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TRADING A SHORT-SIDE POUND PATTERN P. 31
Chinas new normal,
and the implicationsfor currencies p. 6
Excess volatility
and the major
FX pairs p. 20
Building an FX
system with atrailing stop p. 16
The beginnings
of a panic? p. 10
Strategies, analysis, and news for FX traders
February 2014
Volume 11 No. 2
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2/312 February 2014 CURRENCY TRADER
CONTENTS
Contributors.................................................4
Global Markets
Chinas new normal ....................................6
Single-digit GDP growth is the new paradigm,
with credit-bubble risks looming in the
background. Which currencies are most
exposed?
By Currency Trader Staff
On the Money
Seeds of a classic panic maybe.........10
Was the market disruption toward the end of
January a chink in the markets armor, or justanother pullback?
By Barbara Rockefeller
Trading Strategies
Trailing stops, curtailing losses .............16
Starting with a trailing stop rule can make your
forex system easier to trade.
By Daniel Fernandez
Advanced Concepts
When excess becomes predictable:
The majors ................................................20
Find out whether carry returns from the U.S.
dollar, along the money-market yield curve,
can predict the excess of implied volatility over
historical volatility.
By Howard L. Simons
Global Economic Calendar ........................26
Important dates for currency traders.
Events .......................................................26
Conferences, seminars, and other events.
Currency Futures Snapshot.................27
BarclayHedge Rankings........................27
Top-ranked managed money programs
International Markets............................28
Numbers from the global forex, stock, and
interest-rate markets.
Forex Journal ...........................................31
Taking a swing at the pound/dollar pair
Looking for an
advertiser?
Click on the companyname for a direct link to the
ad in this months issue.
Ablesys
eSignal
FXCM
Interactive Brokers
Questions or comments?Submit editorial queries or comments to
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4/31
CONTRIBUTORS
4 February 2014 CURRENCY TRADER
Editor-in-chief:Mark Etzkorn
Managing editor:Molly Goad
Contributing editor:
Howard Simons
Contributing writers:
Barbara Rockefeller,
Marc Chandler, Chris Peters
Editorial assistant and
webmaster:Kesha Green
President:Phil Dorman
Publisher, ad sales:
Bob Dorman
Classifed ad sales: Mark Seger
Volume 11, No. 2. Currency Trader is published monthly by TechInfo, Inc.,PO Box 487, Lake Zurich, Illinois 60047. Copyright 2014 TechInfo, Inc.All rights reserved. Information in this publication may not be stored orreproduced in any form without written permission from the publisher.
The information in Currency Trader magazine is intended for educationalpurposes only. It is not meant to recommend, promote or in any way implythe effectiveness of any trading sys tem, strategy or approach. Traders areadvised to do their own research and testing to determine the validity of atrading idea. Trading and investing carry a high level of risk. Past perfor-mance does not guarantee future results.
For all subscriber services:www.currencytradermag.com
A publication of Active Trader
CONTRIBUTORS
qHoward Simonsis president ofRosewood Trading Inc. and a strategist for
Bianco Research. He writes and speaks fre-
quently on a wide range of economic and
nancial market issues.
qDaniel Fernandezis an active trader
with a strong interest in calculus, statistics,
and economics who has been focusing on
the analysis of forex trading strategies,
particularly algorithmic trading and the
mathematical evaluation of long-term sys-tem protability. For the past two years he has published
his research and opinions on his blog Reviewing Every-
thing Forex, which also includes reviews of commercial
and free trading systems and general interest articles on
forex trading (http://mechanicalforex.com). Fernandez is
a graduate of the National University of Colombia, where
he majored in chemistry, concentrating in computational
chemistry. He can be reached at [email protected].
qBarbara Rockefeller(www.rts-forex.com) is an
international economist with a focus on foreign exchange.
She has worked as a forecaster, trader, and consultant at
Citibank and other nancial institutions, and currently
publishes two daily reports on foreign exchange. Rockefel-
ler is the author of Technical Analysis for Dummies, Second
Edition(Wiley, 2011), 24/7 Trading Around the Clock, Around
the World(John Wiley & Sons, 2000), The Global Trader
(John Wiley & Sons, 2001), The Foreign Exchange Matrix
(Harriman House, 2013), and How to Invest Internationally,
published in Japan in 1999. A book tentatively titled How
to Trade FXis in the works. Rockefeller is on the board of
directors of a large European hedge fund.
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]://mechanicalforex.com/http://www.rts-forex.com/http://www.rts-forex.com/http://mechanicalforex.com/mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]8/12/2019 CurrencyTrader0214-jp4p
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GLOBAL MARKETS
China, the worlds second-largest economy,is in transition.Economists increasingly believe a major change is neededfor the Chinese economy, including a shift from the export-led model of recent years to a domestic consumption-ledmodel. However, as Beijing tries to orchestrate a major
structural transformation, concerns over a potential creditbubble are rising to the surface, which could leave thecountrys banking system vulnerable to a shock in 2014.
For the most part, however, the hard-landing scenari-os have eased as overall growth numbers have stabilized,albeit at a much lower rate than in the years prior to the2008 global financial crisis. China registered GDP growthof 7.7% in 2013, the same level as in 2012. With concernsabout social stability in the background, the governmenthas relied on both monetary and fiscal policies to keep thecountrys economic engines moving.
But the fiscally driven infrastructure boom of recentyears has sparked widespread concerns about the rise of
a credit build-up in China and the possibility of a bankingcrisis lurking in the shadows.
For currency traders, the more immediate issues arewhether an evolving Chinese economy portends a moreopen foreign exchange market for the yuan/renminbi, aswell as what other currencies function as good China prox-ies.
Economic outlookFollowing the Communist partys third plenary sessionin 2013, it became clear the days of 10% GDP were over,according to according to Northern Trust vice presidentJames Pressler. Seven to eight percent would be the
expectation going forward, he says. Pressler estimates2014 GDP in the 7.5 to 7.6% range.
Most analysts seem to agree a new era of lower, but stillquite robust economic growth has emerged in China. Thebase case is they remain in the 7-8% growth range, says
Wells Fargo economist Jay Bryson. I dont think they areever going back to double digits.Pressler says Chinas reform strategy includes plans to
shift from the export-driven model that has worked wellin Asia for 20 years to a point where Chinese consumersexert a greater influence on the economy. As a comparison,he notes the U.S. consumer has a 70% impact on GDP,while the Chinese consumer only has about a 33% impact.
Shifts in the global manufacturing and labor landscapeare playing into Chinas desire to decrease its relianceon exports. Now that wages have risen significantly inChina, the rest of Asia is becoming more competitive,Presser says. They are losing the low-wage labor force. A
mid-level garment worker in China makes $500 a month,while in Bangladesh they earn $50-60 a month. Theyre los-ing the low-end manufacturers and the wage competitive-ness they had 10 to 20 years ago.
Lending spreeAnother factor driving the Chinese government to engi-neer slower overall growth levels is rising credit levels.The Chinese government acted swiftly and aggressivelyat the end of 2008 to combat the slowdown in the globaleconomy. The government issued 4 trillion yuan of stimu-lus, Pressler notes. A lot of credit was built up to devel-op infrastructure and real estate projects.
Chinas new normal
Single-digit GDP growth is the new paradigm, with credit-bubble risks
looming in the background. Which currencies are most exposed?
BY CURRENCY TRADER STAFF
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7/31CURRENCY TRADER February 2014
According to Paul Sheard, chief global economist atStandard & Poors, the Chinese governments fiscal poli-cies were generally successful, as evidenced by the coun-trys spectacular performance of around 9% GDP inthe years after the financial crisis. But that success wasnot without cost. The credit-fueled investment boomfocused on infrastructure, he says. The problem withChinas solution to the global financial crisis is it solvedone problem and raised another. Sheard says the countryis dealing with the potential aftermath of a credit-fueled
splurge.The Chinese government supported a massive, rapid
build-up, including apartment complexes and shoppingdistricts essentially complete cities, many of whichcurrently stand completely empty to service what hadbeen a flood of workers moving east in a search for better-paying jobs. Pressler notes that although the developmentwas meeting a need for new housing, a lot of the projectswerent producing the returns that were expected to payoff the projects. Adding to the problem, rising propertyprices put some of the real estate out of the average work-ers reach.
Shadow banking systemIn recent years a so-called shadow banking system hassprung up in China. It includes non-financial companies,such as export or consumer-goods producers that werelooking for an opportunity to invest their excess reserves,according to Pressler. The current low interest rates on sav-ings prompted non-financial companies to expand into theloan business to capture a higher rate of return. Ultimately,however, this exposed these non-financial companies toother areas of the economy especially the real estate sec-tor.
