods and services purchased
by consumers either directly from the service producer or indirectly from a retailer. Because
the PPI target is the output of U.S. producers, imports are excluded. The target set of items
included in the CPI is the set of goods and services purchased for consumption purposes by
urban U.S. households. This set includes imports.
The price collected for an item included in the PPIs is the revenue received by its producer.
Sales and excise taxes are not included in the price because they do not represent revenue
to the producer. The price collected for an item included in the CPI is the out-of-pocket
expenditure by a consumer for the item. Sales and excise taxes are included in the price
because they are necessary expenditures by the consumer for the item.
The differences between the PPI and CPI are consistent with the different uses of the two
measures. A primary use of the PPI is to deflate revenue streams in order to measure real
growth in output. A primary use of the CPI is to adjust income and expenditure streams for
changes in the cost of living.
The composition of items in the Finished Goods Price Index differs from that of the All Items
Consumer Price Index in two major respects. First, the Finished Goods Price Index includes
price changes for producers' durable equipment, which are not purchased by typical
consumers and, therefore, are not included in the CPI. Second, the All Items CPI includes
services which are not reflected in the Finished Goods Price Index. An additional difference
is that the Finished Goods Price Index is only available at the U.S. level, while the All Items
CPI is available at the regional, metropolitan area, and U.S. levels.
Below is a table summarizing major components of a PPI release. Markets are mostly
interested in Finished Goods, Total and Except Foods and Energy (core).
Monthly and annual percent changes in selected stage-of-processing price
indexes, seasonally adjusted.
Finished Goods Intermediate Crude
Foods in goods goods
Month Total Foods Energy (unadj.)
Jan. 1.2 1.7 2.2 0.6 7.4 1.2 2.9
Feb. 0.3 -0.6 1 0.4 6.5 0.9 3.9
Mar. 0.9 1.4 2.5 0.1 6.7 2.4 6.7
Apr. 0.3 0 -0.1 0.5 6.4 1 4.7
May 1.4 0.6 5.3 0.2 7.3 2.7 6.1
June 1.7 1.5 5.6 0.2 9.1 2.2 2.8
July 1.2 0.3 3.4 0.6 9.9 2.7 4
Aug -0.9 0.3 -4.8 0.5 9.7 -1.5 -12.3
Sep -0.4 0.2 -3 0.4 8.7 -0.9 -6
Oct. -2.8 -0.2 -12.8 0.4 5.2 -3.9 -18.6
Nov. -2.2 0 -11.2 0.1 0.4 -4.3 -12.5
Dec. -1.9 -1.5 -9.3 0.2 -0.9 -4.2 -5.3
Source: Bureau of Labor Statistics
Time: 8:30 am EST; monthly, 2 weeks after the reporting month
FX: PPI figures are always released one-two days before the CPI indices. The PPI index is
important because it’s an early indicator of inflationary pressure. However, CPI and PCE
deflator are most important to policymakers. Therefore, the release does not generate much of
volatility in FX rates. Everyone is waiting for the CPI release. Also PPI series is weakly
correlated to CPI for monthly changes. Even lagged correlations between these two series do
not show strong correlations. For all those reasons, trading on expectations is limited. We can
exploit some exaggerated moves that can revert due to uncertainty of the CPI figures.
Nonfarm payrolls and employment situation
One of the most widely anticipated reports on the US economic calendar, the Employment
Situation is a timely report that gives a picture of job creation, loss, wages and working hours in
the United States. Data in the report relies on the Household Survey and the Establishment (or
Payroll) Survey. While the Household Survey is based on the interviews to US households, the
Establishment Survey queries business establishments, making it the preferred source of data.
The Employment Situation's has many significant figures such as: Change in Nonfarm Payrolls,
Unemployment, and Average Hourly Earnings.
Below description is taken from dailyfx.com:
(a) Change in Non-farm Payrolls
Monthly change in employment excluding the farming sector. Non-farm payrolls is the most closely watched
indicator in the Employment Situation, considered the most comprehensive measure of job creation in the
US. Such a distinction makes the NFP figure highly significant, given the importance of labor to the US
economy. Specifically, political pressures come into play, as the Fed is responsible for keeping employment
in a healthy range and utilizes interest rate changes to do so. A surge in new Non-farm Payrolls suggests
rising employment and potential inflation pressures, which the Fed often counters with rate increases. On
the other hand, a consistent decline in Non-farm Employment suggests a slowing economy, which makes a
decline in rates more likely.
