Fx Strategies

Alternatives to standard carry and momentum in FX

John NormandAC

(44-20) [email protected]. Morgan Securities Ltd.

Kartikeya Ghia(44-20) [email protected]. Morgan Securities Ltd.

www.morganmarkets.comThe certifying analyst is indicated by an AC. See page 23 for analystcertification and important legal and regulatory disclosures.

• Carry and momentum are the most commonly followed trading strategies incurrency markets, and probably in any asset class.

• While standard approaches are profitable, they suffer several shortcomings.Carry incurs high drawdown, particularly when volatility rises. Thedrawdown on momentum strategies is also high, and returns are poor inrange-trading markets. Minor modifications to each strategy can improveperformance by better exploiting the interest rate/FX relationship.

• This paper proposes three such alternatives. (1) Forward Carry positions onchanges in expected cash rate spreads rather than current cash ratedifferentials. (2) Forward Carry Overlay uses these spread movements totime entry into and exit from traditional carry trades. (3) ForwardMomentum Overlay uses Forward Carry to time standard spot momentumtrades.

• As a stand-alone strategy, Forward Carry delivers similar risk-adjustedreturns to standard carry strategies (IR of approximately 0.8) but offers twoadvantages. Returns are positively correlated with changes in volatility andthe drawdown is 1/4th to 1/2 that of traditional approaches.

• Using Forward Carry as an overlay on standard carry and momentumbaskets also reduces drawdown by half, and improves the performance ofmomentum models in range-trading markets.

• Recommendations from these models and performance statistics arereported regularly in the Investable Indices & Alpha Strategies section ofJPMorgan’s FX Markets Weekly.

Simple enhancements to conventional approachesCarry and momentum are the most widely-followed trading strategies in cur-rency markets, and probably in any asset class. Indeed, these approachesinform the majority of rule-based investment styles outlined in the InvestmentStrategies series launched by JPMorgan in 2001 (see page 24). In currencies,the standard carry model positions on libor differentials (buying high vs lowyielders), while the standard momentum model positions on recent spot trends(buying the currency which has appreciated). While still profitable, thesestrategies come with pitfalls. Carry suffers high drawdown, particularly whenvolatility rises. Momentum strategies perform better in high-volatility environ-ment but still incur sizable drawdown. In addition, trend-following systemsperform poorly when the dollar range trades.

Global FX StrategyJPMorgan Securities Ltd.London, August 8, 2008

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Contents

Simple enhancements to conventional approaches 1Forward Carry 2Forward Carry Overlay 5Forward Momentum Overlay 7Conclusions 10Appendix tables 15

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J.P. Morgan Securities Ltd.John Normand (44-20) [email protected]

Global FX StrategyAlternatives to standard carry and momentum in FXAugust 8, 2008

This paper outlines three alternatives which improveperformance without much additional complexity.

• Forward Carry trades currencies based on changes inexpected cash rates rather than on current cash ratedifferentials;

• Forward Carry Overlay uses Forward Carry to time theentry into and exit from standard carry strategies; and

• Forward Momentum Overlay uses Forward Carry to timestandard spot momentum trades.

As suggested by the initial descriptions, all strategiesmodify traditional approaches by incorporating rateexpectations. Some of these strategies such as ForwardCarry and Forward Carry Overlay were introduced in earlierJPMorgan research1 and are refined in this paper. ForwardMomentum Overlay draws on previous Investment Strate-gies papers on momentum trading in FX, fixed income andcommodities (see page 24).

Backtesting for all models follows common guidelines:

• Results are calculated over the longest available sampleperiod, which is 1992 based on daily datasets captured inJPMorgan’s Dataquery and on Bloomberg. We divide thedataset into two parts – parameter estimation is carried outduring the in-sample period (1992 - 2006), with 2007- Q22008 used to test out-of-sample performance. Figures arealso reported for the first and second half of the in-sampleperiod (1992 - 98 and 1998 - 2006) as an additional robust-ness check.

• Strategy returns are carry-adjusted based on 1-mo liborrates, such that the investor pays or earns the fundingrate on all trades.

• Returns include transaction costs, which are calculated asthe average bid-ask spread each year of the sample period.These adjustments range from 0.02% per trade for USD/JPY to 0.05% on NZD/USD. Given the lack of daily bid-offer data during the early 1990s, we backfill those yearsusing 1995 spreads as a proxy.