Adding to the worries are these loans lack of visibility.
Its very difficult to monitor how much credit is beingoffered by non-financial organizations, Pressler says.Once you start flying off the radar, its hard to tell what isgoing on.
JPMorgan estimates the entire shadow banking sec-tor, which includes private non-financial lending, trustaccounts, and wealth investment products, totals $6 tril-lion a little less than 70% of GDP, Pressler notes. Thisfigure is in addition to the known total Chinese domesticbanking assets that equal about 250% of GDP. In the U.S.,as of 2012 (the latest numbers that are available), totalassets or loans carried by commercial banks totaled 78.8%of GDP, Pressler notes.
One could argue the pace of development is slowing,and yet you still have credit rising, he says.
Domino effectPressler warns regional and provincial financial institu-tions could be at the biggest risk. If we were to start see-ing defaults at the regional, provincial level or in theworst case, a bank folds then you have a crisis of confi-dence on your hands, he says.
In recent years, wealth management products (WMPs)
have risen in popularity in China. These are products soldby banks in which an individual buys into a collateralizedobligation with the promise of a specific return say, 8%for the time you hold the vehicle.
Pressler says these risks of these products have are somesimilarities to the mortgage-backed crisis the shook theU.S. and other Western economies. Its tough to analyze afund backed by a series of loans into an investment projectwith the assumption of a return, he says. Our larger con-cern is that if something goes wrong, it will spread inter-nally, and within the financial sector.
In other words, Sheard notes, some of those investments
could run into problems. The policy challenge will be ifthere are some non-performing loans and the losses start toripple through the system people could panic and loseconfidence, he says.
Sean Callow, senior currency strategist at WestpacInstitutional Bank, sees a similar risk. Frustrated bycapped interest rates at banks and a lackluster local stockmarket, investors are attracted by high-yielding wealthmanagement products often sold through banks, he says.Recently there has been increased concern over theseWMPs as defaults loom. High return of course means highrisk; the danger is that WMP defaults will have a spillovereffect on the financial system and investor confidence.
While this is an underlying risk for the economy, someargue Chinas tight economic controls could keep a finan-cial crisis in check. Over the last 35 years, the authori-ties have been able to manage their economy very well,Sheard says. There will be localized sporadic events, thequestion is whether they become systemic. Our base caseis no.
This challenge has emerged at a time when the Chineseauthorities are attempting to liberalize the financial systemsomewhat to allow market forces a stronger hand. Thiswill be a longer-term dynamic playing out in China: Howdo you transition from one economic model to another?Sheard says.
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GLOBAL MARKETS
Yuan action
In the meantime, the Chinese yuan remains under the firmhand of the monetary authorities, with the USD/CNYtrading around 6.04 in late January (Figure 1). The yuanappreciated steadily from late 2005 into late 2008, but oncethe global financial crisis began, the currency leveled outand moved sideways around 6.80 until September 2010,when the appreciation trend restarted. The last severalyears have seen the USD/CNY rate fall to its recent lowaround 6.04.
The yuan is now the strongest its been since the rebal-ancing in 1993, Pressler notes. However, he adds it stillremains undervalued. I think it should be around 5.4-5.4, he says.
Pressler notes the Chinese government allowed the yuanto appreciate by 2.7% in 2013. We believe given theireconomy will slow down and they will be sensitive to theneeds of exporters, they probably wont let it cross the6.00 level until the third quarter, he says. Once you let itbreak into the high 5.90s, youre crossing a boundary.
Callow says the most likely scenario for the CNY issteady gains. He notes Chinas FX reserves grew $157 bil-lion in the fourth quarter 2013, while CNY rose just 1.1%over those three months.
Chinas trade and net foreign direct investment positionremains very strong, he says. The clear impression isthat USD/CNY is not very close to the equilibrium officials
seek, so intervention will only slow the pace of yuan gains.
Investors are likely to continue to view CNY as a one-waybet in 2014, just not a bet with a big payoff perhaps only3-4%.
Will China have a freer and more open foreign exchangemarket? Will it be significantly more open this year? No,Bryson says. In five to 10 years? Yes. All policies there areglacial. Everything is measured, everything moves veryslowly. They are not up for the big bang experiment.
Spillover impactIf some banking or credit issues explode later in 2014, whatcountries and other global currencies could see an impact?
The Australian dollar remains very sensitive to any
developments that would hurt Chinas economy, so itwould be speculators preferred short on any notable Chinaturmoil this year, Callow notes. The Japanese yen is alikely beneficiary, along with the Swiss Franc and U.S. dol-lar, which are the proven safe-havens in the global crisis.
BNP Paribas FX strategist Vassili Serebriakov agrees theAustralian dollar is the G-10 currency that is most sensitiveto the China story (Figure 2). It is the G-10 economy withthe largest share of its exports going to China. The risksare to the downside for the Aussie. The base scenario isthat China sees some slowing, but growth remains above7%. It wont be a source of bad news, but it wont boost theAussie. But if a more negative scenario plays out it will be
FIGURE 1: YUAN TREND
The yuans steady appreciation vs. the U.S. dollar pushed the USD/CNY to new
lows in early 2014.
Source: TradeStation
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9/31CURRENCY TRADER February 2014 9
more negative for commodity produc-ers, like the Aussie. The Aussie will be
more sensitive to bad news than goodnews this year.
Looking beyond the G-10 currencylandscape, Pressler warns if a creditimplosion occurs, the impact wouldbe greatest on Pacific Rim commodityproducers, such as Indonesia, Thailand,Taiwan, and Malaysia, which are pro-ducers of copper, palm oil, and rubbergoods. Pressler also notes if Chinaslows down and global commodityprices dip, it would benefit the U.S.
He cites the example of commodityprices prior to the 1997 Asian financialcrisis. Commodity prices were run-ning briskly until the crisis, and thenmajor consumers fell into deep reces-sion and we saw a significant slow-down, he explains. Their currenciesdropped by 40%. Oil fell to $14 barrel.As a developed country, we benefitedfrom the Asian recession.
General playsBarring some type of credit crisis,
the Australian dollar remains the toppick for a China play among analysts,although Callow says that withinAsia, the Singapore dollar (SGD) andKorean won (KRW) should track thegeneral mood on China (Figure 3).The Aussie dollar is the most popularproxy for the Chinese economy amongthe free-floating currencies, Callowsays. The New Zealand dollar is alsosomewhat sensitive now that China hasovertaken Australia to become NewZealands largest trading partner.y
FIGURE 2: AUSSIE DOLLAR
Some analysts believe the Australian dollar is the major currency that is most
susceptible to the China story.
Source: TradeStation
FIGURE 3: CHINA PROXIES
The Singapore dollar (top) and Korean won (bottom) should also track China,
if not to the same extent as the Aussie dollar.
Source: ADVFN.com
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10/31
By mid-January 2014, FX traders were getting bored bythe main themes in the market Fed tapering, Europeandeflation, iffy Chinese growth. Just as FX traders werecasting around for some new factors to chew on, equitytraders decided to panic about deteriorating conditions inemerging markets.
The tendency toward contagion in stock markets was ondisplay in all its glory. In a single day (Friday, Jan. 24), theETF on the MSCI emerging markets index fell 2.6% on anopening gap (Figure 1). The Dow dropped 1.96%, the S&P,
2.09%, and the Europe Stoxx 600, 2.39%.Its uncertain yet whether the one-day sell-off will be a
buy-the-dip opportunity or the start of something bigger,but its a Shock and has the potential to change the globalfinancial environment for the entire year. Not only coulda bear market in equities emerge, the Fed may decide topostpone or cut back tapering.
Its interesting that on Jan. 24, the only major stock mar-ket that posted a gain was the Shanghai, which is espe-cially ironic because a sub-par HSBC flash PMI was one ofthe drivers contributing to the emerging-markets panic. Tobe fair, nobody really knows whether it was the Chinese
PMI, Turkish lira crash, Argentinas devaluation, or some-thing else that was the tipping point. But a critical mass
was reached.
Emerging markets and FX
Emerging-market stock markets are joined atthe hip with currencies. Political problems inTurkey drove the lira to an all-time low. Therewere street riots in Bangkok, although the bahtand SET stock index fell by only a little. TheArgentine peso fell 15% (including an officialdevaluation), the Russian ruble fell to a five-
year low, and the South African rand fell to itslowest level since June 2008.