My two cents. Analysis of nonfarm payrolls should concentrate on moving averages stretching
a few months, not month-by-month. Below chart shows monthly, 3-month, and 12-month
changes in nonfarm payrolls. There are a few conclusions that we can draw. Changes in
employment are cyclical. But do not look for some patterns. It’s just a response to overall
economic conditions at the given time. Nonetheless, being aware of cyclicality help us to spot a
trend and act on it.
Analysis of 3-month changes in nonfarm payrolls points to a pattern. Namely, a negative growth
tends to continue when the average crosses negative numbers. Position traders can utilize this
pattern for longer holding. The pattern is even more useful for investing in equities, especially
industry sectors. Most recently, negative trend first showed up in January 2008 and continues
to this day (February 2009).
Nonfarm Payroll: 1-,3-, 12-month change
Source: Federal Reserve Bank of St. Louis, author
(b) Unemployment Rate
The percentage of people registered as unemployed in the United States. The figure is calculated by dividing
the number of unemployed individuals in the labor force by the total labor force. Where the headline figure
Change in Non-Farm Payrolls generally moves the market upon release, the Unemployment Rate serves as
the most popular snap-shot figure for current labor conditions in the US.
The unemployment figure can give insight into the economy's production, consumption, earnings, and
consumer sentiment. A lower unemployment rate equates to increased expenditure, as more people have
jobs and wages to spend. Increased expenditure encourages economic growth, which can spark inflation
pressures. Conversely, high levels of unemployment signal economic instability and weakened demand.
Persons are considered unemployed if they are able and willing to work but without a job and have actively
sought employment within the last four weeks. The labor force includes all employed and unemployed
individuals 16 years and older.
Analysis of data does not pinpoint to recognizable patterns. It’s just the circumstance of the
time. Recessions start at very different levels of unemployment that range from circa 4% to 7%.
Chart with total number of unemployed shows clearly cyclicality of employment. It also shows
upward drift associated with the growth of population. We are not far away from surpassing
total number of unemployed that was reached during the recession in 1980.
Data showing Civilian Employment-Population Ratio seems to be somewhat skewed compared
to the decades from 1950 thru 1980. Probably part-time employment and holding two jobs have
changed the ratio pattern. It also implies that we have to work harder.
(c) Average Hourly Earnings
An indicator of how the average level of pay is changing. The Average Hourly Earnings figure provides
insight into future spending and inflation. A High Average Hourly Earnings bodes well for future
consumption, as workers have more disposable income. High figures may indicate inflationary pressures due
to employee's additional potential to spend. The figure is either measured in hourly or weekly averages or as
a percent change from the previous month.
For the period from 1980 thru present, the average weekly hours ranged from 35.2 to 33.1.
I’m devoting a lot of space to the Employment Situation because the release shakes the
markets. Below is description taken from the Bureau of Labor Statistics:
The employment report is actually two separate reports which are the results of two separate surveys. The household survey is a
survey of roughly 60,000 households. This survey produces the unemployment rate. The establishment survey is a survey of
375,000 businesses. This survey produces the nonfarm payrolls, average workweek, and average hourly earnings figures, to name
a few. Both surveys cover the payroll period which includes the 12th of each month.
The reports both measure employment levels, just from different angles. Due to the vastly different size of the survey samples
(the establishment survey not only surveys more businesses, but each business employs many individuals), the measures of
employment may differ markedly from month to month. The household survey is used only for the unemployment measure - the
market focuses primarily on the more comprehensive establishment survey. Together, these two surveys make up the
employment report, the most timely and broad indicator of economic activity released each month.