• Since signals are based on end-of-day data, trades areassumed to be executed the following day.

Chart 1: Correlaton between currency manager returns and carrystrategies in G-10 and emerging marketsManager returns based on Barclay Currency Trader Index, monthly data,rolling 12-mo window

Source: JPMorgan

1. See JPMorgan’s FX Barometer, J. Normand, Sep 2004 and Currencies in 2008: Is there anything butcarry?, J. Normand, Nov 2007, both available on www.morganmarkets.com.

• All models include robustness checks around alternativeparameters to the baseline model. These results areincluded in the main text and in the Appendix tables onpage 15-19.

• Returns are reported for three currency blocs: (1) USDpairs, (2) Most-liquid G-10 pairs and (3) Major G-10pairs. The USD pairs are EUR/USD, GBP/USD, USD/CHF,USD/NOK, USD/SEK, USD/CAD, AUD/USD, NZD/USD& USD/JPY. Most-liquid G-10 pairs are the previous nineUSD pairs plus the five euro crosses of EUR/GBP, EUR/CHF, EUR/SEK, EUR/NOK and EUR/JPY. Major G-10pairs are the 14 Most-liquid G-10 pairs plus other com-monly-traded crosses such as AUD/CAD, CAD/JPY,NOK/SEK, NOK/JPY, GBP/JPY, AUD/NZD, AUD/JPY andNZD/JPY (22 pairs in total).

More detailed results by individual currency are available onrequest.

1. Forward CarryJudging from its correlation with currency manager returns,the carry trade has been the industry’s mainstay for the pastfive years, first in G-10 pairs and more recently in emergingmarkets (chart 1). Carry’s popularity stems from threesources: the trading rule is simple (buy high vs low-yielders); the inefficiency is persistent (the forward ratebias); and the returns have been high over the past decade(return-to-risk of 0.8 to 1.2 on G-10 and emerging marketsbaskets). Yet the negative returns on G-10 carry since mid-2007 and on emerging markets baskets in early 2008 also

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J.P. Morgan Securities Ltd.Kartikeya Ghia (44-20) [email protected]


highlight the strategy’s chief pitfall: returns tend to moveinversely with volatility (chart 2), so are vulnerable tocyclical and policy shocks such as recession and centralbank surprises. Drawdown is often significant, at some 20%for a typical carry basket.

Intuition: FX responds to rate changes as much asrate levelsRegardless of its long-term profitability, trading currenciesonly on carry ignores the other link between interest ratesand FX: currencies respond as much to changes in rates asthey do to current rate differentials. Rising rates relative tothe rest of the world usually signals cyclical strength whichdraws capital inflows and sponsors currency appreciation,even for low-yielders. When rate spreads are stable, thetraditional carry dynamic tends to dominate, leading highyielders to appreciate versus low-yielders.

There are numerous examples of this interplay in practicethroughout the G-102. USD/JPY’s appreciation from mid-2006to mid-2007, even as US - Japan libor spreads were stable(chart 3), illustrated the dominance of carry. The dollar’ssubsequent fall from mid-2007 to Q1 2008 as spreads nar-rowed, even as the US remained the high-yielder, highlightedthe dominance of spread changes. EUR/USD has respondedexclusively to spread changes over the past few years; risingversus the dollar since 2006 as spreads narrowed, eventhough the US retained a rate advantage until early 2008(chart 4).

Strategy: trade FX in the direction of spreadchangesA simple strategy to capture this spread dynamic would beto buy the currency in whose favor rates had moved oversome defined period, and to sell the currency when that ratemomentum reversed. This rule would apply regardless ofwhether the focus currency were a high or a low-yielder,since funding currencies can rally as their yield deficitdiminishes. Since the strategy is based on the expected cashrate differential, we call this approach Forward Carry, a termintroduced in the 2004 publication JPMorgan’s FX Barom-eter (J. Normand, Sep 2004).