Meanwhile, advanced-country currencies thatsometimes act like emerging-market currencieswere also on the defensive the Canadianand Australian dollars were already fallingdramatically, and fell some more on the keydays. The flight to safety in the Swiss franc andyen was immediate and powerful. The Swissfranc gained 1.88% and the dollar/yen rate lost2.08% during the last two days of the week(Jan. 23 and 24).
On the Money
10 February 2014 CURRENCY TRADER
ON THE MONEY
Seeds of a classic
panic maybe
Was the market disruption toward the end of January a chink
in the markets armor, or just another pullback?
BY BARBARA ROCKEFELLER
FIGURE 1: MSCI EMERGING MARKETS INDEX
Led by emerging markets, equity markets took a hard hit on Jan. 24.
Source: Chart Metastock; data Reuters and eSignal
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11/31CURRENCY TRADER February 2014 11
You cant hear Thailand-Argentina-Russiawithout remembering the emerging-market crashof 1997-98. Flight out of emerging-market cur-rencies, equities, and bonds led in fairly shortorder to default by Argentina and Russia, withhigh-profile hedge fund Long-Term CapitalManagement failing in 1998. LTCM underwenta dramatic $3.625 billion rescue by a consortiumorganized by the New York Fed (resulting oneof the best books on finance, When Genius Failed:The Rise and Fall of Long-Term Capital Managementby Roger Lowenstein). It was the first big taste
of moral hazard, and it set off a flurry of aca-demic papers by everybody and his brother,including the BIS, numerous PhD theses, and theFed itself.
Moral hazard wasnt the only concept to gomainstream from the Asian crisis of 1997-98.
FIGURE 2: S&P 500
Although the Jan. 24 sell-off dropped the S&P only to its mid-December
level, the index held above its 100- and 200-day moving averages.
Many times, markets just test support levels before
resuming the trend on a large scale. If you know
where the support levels are, you can watch the
market as it tests the support levels with ease. You
will not be scared and prematurely exit the market,
but will be able to continue to profit as the market
goes up. Thats exactly what AbleTrend provides.
Award-winning AbleTrendsupport levels are
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as prices change. Because they are determined by
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THESE RESULTS ARE BASED ON SIMULATED OR HYPOTHETICAL PERFORMANCE RESULTS THAT HAVE CERTAIN INHERENT LIMITATIONS. UNLIKE THE RESULTS SHOWN IN AN ACTUAL PER-FORMANCE RECORD, THESE RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, BECAUSE THESE TRADES HAVE NOT ACTUALLY BEEN EXECUTED, THESE RESULTS MAY HAVE UNDER-OROVER-COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED OR HYPOTHETICAL TRADING PROGRAMS IN GENERAL ARE ALSOSUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS ORLOSSES SIMILAR TO THESE BEING SHOWN. THE TESTIMONIAL MAY NOT BE REPRESENTATIVE OF THE EXPERIENCE OF OTHER CLIENTS AND THE TESTIMONIAL IS NO GUARANTEE OF FUTUREPERFORMANCE OR SUCCESS. TECHNICAL ANALYSIS OF STOCKS & COMMODITIES LOGO AND AWARD ARE TRADEMARKS OF TECHNICAL ANALYSIS, INC.
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ON THE MONEY
There was also contagion and asymmetricinformation, the one-note pony phenomenonthat underlies the herd mentality and leads tofinancial market disruptions disproportionateto the true underlying financial and economic
conditions.
Perspective on U.S. equities
How should we put the Jan. 24 global sell-offin perspective? After all, in the U.S. the S&Psone-day decline of 2.09% is a drop in the bucketof its 600-point gain over the past two years.The move dropped the S&P only to its mid-December level, and the chart shows the indexholding above the 100-day and 200-day movingaverages, if below the 55-day (Figure 2).
Besides, in 1998, the S&P did not suffer con-
tagion: After a minor dip from July to October,it went on to higher levels until its March 2000peak, and almost everyone agrees the pullbackafter that was the result of a belated recognitionof the ridiculous valuations accorded to high-tech companies. (The pullback was dubbed theTech Wreck.) Therefore, based on this recenthistory, the U.S. and presumably other devel-oped equity markets can probably escape directcontagion from emerging-market woes.
The problem is that once a sell-off begins,the sell-off is the Event. Risk-averse market
sentiment pays no heed to its origin. Chatterdevelops about non-EM reasons for U.S. equi-ties to correct, and some of them are fairlyconvincing. Robert Shiller, for example, offerssomething called a cyclically adjusted P/Eratio, or CAPE. This divides the current priceby the average inflation-adjusted earningsover the previous 10 years. Historically, marketpeaks tend to occur at around 29 times CAPE.And CAPE is pretty high right now at a 25.4multiple, implying a pullback from overvalu-
FIGURE 4: US 10-YEAR NOTE YIELD INDEX
The 10-year Treasury yield fell from above 3% at the end of December
to 2.735% on Jan. 24.
FIGURE 3: PIMCO EMERGING MARKETCURRENCY FUND (WEEKLY)
The PIMCO Emerging Market Currency Fund gained a 54% between
March 2009 and May 2011, but in November 2011 it dipped sharply and
rallied just as abruptly to a lower peak in May 2013.
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ation would be warranted. Note that in March 2000 as themarket was about to experience the Tech Wreck, the CAPEmultiple was 43.
Combine a peaky P/E with the prospect of the Fed rais-ing rates, even if more than a year away, and its no won-
der equity analysts are worried the EM crisis is just a trig-ger for a bigger and more long-lasting pullback, perhaps ofbear proportions. Then add to this fear the idea that somemajor U.S. companies are dependent on foreign earnings,including earnings from emerging markets, that may nowdisappoint.
A really interesting tidbit comes from seekingalpha.com Googles non-U.S. revenues are higher than domesticrevenues by a giant $4 billion in the first nine months of2013. The currencies that pose the most risk to Google for-eign earnings are the Japanese yen, the Brazilian real, andthe Euro or two out of three from the EM basket.
The underlying conditions that led up to the EM sell-offwere in the making for some time before the blow-out.Turkey and Thailand had been having political problems(over corruption and inefficiency) for weeks and evenmonths. In fact, Turkey was eerily like Thailand in 1997 a construction bubble fueled by foreign credit that turnedhot faster than anyone had imagined. Its also importantto note that some parties getting tarred by the EM brush,such as South Korea, are blameless and dont deserve acurrency and equity market sell-off. Thats the toxic natureof contagion. But once a giant sell-off has occurred, theactual causes are no longer the important thing.
All kinds of observations everyone had been ignoringsuddenly become relevant. We knew ultra-low returns hadbeen luring yield-hungry investors into various high-riskasset classes and sectors for some time since the Fedsquantitative easing began in 2008, to be precise (Figure3). The PIMCO Emerging Market Currency Fund hadgained a whopping 54% between March 2009 and its May2011 peak, but it then dipped sharply in November 2011and rallied just as abruptly to a lower peak in May 2013.The current drop echoes the drop in May, when the Fedannounced tapering was imminent. In May, the countries
most affected included India and Brazil. Now that Indiahas a highly respected new Reserve Bank chief, the rupeeand the Sensex suffered relatively less effect on the crashday. This tells us something valuable that traders arenot totally indiscriminate. If the South Korean won was the
biggest loser on Jan. 24, as Bloomberg reports, it could bebecause the country was being used as a proxy for expo-sure to China. Selling South Korea (and Taiwan) was actu-ally selling China, which is notoriously hard to do.
The new round of risk aversion was actually becomingvisible on the chart of the 10-year Treasury yield for abouttwo weeks ahead of the EM crisis (Figure 4). The yield fellfrom above 3% at the end of December to 2.735% on Jan.24. This was likely more a result of the U.S. stock marketputting in a bad first five days, traditionally a harbingerof a bad month, plus the usual market jibber-jabber abouttoo-high P/Es, disappointing sales or earnings, and so on.
But the reason the stock indices had gained so much overthe previous two years was the search for yield in a worldwhere bonds returned so little the same motivation as inemerging markets.
In fact, falling sovereign bond yields in many placesindicate risk aversion was starting to get a grip for severalweeks before the EM crisis. In the UK, the 10-year Giltyield fell from 3.03% at year-end to 2.77% on Jan. 24, whilethe German Bund yield fell from 1.94% to 1.66%. Irishyields fell to 3.31% after Irelands first post-bailout issu-ance in January was well received. Portugal also made anew five-year offering in January, with the 10-year yield
falling from 6.2% at year-end to 3.80% on Jan. 24. Analyststook the drop in peripheral European sovereign yields tomean the debt crisis was behind us, but now that we havethe EM crisis, you have to wonder if flight from Turkeyhelped, say, Portugal. Also, it remains to be seen whetherthe peripherals will continue to be considered part of thedeveloped basket or slide into the EM basket.