Total payrolls are broken down into sectors such as manufacturing, mining, construction, services, and government. The markets
follow these components closely as indicators of the trends in sectors of the economy; the manufacturing sector is watched the
most closely as it often leads the business cycle. The data also include breakdowns of hours worked, overtime, and average
The average workweek (also known as hours worked) is important for two reasons. First, it is a critical determinant of such
monthly indicators as industrial production and personal income. Second, it is considered a useful indicator of labor market
conditions: a rising workweek early in the business cycle may be the first indication that employers are preparing to boost their
payrolls, while late in the cycle a rising workweek may indicate that employers are having difficulty finding qualified applicants
for open positions. Average earnings are closely followed as an indicator of potential inflation. Like the price of any good or
service, the price of labor reacts to an overly accommodative monetary policy. If the price of labor is rising sharply, it may be an
indication that too much money is chasing too few goods, or in this case employees.
Time: First Friday of the month at 8:30 am EST for the prior month
FX: best bet is to trade Employment Situation before it is released based on expectations. We
cannot trade at the release because market makers stretch bid/ask spread to huge number of
pips. We have to anticipate how to trade after the situation settles given the figures. But key
questions are the same: what are the impacts on GDP and inflation? Growing numbers
strengthen the USD and weaken the USD otherwise.
University of Michigan Consumer Confidence
It assesses consumers on their finances, business conditions and purchasing power based on
The Index of Consumer Sentiment (ICS) is derived from the following five questions:
X1 = "We are interested in how people are getting along financially these days. Would you say
that you (and your family living there) are better off or worse off financially than you were
a year ago?"
X2 = "Now looking ahead--do you think that a year from now you (and your family living there)
will be better off financially, or worse off, or just about the same as now?"
X3 = "Now turning to business conditions in the country as a whole--do you think that during the
next twelve months we'll have good times financially, or bad times, or what?"
X4 = "Looking ahead, which would you say is more likely--that in the country as a whole we'll
have continuous good times during the next five years or so, or that we will have periods
of widespread unemployment or depression, or what?"
X5 = "About the big things people buy for their homes--such as furniture, a refrigerator, stove,
television, and things like that. Generally speaking, do you think now is a good or bad time
for people to buy major household items?"
The index is released twice a month. Preliminary surveys are released on the second Friday of each
month at 9:45 EST. Preliminary releases have the biggest impact on capital markets because of their
forecasting nature. Final numbers are released on the last Friday of the month.
Index of Consumer Sentiment
To calculate the Index of Consumer Sentiment (ICS), first compute the relative scores (the
percent giving favorable replies minus the percent giving unfavorable replies, plus 100) for each
of the five index questions (x1 ...x5 listed below). Using the formula shown below, sum the five
relative scores, divide by the 1966 base period total of 6.7558, and add 2.0 (a constant to
correct for sample design changes from the 1950s).
Total ICS = (X1 + X2 + X3 + X4 + X5)/6.7558 + 2.0
Index of Current Economic Conditions
Current ICS = (X1 + X5)/2.6424 + 2.0
Index of Consumer Expectations
Expectations ICS = (X2 + X3 + X4 )/4.1134 + 2.0
For the sample from Jan 1978 thru Nov 2008, Max value for total ICS was 112.0 and min 51.7.
Below is a frequency distribution with bins of 10 points:
ICS No. Most prevalent levels of the index were between the values of 90 and 100
120 4 (149 occurrences). The median for the sample is about 90. Anything
110 43 above that value can be construed as good economic conditions.
100 149 Good Values below 90, on the other hand, indicate economic conditions that
90 78 range from deterioration to recession.
80 49 Bad
This is an influential release for all asset classes. Since consumer spending counts for about
70% of GDP, consumer expectations is a good harbinger of the growth of GDP. .
ISM Semiannual Economic Forecast.
ISM business survey committee gathers members' views of the general business outlook six to
eight months ahead in ISM's Semiannual Economic Forecast. Below are headlines of two
Spring 2008 Semiannual Economic Forecast (May 6, 2008)
ECONOMIC GROWTH TO CONTINUE THROUGHOUT 2008
Manufacturing Growth Marginal in 2008
Revenue to Increase 1%
Capital Investment to Increase 1%
Capacity Utilization at 78.6%
Non-Manufacturing Growth Sustainable in 2008
Revenue to Increase 2.7%
Capital Investment to Decrease 2.7%
Capacity Utilization at 85.9%
ECONOMIC SLOWDOWN TO CONTINUE IN 2009 (December 9, 2008)
Manufacturing Contraction Expected in 2009
Revenue to Decrease 1.1%
Capital Expenditures to Decrease 6.7%
Capacity Utilization Currently at 75.2%
Non-Manufacturing to Maintain Slight Growth
Revenue to Increase 0.7%
Capital Expenditures to Decrease 8.4%
Capacity Utilization Currently at 83.1%
As we can see from the Spring 2008 survey, predictions did not worked out. Nobody had seen
the crush coming. So those surveys should be taken with cautions. Markets by and large do
not pay much of attention to these forecasts so there is no formal reaction to it. But they are
contributing elements in forming opinion about the future.