Logically, if equity investors are fleeing emerging mar-kets, the U.S. should be the number one bolt-hole. Afterall, U.S. equity markets comprise about 34% of total worldmarket capitalization, more than any other single coun-
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try. At the end of 2012 U.S. equity markets represented$18.7 trillion in market cap, vs. $54.6 trillion for the worldand $11.762 trillion for the top-22 European countries,including Switzerland and the UK (www.quandl.com/
economics/stock-market-capitalization-all-countries).The Economist magazine (Jan. 18, 2014 issue) publisheda world map showing that, apart from government own-ership, many emerging-market stock markets are reallytiny. For example, all the equities of India are worth aboutthe same as Nestle. Egypts market cap is the equivalentto Burger King. The Russian stock market is the size ofProctor & Gamble, Mexico is comparable to IBM, andVenezuela is equivalent to Merck.
The first lesson is that emerging economies have smalland illiquid markets. The second lesson is that theresreally not really much money available to be siphoned
from EM markets to developed country markets, includingthe U.S.
If investors generally are fleeing emerging-market cur-rencies, the U.S. dollar should benefit as a safe haven,alongside the traditional Swiss franc, and home-countryadvantage for the Japanese, the yen. As the emerging-market crisis exploded on Jan. 23 and Jan. 24, however, thedollar tanked (Figure 5). As with the S&P, the fall in thedollar index is not fatal from a chart perspective yet.The dollar is tracking the 10-year yield and not followingthe conventional risk-aversion playbook.
Commodities oddities
The case of the curiously falling dollar brings us to thesubject of commodities and the intermarket correlationgremlins. We expect equities and bonds to move inversely
thats a classic relationship. We also expect commoditiesto move inversely to equities, if they are correlated at all,but so far the gains in the CRB index and even oil and goldare not proportionate to the drop in equities.
The time to get worried about contagion from theemerging-market crisis will be when these normal relation-ships do not behave as expected, and we might be seeingthe start of that. In other words, equities could be fallingbut commodities could be falling, too.
The underlying reason for commodities to be losing theirappeal is the commodity super-cycle may be ending.The landscape for oil changed when the U.S. got an 18%
rise in domestic production in 2013 back to levels notseen in 25 years. The International Energy Agency says theU.S. will be the top producer by 2015. In fact, in the firsteight months of 2013, the U.S. was able to produce 86% ofits energy needs from all sources (natural gas, petroleum,nuclear ,and renewables such as wind and solar). This is agame-changer.
Another game-changer is the 2013 slowdown in Chinesegrowth from double digits to 7.7%. No one knows how bigChinese commodity stockpiles are, but they are not negli-gible for things like copper and aluminum. As the Chinese
government institutes reforms, including reining in the
FIGURE 5: DOLLAR INDEX
As the emerging-market crisis exploded on Jan. 23 and Jan. 24, the
dollar tanked.
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shadow banks that fund uneconomic building and manu-facturing projects, demand for commodities from Chinacould well be in decline. In fact, for all anyone knows, the
build-up of commodity inventories in China may havebeen financed by the very shadow banks that are nowunder the gun. We shouldnt be surprised. Financing illiq-uid assets that are long-term by nature with short-termfunding is a classic beginners mistake. At a guess, Chinaintends to manage the contraction of its shadow bankingindustry (and the restructuring of the official banking sec-tor) very, very carefully. This is not to forecast a burstingbubble, but rather a cut in demand from the country thathas demanded more than half the worlds commodities inrecent years.
Until the EM crisis, the only real distress was in Canada
and Australia, two countries that are sane and well-man-aged. But both countries face recessionary and deflationaryconditions coupled with real estate booms that might wellbe bubbles, and thus endanger the banking system downthe road. The solution? Jawboning the currency lower topromote exports and give manufacturing whatever minorboost it can use, even if cutting rates is not on the tablebecause it would exacerbate the housing bubble. However,a housing bubble is only a mask for excessive householddebt, which means the central bank might be better offraising rates to cool down housing at the expense of
that weak sector, manufacturing (and thus, employment).Where does this leave the United States? The U.S. isactually in pretty good shape, considering it has emergedfrom its worst recession since the 1930s. The bond market,after a stumble in May and June when the first announce-ment of tapering sent yields too high, now accepts the Fedis truthful when it says lower for longer. (Overreactionwas the problem in May and June, when the initialannouncement of tapering took the yield from a low of1.614% on May 1 to 2.214% on May 31, and thence to anintermediate high of 2.725% on July 5.)
In one of his farewell speeches, Fed chief Ben Bernanke
pointed out real GDP is up in 16 of the past 17 quarters. ByQ3 2013, GDP was up 5.5% above the peak in 2008, beforethe recession hit. Unemployment dropped from 10% in2009 to 7% by the end of 2013 to. And all this in the face ofcontracting fiscal policy that took as much as 1.5% off GDP,according to the Congressional Budget Office. Bernankedidnt mention it, but households deleveraged, too. Asof the end of Q3 2013, household debt was $11.28 trillion(covering mortgages, autos, education and credit cards),from the peak of $12.68 trillion in the third quarter of 2008,according to the New York Fed. Mortgage and credit carddelinquencies are also lower.
The possibly developing emerging-market crisis couldput the kybosh on the U.S. recovery but not for reasonsoriginating in the U.S. Instead, we might be seeing the
classic features of a financial crisis, just not all in one place.One feature is excessive credit creation by incompetentbankers who are insufficiently regulated by central banksand other supervisors, so the backlog of non-performingloans gets out of hand. This is probably the case in Chinaand Turkey, for example, as well as several European coun-tries. Another contributor to a classic crisis is artificiallylow rates, whether from central bank policy or a savingsglut, which drive investors into riskier assets and sectors,including real estate in a phrase, over-leveraging andbubbles.
The other shoe
The catalyst for a wider, deeper crisis is always the fail-ure of a big financial institution, as in the September 2008Lehman Brothers collapse. Now the task is to identifywhich financial institution is going to fail. Chances are itsnot one in the U.S. the banks may not be completelyclean, but they are in sounder shape than in 2008. Chancesare its not in China, either the government there can becounted on to control (and disguise) a banking crisis.
That pretty much leaves Europe, where the banks justgot a reprieve on the timetable and amount of new capital
adequacy requirements and other balance-sheet house-cleaning. This observation is not a forecast of a Europeanbank failure, but it is a warning. Other countries can fol-low the example of the U.S. and reduce leverage, improvehousehold, corporate, and bank balance sheets, and prickhousing bubbles without the fallout reaching Americanshores, but dont count on it. Once fear gets a grip, its per-vasive and contagious.
As for the dollar, it doesnt get credit for having a health-ier and faster-growing economy, but it may get credit inthe end, so to speak, for having a more stable economicand financial environment. Unfortunately, it will probably
take some Euro-negative development to make that pointclear, such as some form of ECB easing or a European bankfailure.
Until then, the dollar is susceptible to the perception thata global crisis will stay the hand of the Fed and taperingwill be postponed or cut back.yBarbara Rockefeller (www.rts-forex.com) is an international econo-
mist with a focus on foreign exchange, and the author of the new
book The Foreign Exchange Matrix(Harriman House). For more
information on the author, see p. 4.
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Trading systems are often difficult to execute because oftheir tendency to surrender profits after a position moves
into favorable territory a problem especially noticeable
in trend-following systems. Many traders watch signifi-
cant gains evaporate and turn into losses when a trading
system fails to take action when market conditions move
against it.
There are different ways to address this problem, but
most represent some type of trade-off: Long-term profit-
ability is typically sacrificed to accommodate a rule that
takes profits in some way as to avoid the psychologically
challenging experience of watching winners turn into los-ers.
Traders can turn things in their favor by designing
systems that are easier to trade from the start. Here well
explore a trading system along these lines that uses a trail-
ing stop. Well see how the stop mechanism makes trading
easier, and examine its impact on the trading strategys
performance.
Entry rules
The system, which was generated using one-hour data in
the Euro/U.S. dollar pair (EUR/USD), uses a few simplerules to execute entries and exits:
Long entry (short exit):
1. The hour is 6 (GMT +1 (DST = GMT+2)).2. The high of the previous hourly bar is less than the
open 31 bars ago (High[1] < Open[31]).3. The open nine bars ago is greater than the high 44
bars ago (Open[9] > High[44]).
Short entry (long exit):
1. The hour is 6 (GMT +1 (DST = GMT+2)).
2. The low of the previous hourly bar is greater thanthe open 31 bars ago (Low[1] > Open[31]).
3. The open nine bars ago is less than the low 44 barsago (Open[9] < Low[44]).
Where,0, 1, 2, etc., reference the most recently closed hourly
bar, the previous bar, the bar two bars ago, etc. A newtrade is entered on a new bar whenever one of the sig-nal conditions is met.
The systems initial stop-loss is two times the 20-periodaverage true range (ATR). A trade is closed whenever a
stop-loss is hit or a signal in the opposite direction occurs.
In the case of a signal in the same direction, the stop-loss
is updated as if a new trade had been opened and the cur-
rent price bar (which would represent a new entry if there
wasnt already an open position) is used to calculate the
trailing stop, which well discuss next.
The trailing stop
The systems trailing stop adjusts to price as the market
moves in the positions favor that is, moving higheras price rises in a long trade, and moving lower as price
declines in a short trade. When price moves a specific dis-
tance in this case, two times the 20-period ATR the
system moves the trades stop-loss to break-even.
For every favorable move above this ATR profit level,
the system places (for a long position) a stop-loss two
times the 20-period ATR below the current hourly bars
open. This means once the EUR/USD pair reaches the ATR
profit threshold, price can never trade below breakeven,
but it can oscillate freely above this level and accommo-
date potential volatility bursts in the trades favor. (The
TRADING STRATEGIESTRADING STRATEGIES
Trailing stops,
curtailing lossesStarting with a trailing stop rule can make your forex system easier to trade.
BY DANIEL FERNANDEZ
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stop-loss and trailing-stop values arenot optimized.)
Figures 1 and 2 illustrate a sample
trade. Figure 1 is a close-up that high-
lights the trade-entry setup, which
resembles a consolidation pattern.
After a successful downside run,
Figure 2 shows how the short trade
was exited with the trailing stop,
which ensured only a limited portion
of the open profit was given back as
price continued to fall. The next trade(a buy) was exited at breakeven after
the EUR/USD pair failed to develop
any favorable momentum.
Testing the system
The system was tested on EUR/USD
hourly data from Jan. 1, 1988 to Jan.
1, 2014, with the Deutsche mark/U.S.
dollar rate used as a proxy prior to
1999. (Interest earned and paid through
swap rates was accounted for in thesimulation using historical interest rate
values.) The simulation used an initial
account balance of $100,000, and risked
1% of account equity on each trades
initial stop-loss amount.
The test data was split into two peri-
ods:In-sampledata from Jan. 1, 1988
to Jan. 1, 2005 was used for strategy
generation, while the final eight years
were used as an out-of-sampleperiod.
The system was generated seeking
FIGURE 1: SHORT-TRADE ENTRY, EUR/USD, 60-MINUTE
This short trade was triggered by the entry setup, which essentially identifies a
consolidation pattern.
FIGURE 2: SHORT EXIT, LONG ENTRY, EUR/USD, 60-MINUTE
The short trade was exited with the trailing stop, which prevented losing too
much of the open profit. A second, long trade was exited at breakeven.
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highly linear in-sample results (i.e.,
linear regressionR2values greater
than 0.98). Note: Other systems cre-
ated with this process yielded similar
results; this system was picked at ran-
dom from the generated pool.
System performanceFigure 3 shows the system, on a
non-compounded basis (i.e., always
risking $1,000 per trade), produced
a highly linear equity curve over the
past 26 years a period that encom-
passed a wide variety of market
conditions. Furthermore, this positive
characteristic sustained itself through
the out-of-sample period. The R2
value for the entire test in-sample
and out-of-sample was 0.96 (seethe linear regression line in the chart).
Figure 4 shows the systems com-
pounded equity curve (i.e., risking 1%
per trade).
The system produced a good
simulated track record (Table 1).
The ratio of overall average yearly
profit to maximum drawdown was
0.87 (9.19%/10.56%), with maximum
drawdown length of 807 days occur-
ring around 1995 (and a maximum
drawdown length of less than one
year over the past six years). The
out-of-sample maximum drawdown
length was 565 days. (The in-sample
and total maximum drawdown
lengths are equal because the longest
drawdown occurred in the in-sample
period.)
Figure 5 shows the systems annual
profits. There were only four los-
ing years in the 26-year test period,
18 February 2014 CURRENCY TRADER
TRADING STRATEGIES
FIGURE 4: EQUITY CURVE (COMPOUNDED)
The drawdown near the end of the test period only appears larger because of
the effect of compounding.
FIGURE 3: EQUITY CURVE (NON-COMPOUNDED)
The system generated a highly linear equity curve over the wide-ranging
simulation period.
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19/31CURRENCY TRADER February 2014 19
and although the system is currently underperforming, it
remains within the drawdown boundaries defined by the
out-of-sample test. Also, the drawdown near the end of the
test in Figure 4, only appears larger because of compound-
ing; see the linear chart in Figure 3 to compare this draw-
down with previous periods.
The system doesnt trade as much like a higher-frequen-
cy, shorter-time frame system as it does like a daily systemwith fine-tuned entries. This explains why the trailing-stop
and stop-loss values are so large (two times the 20-period
ATR) and why the system trades infrequently (0.6 trades
per week on average, with an average trade duration of six
days and 21 hours).
One favorable characteristic of this
system is its historically high math-
ematical expectancy. The system has
an overall reward-to-risk ratio of 1.39
and a winning percentage of 54%. The
combination of a reward-to-risk ratio
greater than 1.00 and a winning per-
centage above 50%, which is a function
of the trailing stop, is not very common
because it requires a very high per-
trade expectancy. This is what makes
this system psychologically easier to
trade: A system that is expected to win
more than 50% of the time is easier
to trade than one with a sub-50% win
rate.
Easier-to-trade systems using a trailing stop
The trailing stop gives us the opportunity to develop
strategies with higher mathematical expectancies, linear-
ity, and better out-of-sample testing results. When systems
are developed to complement a position-management
approach that forces an increase in the signals mathemati-
cal expectancy, a better trading strategy is the result.yDaniel Fernandez is an active trader focusing on forex strategy
analysis, particularly algorithmic trading and the mathematical
evaluation of long-term system protability.For more information on
the author, see p. 4.
FIGURE 5: ANNUAL RETURNS
There were only four losing years in the 26-year test period.
TABLE 1
All data In-sample Out-of-sample
Average yearly return 9.19% 9.98% 7.65%
Total return 809% 377% 90%
No. of trades 840 553 287Profit factor 1.64 1.8 1.55
Max. drawdown 10.56% 8.16% 10.53%
Max. drawdown length 807 days 807 days 565 days
Reward-to-risk ratio 1.39 1.48 1.38
Win percentage 54% 55% 53%
Ulcer Index 3.17 3.23 3.05
Years in test 26 17 6
The systems simulated track record had mostly positive characteristics, out of
sample as well as in sample.
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TRADING STRATEGIES
When excess becomes
predictable: The majors
Find out whether carry returns from the U.S. dollar, along the money-market yield
curve, can predict the excess of implied volatility over historical volatility.
BY HOWARD L. SIMONS
20 February 2014 CURRENCY TRADER
TRADING STRATEGIESADVANCED CONCEPTS
The course of the past four months has been examiningwhether the skew and smile of currency options could beused in conjunction with those currencies money-marketyield curves to predict carry returns from the USD intoindividual currencies. In general, the skew of the optionscurve as measured by risk reversals proved useful, whilethe smile of the options curve as measured by the butterflydid not.
Now lets turn the tables and ask whethercarryreturns
from the USD in conjunction with the money-market yield
curve can be used to predict the excess of implied vola-
tilityover historical volatility.Readers may be familiar
with excess volatility, the markets demand for insurance,
defined as the ratio of the implied volatility for three-
month non-deliverable forwards to high-low-close (HLC)
volatility, minus 1.00.HLC volatility is defined as:
[[.5* (ln(max(H,Ct1)
min(L,Ct1)
))2 .39*(ln( CC
t1
))2]*260
N]1/2
i=1
N
Where Nis the number of days between 4 and 29 thatminimizes the function:
1
N*
N
Vol2
i=1
N
* | (P MA) |* |MA |
FIGURE 1: THE EURO AND 90-DAYEXCESS VOLATILITY
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
70%
80%
1.98
2.00
2.02
2.04
2.06
2.08
2.10
2.12
Jan-06
Jul-06
Feb-07
Sep-07
Apr-08
Oct-08
May-09
Dec-09
Jul-10
Jan-11
Aug-11
Mar-12
Oct-12
May-13
Nov-13
90-DayEx
cessVolatilityLed3Months
Log10
USDCarryReturnIntoEUR,
Jan.4,2006=2.00
Excess Volatility
Carry
FIGURE 2: THE JAPANESE YEN AND90-DAY EXCESS VOLATILITY
-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
1.94
1.96
1.98
2.00
2.02
2.04
2.06
2.08
2.10
2.12
2.14
Jan-06
Jul-06
Feb-07
Sep-07
Apr-08
Oct-08
May-09
Dec-09
Jul-10
Jan-11
Aug-11
Mar-12
Oct-12
May-13
Nov-13
90-DayExcessVolatilityLed3Months
Log10
USDC
arryReturnIntoJPY,
Jan.