Current Economic Conditions, commonly known as the Beige Book, is published two weeks
prior to each FOMC meeting eight times per year. Each Federal Reserve Bank gathers
anecdotal information on current economic conditions in its District through reports from Bank
and Branch directors and interviews with key business contacts, economists, market experts,
and other sources. The Beige Book summarizes this information by District and sector. An
overall summary of the twelve district reports is prepared by a designated Federal Reserve
Bank on a rotating basis.
The report provides information in the following categories:
Overall economic activity
Manufacturing and Other Business Activity
Real Estate and Construction
Banking and Finance
Natural Resource Industries
Thought the report seldom moves the markets, it provides very useful information. Big players
may not necessarily react to it instantly but will certainly incorporate result of the survey to their
long term trading decisions. It is worth juxtaposing this release with forecasts on Fed decision
about the fed fund rates (www.clevelandfed.org/research/data/fedfunds/index.cfm - see section
Central banks and Interest Rates, United States).
Time: 2pm EST; 8 times a year, 2 Wednesdays before each FOMC meeting
Web: www.federalreserve.gov/monetarypolicy/default.htm <<Reports << Beige Book
FX: The release is rather useful for position trading. Key question to ask is how much the
release changes the current beliefs. The trend will continue if the Beige Book reinforces the
current view on economic conditions. If the Beige Book signals deviations from the current
beliefs, reversal in FX rates are expected and can be continual.
Testimonies before US Congress
Chairman of the Federal Reserve is required to submit a Monetary Policy Report to the US
Congress, pursuant to section 2B of the Federal Reserve Act. Twice a year in the second
halves of February and July, the Chairman testifies before the Congress. Markets can and
usually do gyrate during the time of testimony. Reactions are a bit of a surprise because most
of the testimonies are already known and are in congruence with the current beliefs. It is just
reinforcing of the current beliefs. Most valuable information is in Chapter 4 of the report,
Summary of Economic Projections.
FX: Traders are usually idle just prior to the testimony. And during the testimony, markets often
zigzags to short-lived exaggerated levels. Even the confirmation what is already known by
market participants but is coming from the Chairman’s mouth can generate sharp responses. It
is advisable to take the Chairman’s statements at face value. But keeping in mind that a next
statement during the testimony may mitigate the initial reaction. Alan Greenspan was famous
for his on-the-other-hand counterbalanced comments. We can trade those exaggerations but
have to be quite prepared and identify what constitutes an exaggerated move of FX rates.
Best bet for traders is to apply projections of the report in Chapter 4. Growth of GDP and
inflation are key figures to look for. The growth of GDP and inflation strengthens the USD –
under normal economic conditions.
Empire State Manufacturing Survey
The survey is assessing business conditions and expectations of manufacturing executives in
the State of New York. It is a harbinger of the overall manufacturing situation in the U.S. The
number is a diffusion index; levels above zero shows growing economy and below zero
In addition to the overall index, the
survey provided insight to Future
General Business Conditions and
Time: 8:30 am EST, about 15 days after the end of the reporting month
FX: reaction to this release is rather short-lived. Most traders will wait for the release of the
national ISM. However, big change in Future General Business Conditions survey can indicate
a long lasting trend and trigger trading activities.
Minutes of FOMC Meeting
Key inquiry to the Minutes is to infer future direction of interest rates from comments of the
voting members and opinions on economic developments. Is the Fed dovish or hawkish in the
Time: 1:00 pm EST three weeks after the date of the FOMC meeting
FX: we can trade this release only at the time it is released and afterwards.