4,
2006=2.0
0Excess Volatility
Carry
http://www.currencytradermag.com/index.php/c/Key%20Concepts#CDhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#CDhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#UVhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#UVhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#UVhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#UVhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#UVhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#UVhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#UVhttp://www.currencytradermag.com/index.php/c/Key%20Concepts#CD8/12/2019 CurrencyTrader0214-jp4p
21/31CURRENCY TRADER October 2010 21CURRENCY TRADER February 2014 21
As our target now is to predict a measure of excess volatil-
ity with the ultimate objective of trading it, lets switch from
this dynamic measure to a simple ratio of 90-day volatility
to 90-day realized volatility, minus 1.00. The first section of
the following discussion will be devoted to mapping returnson the major currencies as the common logarithm of the total
carry return from the U.S. dollar into those currencies rein-
dexed to January 2006. This both approximates the return
path of a continuous currency future and allows for the more
intuitively appealing rising line depicting a stronger currency.
The second section will look at this measure of excess
volatility as a function of the carry return over the past three
months and of the lagged value of the money-market yield
curve as measured by the forward rate ratio between six and
nine months (FRR6,9) for the major currencies. The FRR6,9is
the rate at which we can lock in borrowing for three monthsstarting six months from now, divided by the nine-month rate
itself. The steeper the yield curve, the more this ratio exceeds
1.00; an inverted yield curve has an FRR6,9less than 1.00.
Excess volatility and returns
The Euros excess volatility appears to be an asymmetric
process with positive spikes greatly exceeding negative ones
(Figure 1). The general ebb and flow of excess volatility with
a three-month lag to carry returns is expected, but the increas-
ing demand for insurance when carry returns rose in early
2008, 2009, and again in mid-2011 is somewhat surprising.This pattern of increasing anxiety in the face of a currencys
strength is far more common for emerging market and minor
currencies, not for what is still the second-most important
currency in the global system.
Critically, when carry returns start to rise from low levels,
excess volatility tends to rise as well; this suggests option
strategies involving long Euro volatility positions would
work.
The yens excess volatility was symmetric prior to the adop-
tion of quantitative easing by the U.S., UK, and Switzerland
in March 2009 (Figure 2). It then shifted to an asymmetric
FIGURE 3: THE CANADIAN DOLLAR AND90-DAY EXCESS VOLATILITY
-35%
-25%
-15%
-5%
5%
15%
25%
35%
45%
55%
65%
1.92
1.94
1.96
1.98
2.00
2.02
2.04
2.06
2.08
2.10
Jan-06
Jul-06
Feb-07
Sep-07
Apr-08
Oct-08
May-09
Dec-09
Jul-10
Jan-11
Aug-11
Mar-12
Oct-12
May-13
Nov-13
90-DayExcessVolatilityLed3
Months
Log10
USDC
arryReturnIntoCAD,
Jan.
4,
2006=2.0
0
Excess Volatility
Carry
FIGURE 4: THE AUSTRALIAN DOLLAR AND90-DAY EXCESS VOLATILITY
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
1.92
1.94
1.96
1.98
2.00
2.02
2.04
2.06
2.08
2.10
2.12
2.14
2.16
2.18
2.20
2.22
2.24
2.26
2.28
Jan-06
Jul-06
Feb-07
Sep-07
Apr-08
Oct-08
May-09
Dec-09
Jul-10
Jan-11
Aug-11
Mar-12
Oct-12
May-13
Nov-13
90-DayE
xcessVolatilityLed3Months
Log10
USDC
arryReturnIntoAUD,J
an.
4,
2006=2.0
0
Excess Volatility
Carry
FIGURE 5: THE SWISS FRANC AND90-DAY EXCESS VOLATILITY
-45%
-35%
-25%
-15%
-5%
5%
15%
25%
35%
45%
55%
65%
75%
1.98
2.00
2.02
2.04
2.06
2.08
2.10
2.12
2.14
2.16
2.18
2.20
2.22
Jan-06
Jul-06
Feb-07
Sep-07
Apr-08
Oct-08
May-09
Dec-09
Jul-10
Jan-11
Aug-11
Mar-12
Oct-12
May-13
Nov-13
90-DayExcessVolatilityLed3Months
Log10
USDC
arryReturnIntoCHF,
Jan.
4,
2006=2.0
0 Excess Volatility
Carry
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ON THE MONEYON THE MONEY
22 February 2014 CURRENCY TRADER
ADVANCED CONCEPTS
pattern as Japan began a series of attempts to drive the JPY
lower in late 2012 and early 2013. These attempts pushed
excess volatility to negative levels as implied volatility
declined in the face of predictable policy.
The pattern for the Canadian dollar has been very dif-ferent (Figure 3). Not only has excess volatility been a
symmetric affair, its positive spikes have been unrelated to
changes in the CADs carry return. However, just as in the
case of the EUR, shifts higher in the carry return have led
to shifts higher in the excess volatility measure. A stronger
CAD invites a long volatility position.
The pattern for the Australian dollar retains both the
symmetry of the Canadian dollars excess volatility and its
tendency to move higher after carry returns move higher,
but adds irregular episodes of positive spikes following
gains in the AUDs carry return (Figure 4).We should expect the pattern for the Swiss franc to have
been distorted by the September 2011 imposition of the
franc ceiling and simultaneous pledge to print the CHF
in unlimited quantities to enforce that pledge (Figure 5).
Excess volatility plunged to deeply negative levels on the
imposition of the ceiling and then jumped as 90-day real-
ized volatility, the fractions denominator, fell.
The Swedish krona had one of the cleanest patterns and
direct linkages to carry returns of any currency prior to
the May 2010 backstopping of Greece (Figure 6). Then the
SEK became a safe-haven currency, albeit not as much asthe CHF was, and implied volatility fell as the carry return
moved higher. The market simply accepted the SEKs
strength and did not fear a Swiss-like response to it.
Finally, the linkage between the carry into the British
pound and its excess volatility has been very direct
throughout the data sample (Figure 7). Excess volatility
has been asymmetric in a manner very similar to Japans
since the U.K. began its quantitative easing program in
March 2009. While the U.K. has not engaged in direct and
public campaigns to weaken the GBP as Japan has with
FIGURE 8: 90-DAY EXCESS VOLATILITYFOR THE EURO
FIGURE 6: THE SWEDISH KRONA AND
90-DAY EXCESS VOLATILITY
-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
1.90
1.92
1.94
1.96
1.98
2.00
2.02
2.04
2.06
2.08
2.10
2.12
Jan-06
Jul-06
Feb-07
Sep-07
Apr-08
Oct-08
May-09
Dec-09
Jul-10
Jan-11
Aug-11
Mar-12
Oct-12
May-13
Nov-13
90-DayExcessVolatilityLed3Months
Log10
USDC
arryReturnIntoSEK,
Jan.
4,
2006=2.0
0
Excess Volatility
Carry
FIGURE 7: THE BRITISH POUND AND 90-DAYEXCESS VOLATILITY
-25%
-15%
-5%
5%
15%
25%
35%
45%
55%
65%
75%
1.90
1.92
1.94
1.96
1.98
2.00
2.02
2.04
2.06
2.08
Jan-06
Jul-06
Feb-07
Sep-07
Apr-08
Oct-08
May-09
Dec-09
Jul-10
Jan-11
Aug-11
Mar-12
Oct-12
May-13
Nov-13
90-DayExces
sVolatilityLed3Months
Log10
USDCarryReturnIntoGBP,Jan.4,2006=2.00
Excess Volatility
Carry
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23/31CURRENCY TRADER October 2010 23CURRENCY TRADER February 2014 23
the yen, no one has had to question the bias of British mon-
etary policy.
Leading indications of excess volatility
Now lets look at excess volatility for each of the majorcurrencies as a function of the previous three months
carry return and three-month-ago values of its FRR6,9. In
Figures 8 through 14, positive levels of excess volatility
are depicted with green bubbles, negative levels with red
bubbles; the diameter of the bubble corresponds to the
absolute magnitude of the excess volatility level. The last
datum used is highlighted and the current environment is
depicted with a crosshair.
The map for the Euro affirms the earlier observation neg-
ative carry returns lead positive movements in excess vola-
tility (Figure 8). Observations of negative excess volatilitycluster in zones of positive carry returns combined with
slightly inverted yield curves. This cluster is too isolated
and too small to be of much direct trading use.
The yen has a large band of negative excess volatility
readings at FRR6,9levels less than 0.90; these become inter-
spersed with positive observations once the previous three
months carry moves over 5.0% (Figure 9). The region of
the map with FRR6,9levels between 0.90 and 1.25 is domi-
nated heavily by positive excess volatility levels. These
defined clusters suggest direct volatility-trading strategies
are available.The CADs map is somewhat discouraging for volatil-
ity trading (Figure 10). The clusters of excess volatility are
very well-defined but they are too interspersed with each
other to invite direct long- or short-volatility positions.
The Australian dollar, however, has an almost direct
split along the dimension of the yield curve for positive
and negative excess volatility levels (Figure 11). If the AUD
FRR6,9was below 1.05, implied volatility was relatively
cheap. Interestingly, the previous three-month carry returns
were largely irrelevant for the AUD.
FIGURE 11: EXCESS VOLATILITY FOR THEAUSTRALIAN DOLLAR
FIGURE 10: EXCESS VOLATILITY FOR THECANADIAN DOLLAR
FIGURE 9: EXCESS VOLATILITY FOR THEJAPANESE YEN
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ON THE MONEYON THE MONEY
24 February 2014 CURRENCY TRADER
ADVANCED CONCEPTS
We can and probably should ignore the Swiss franc
unless we have reason to believe future policies will be
as dominant as the franc ceiling has been (Figure 12).
The large cluster of negative excess volatility levels in the
northwest corner of the map were the direct result of the
unusual market conditions created in September 2011.
The map for the Swedish krona has two well-defined
zones based on previous returns outside of an absolute
15% range (Figure 13). Positive carry returns lead to
negative excess volatility and vice versa.Finally, the map for the British pound has clean divi-
sions along both dimensions (Figure 14). With the excep-
tion of a small cluster of negative excess volatility, a GBP
FRR6,9greater than 0.90 following negative carry returns
is associated with positive excess volatility. Flatter yield
curves have the same mean-reverting division at abso-
lute previous carry returns greater than 15% as seen for
the SEK. The available data sample suggests the GBP is
highly amenable to volatility trading.
The response of excess volatility to both the yield
curve and carry returns seen for the majors should not
be surprising. Both the very steep yield curves seen in
recent years and the less common inverted yield curves
are responses to monetary policies often seen as tempo-
rary and unstable; these opinions lead traders to insure
themselves against policy reversals. Similarly, many
strong currency moves in either direction are the result of
policies as well.
It would be nicer if the responses seen across curren-
cies were more uniform and less anecdotal, but this may
be asking far too much in a world where central banks
and governments dominate short-term interest rate and
currency markets. The key for traders is interpretingwhether markets find the latest policy moves stable or
not. If not, implied volatility will rise and dictate a long
volatility position; if so, short volatility positions are in
order.
The responses of selected minor currencies will be
examined next month.yHoward Simons is president of Rosewood Trading Inc. and a
strategist for Bianco Research. For more information on the author,
see p. 4.
FIGURE 14: EXCESS VOLATILITY FOR THEBRITISH POUND
FIGURE 13: EXCESS VOLATILITY FOR THESWEDISH KRONA
FIGURE 12: EXCESS VOLATILITY FOR THESWISS FRANC
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25/31CURRENCY TRADER February 2014 25
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26/3126 February 2014 CURRENCY TRADER
CPI: Consumer price index
ECB: European Central Bank
FDD (rst delivery day): The rst
day on which delivery of a com-modity in fulllment of a futures
contract can take place.
FND (rst notice day): Also
known as rst intent day, this is
the rst day on which a clear-nghouse can give notice to abuyer of a futures contract that itntends to deliver a commodity infulllment of a futures contract.
The clearinghouse also informsthe seller.
FOMC: Federal Open MarketCommittee
GDP: Gross domestic product
ISM: Institute for supplymanagement
LTD (last trading day): The nal
day trading can take place in a
futures or options contract.
PMI: Purchasing managers index
PPI: Producer price index
Economic Releaserelease (U.S.) time (ET)
GDP 8:30 a.m.
CPI 8:30 a.m.
ECI 8:30 a.m.
PPI 8:30 a.m.
SM 10:00 a.m.
Unemployment 8:30 a.m.
Personal income 8:30 a.m.
Durable goods 8:30 a.m.Retail sales 8:30 a.m.
Trade balance 8:30 a.m.
Leading indicators 10:00 a.m.
GLOBAL ECONOMIC CALENDAR
February
1
2
3U.S.: January ISM manufacturingreportCanada: December PPI
45
6
U.S.: December trade balanceUK: Bank of England interest-rateannouncementECB: Governing council interest-rateannouncement
7
U.S.: January employment reportBrazil: January CPI and PPICanada: January employment reportLTD: February forex options;February U.S. dollar index options
(ICE)8
9
10Mexico: Jan. 31 CPI and JanuaryPPI
11 South Africa: Q4 employment report
12
13
U.S.: January retail salesAustralia: January employmentreportGermany: January CPI
Japan: January PPI
14
Germany: Q4 GDPIndia: January PPIJapan: Bank of Japan interest-rateannouncement
15
16
17 Japan: Q4 GDP
18Hong Kong: November-Januaryemployment reportUK: January CPI and PPI
19U.S.: January PPI and housing startsSouth Africa: January CPIUK: January employment report
20
U.S.: January CPI and leadingindicatorsBrazil: January employment reportFrance: January CPIGermany: January PPI
21
Canada: January CPIHong Kong: January CPIMexico: Q4 GDP and Januaryemployment report
22
23
24
25Mexico: Feb. 15 CPISouth Africa: Q4 GDP
26 Hong Kong: Q4 GDP
27
U.S.: January durable goodsBrazil: Q4 GDPGermany: January employmentreportSouth Africa: January PPI
28
U.S.: Q4 GDP (second)Canada: Q4 GDPFrance: January PPIIndia: Q4 GDP and January CPIJapan: January employment reportand CPI
March
12
3U.S.: January personal income andFebruary ISM manufacturing reportCanada: January PPI
4
5
U.S.: Fed beige bookAustralia:Q4 GDPCanada: Bank of Canada interest-rate announcement
The information on this page is sub-
ect to change. Currency Traderis
not responsible for the accuracy of
calendar dates beyond press time.
Event:The Traders Expo New YorkDate:Feb. 16-18Location:New YorkFor more information:Go towww.moneyshow.com
Event: 39th Annual InternationalFutures Industry ConferenceDate: March 11-14Location: Boca Raton Resort & Club, Boca Raton, Fla.For more information: Go to www.futuresindustry.org
Event:The MoneyShow Las VegasDate:May 12-15Location:Caesars Palace, Las VegasFor more information:Go to www.moneyshow.com
Event:The MoneyShow San FranciscoDate:Aug. 21-23Location:San FranciscoFor more information:Go towww.moneyshow.com
EVENTS
8/12/2019 CurrencyTrader0214-jp4p
27/31CURRENCY TRADER February 2014 27
CURRENCY FUTURES SNAPSHOTas of Jan. 31
The information does NOT constitute trade
signals. It is intended only to provide a brief
synopsis of each markets liquidity, direction,
and levels of momentum and volatility. See
the legend for explanations of the different
fields. Note: Average volume and open
interest data includes both pit and side-by-
side electronic contracts (where applicable).
LEGEND:
Volume: 30-day average daily volume, in
thousands.
OI: 30-day open interest, in thousands.
10-day move: The percentage price move
from the close 10 days ago to todays close.20-day move: The percentage price move
from the close 20 days ago to todays close.
60-day move: The percentage price move
from the close 60 days ago to todays close.
The % rank fields for each time window
(10-day moves, 20-day moves, etc.) show
the percentile rank of the most recent move
to a certain number of the previous moves of
the same size and in the same direction. For
example, the % rank for the 10-day move
shows how the most recent 10-day move
compares to the past twenty 10-day moves;
for the 20-day move, it shows how the most
recent 20-day move compares to the pastsixty 20-day moves; for the 60-day move,
it shows how the most recent 60-day move
compares to the past one-hundred-twenty
60-day moves. A reading of 100% means
the current reading is larger than all the past
readings, while a reading of 0% means the
current reading is smaller than the previous
readings.
Volatility ratio/% rank: The ratio is the short-
term volatility (10-day standard deviation
of prices) divided by the long-term volatility
(100-day standard deviation of prices). The
% rank is the percentile rank of the volatility
ratio over the past 60 days.
BarclayHedge Rankings:Top 10 currency traders managing more than $10 million
(as of Dec. 31 ranked by December 2013 return)
Trading advisorDecember
return2013 YTD
return
$ Undermgmt.
(millions)
1 Gedamo (FX Alpha) 4.71% 22.80% 39.9
2 Alder Cap'l (Alder Global 20) 3.60% 17.40% 504.0
3 CenturionFx Ltd (6X) 3.50% 40.63% 41.3
4 Sequoia Capital Fund Mgmt (FX) 2.90% 3.46% 77.85 DynexCorp (Currency) 2.27% 9.39% 30.0
6 Alder Cap'l (Alder Global 10) 2.20% 9.37% 15.0
7 Gedamo (FX One) 2.01% 12.68% 51.6
8 Trigon (Foreign Exchange) 1.76% 0.44% 103.4
9 FDO Partners (Emerging Markets) 1.28% 7.82% 2135.0
10 Cambridge Strategy (Emerging Mkts) 1.12% -0.29% 561.0
Top 10 currency traders managing less than $10M & more than $1M
1 Investment Capital Adv (Managed Acts) 15.30% 104.73% 5.5
2 Fornex (Foyle) 6.28% 43.55% 4.0
3 Gloranis GmbH (Forex Private 1) 2.43% 3.26% 2.34 Blue Fin Capital (Managed FX) 2.10% 0.92% 2.0
5 AG Bisset (Defensive Alpha) 1.60% -17.49% 1.0
6 Smart Box Capital (Leveraged FX) 0.99% -19.31% 1.1
7 Hartswell Capital Mgmt (Athena) 0.78% 9.87% 1.1
8 Cambridge Strategy (Extended Mkts) 0.73% -10.57% 4.0
9 Altus Trading (Managed Forex A) 0.67% 5.68% 2.2
10 Orwell Capital (Currency Alpha) 0.64% 0.19% 8.5
Based on estimates of the composite of all accounts or the fully funded subset method.
Does not reflect the performance of any single account.
PAST RESULTS ARE NOT NECESSARILY INDICATIVE OF FUTURE PERFORMANCE.
Market Sym Exch Vol OI10-day
move / rank
20-day
move / rank
60-day
move / rank
Volatility
ratio / rank
EUR/USD EC CME 176.0 241.4 -0.95% / 88% -1.23% / 61% -0.25% / 5% .58 / 93%
JPY/USD JY CME 129.0 224.0 1.93% / 77% 2.30% / 75% -3.69% / 52% .31 / 48%
GBP/USD BP CME 88.4 198.5 0.47% / 40% 0.09% / 0% 2.90% / 41% .32 / 90%
AUD/USD AD CME 78.9 123.3 -0.69% / 23% -1.61% / 25% -8.02% / 93% .12 / 3%CAD/USD CD CME 60.8 152.6 -1.83% / 33% -4.10% / 95% -6.33% / 98% .25 / 15%
MXN/USD MP CME 32.2 117.5 -0.43% / 11% -1.03% / 50% -2.54% / 49% .38 / 28%
CHF/USD SF CME 29.8 44.9 -0.31% / 0% -0.75% / 27% 0.24% / 6% .63 / 98%
U.S. dollar index DX ICE 20.9 44.8 0.05% / 13% 0.55% / 35% 1.05% / 59% .69 / 100%
NZD/USD NE CME 11.5 20.5 -3.20% / 100% -0.96% / 43% -2.46% / 85% .84 / 100%
E-Mini EUR/USD ZE CME 5.1 4.9 -0.95% / 88% -1.23% / 61% -0.25% / 5% .58 / 93%
Note: Average volume and open interest data includes both pit and side-by-side electronic contracts (where applicable). Price activity is
based on pit-traded contracts.
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28/31
INTERNATIONAL MARKETS
28 February 2014 CURRENCY TRADER
CURRENCIES (vs. U.S. DOLLAR)
Rank CurrencyJan. 30
price vs.U.S. dollar
1-monthgain/loss
3-monthgain/loss
6-monthgain/loss
52-weekhigh
52-weeklow
Previous
1 Japanese yen 0.00973 2.31% -4.89% -4.70% 0.011 0.0095 17
2 New Zealand dollar 0.827185 1.50% 0.06% 2.57% 0.8619 0.7704 9
3 Swedish krona 0.15526 1.08% -1.18% 0.46% 0.159 0.1464 7
4 Great Britain pound 1.65711 0.53% 3.01% 7.79% 1.6588 1.4877 2
5 Taiwan dollar 0.033415 0.41% -1.74% 0.00% 0.0341 0.0326 12
6 Chinese yuan 0.16386 0.18% 0.38% 1.17% 0.1642 0.1588 6
7 Hong Kong dollar 0.128805 -0.11% -0.13% -0.09% 0.129 0.1288 8
8 Thai baht 0.030385 -0.25% -5.62% -5.31% 0.0348 0.0302 14
9 Singapore dollar 0.78473 -0.44% -2.75% -0.67% 0.8136 0.7792 11
10 Euro 1.365875 -0.66% -0.82% 2.90% 1.3802 1.2798 3
11 Swiss franc 1.113775 -0.73% -0.10% 3.50% 1.1277 1.0274 1
12 Indian rupee 0.016 -1.02% -2.02% -4.93% 0.0188 0.0147 5
13 Australian Dollar 0.87768 -1.04% -7.72% -5.01% 1.0545 0.8677 16
14 Brazilian real 0.41131 -3.82% -10.31% -7.13% 0.5137 0.4082 15
15 Canadian dollar 0.8969 -3.97% -6.31% -7.89% 1.0035 0.8968 10
16 South African rand 0.090295 -4.85% -10.96% -11.57% 0.1134 0.0897 13
17 Russian ruble 0.028675 -6.52% -8.27% -5.94% 0.0337 0.028675 4
GLOBAL STOCK INDICES
Country Index Jan. 301-monthgain/loss
3-monthgain/loss
6-monthgain loss
52-weekhigh
52-weeklow
Previo
Italy FTSE MIB 19,411.60 2.34% 1.28% 17.34% 19,697.20 15,056.60 9
2 Canada S&P/TSX composite 13,735.30 1.13% 2.08% 9.17% 14,002.40 11,759.00 7
3 Switzerland Swiss Market 8,205.00 0.02% -0.28% 5.05% 8,544.10 7,247.30 11
4 Germany Xetra Dax 9,373.48 -1.87% 4.03% 13.33% 9,794.05 7,418.36 4
5 South Africa FTSE/JSE All Share 45,178.25 -2.07% -0.95% 10.21% 47,045.44 38,630.54 3
6 France CAC 40 4,180.02 -2.24% -2.20% 4.85% 4,356.28 3,575.17 12
7 U.S. S&P 500 1,794.19 -2.55% 1.75% 6.42% 1,849.44 1,485.01 6
8 UK FTSE 100 6,538.50 -2.86% -3.53% -0.49% 6,875.60 6,023.40 8
9 Australia All ordinaries 5,199.40 -2.96% -4.17% 3.44% 5,453.10 4,610.60 10
0 India BSE 30 20,498.25 -3.05% -2.55% 5.94% 21,483.70 17448.70 2
1 Singapore Straits Times 3,027.22 -4.00% -6.29% -6.72% 3,464.79 2,990.68 13
2 Mexico IPC 41,008.30 -4.54% -0.10% 1.92% 45,811.50 37,034.30 5
3 Hong Kong Hang Seng 22,035.42 -5.20% -5.44% 0.37% 24,111.60 19,426.40 15
4 Japan Nikkei 225 15,007.06 -7.88% 3.48% 8.20% 16,320.20 11,007.80 1
5 Brazil Bovespa 47,244.00 -8.28% -12.79% -2.71% 60,496.00 44,107.00 14
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NON-U.S. DOLLAR FOREX CROSS RATES
ank Currency pair Symbol Jan. 30 1-monthgain/loss
3-monthgain/loss
6-monthgain loss
52-weekhigh
52-weeklow
Previou
1 Yen / Real JPY/BRL 0.02364 6.32% 5.99% 2.52% 0.0248 0.0196 16
2 Pound / Canada $ GBP/CAD 1.847595 4.69% 9.94% 17.02% 1.847595 1.5286 9
3 Euro / Canada $ EUR/CAD 1.522885 3.45% 5.86% 11.71% 1.522885 1.3005 11
4 Franc / Canada