Chart 2. Returns on standard carry strategy vs FX volatility, 2006 - 08based on (1) annual returns for carry basket using Most-liquid G-10 pairs and(2) annual changes in G-10 implied volatility as measured by JPMorgan VXY

Source: JPMorgan

Source: JPMorgan

Chart 3: USD/JPY vs US - Japanese libor differentials

Chart 4: EUR/USD vs Euro - US libor differentials

Source: JPMorgan

2 By contrast in emerging markets, rising rates relative to core markets typically represents a risk premiumfor macroeconomic instability. Hence this trading rule generates decent returns (IR of 0.5 to 1) over longsample periods for currencies where the policy framework has converged towards G-10 (Taiwan,Poland, Mexico), but poor results (negative IR) for countries exhibiting less convergence (South Africa,Hungary, Turkey).

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The model involves three parameters:• The reference interest rate is used to capture monetary

policy expectations over the near term. We test threetenors: 1-month rates 1 month forward, 1-month rates 3months forward and 3-month rates 3 months forward.

• The lookback period is the interval over which the changein spread is measured. We test four possibilities: thechange over the past 1, 3, 6 and 12 months. In general,shorter lookback periods generate stronger results.

• The rebalancing frequency indicates how often thechange in spreads is calculated and trades executed –daily, weekly or monthly. Given transaction costs, thechoice of rebalancing frequency involves a tradeoffbetween greater nimbleness/high turnover costs (daily)and less flexibility/lower transaction costs (monthlymodel).

Performance: comparable returns, less drawdownAs a baseline case, consider a daily model using changes in1-month rates 3 months forward over a 1-month lookbackperiod. Applied to a basket of nine USD pairs, the strategyhas generated a return-to-risk near 0.80 net of transactioncosts since 1992, with good consistency across sub-periods(1992 - 98, 1999 - 2006) and larger currency blocs (Most-liquid G-10 pairs and Major G-10 pairs). For all three blocs,performance has been particularly strong since 2007,highlighting the yield-centric nature of most currencymovements over the past two years. Drawdown is only aquarter the size of the traditional carry strategy (-7% onForward Carry) owing to the model’s ability to be long orshort high-yield currencies depending on the direction ofspread momentum.

For comparison, Table 1 also presents returns for thestandard carry strategy of simply buying high-yieldersversus low yielders. JPMorgan’s carry methodology differsslightly from the conventional approach in that we rankcurrencies by their carry-to-risk ratio (libor differentialdivided by annualised spot FX vol) and hold a basket of thetop four pairs, rebalancing monthly (see JPMorgan’s FXBarometer, Sep 2004). As is the case with carry models inother asset markets, returns on the FX carry strategy havetended to move inversely with volatility. This is illustratedby the negative correlation between the standard carrybasket and aggregate FX volatility as measured byJPMorgan’s VXY (see Introducing the JPMorgan VXY &EM-VXY, J. Normand and A. Sandilya, Dec 2006).

Source: JPMorgan

Table 1. Performance of Forward Carry, 1992 - 2008Sensitivity to FX volatility measured as correlation of strategy return withchange in JPMorgan’s VXY index of G-10 3-mo implied vol.Drawdown defined as deviation of index from its historic level high.

Chart 5. Foward Carry vs Standard Carry: excess returns indexindex level, calculated for basket of Most-liquid G-10 pairs

Source: JPMorgan

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Forward Carry

Standard carry basket: carry-to-risk (USD pairs)

USD pairs Most-liquid G-10 pairs

Major G-10 pairs

1992 - 2006 (full sample)Annualised return 5.6% 4.0% 3.7% 4.3%Volatility 6.9% 5.1% 3.3% 3.8%IR 0.81 0.80 1.10 1.13Correlation with trade-weighted USD -0.19 -0.13 -0.21 -0.27Correlation with VXY -0.17 0.16 0.14 0.19

1992 - 1998 (1st half)Annualised return 2.2% 4.6% 4.3% 5.7%Volatility 6.9% 5.5% 3.6% 3.9%IR 0.31 0.84 1.20 1.47Correlation with trade-weighted USD 0.25 0.24 0.23 0.18Correlation with VXY -0.41 0.40 0.35 0.30

1999 - 2006 (2nd half)Annualised return 8.7% 3.6% 3.2% 3.1%Volatility 6.7% 5.1% 3.2% 3.5%IR 1.28 0.70 0.97 0.88Correlation with trade-weighted USD -0.18 -0.11 -0.23 -0.41Correlation with VXY 0.14 0.03 0.05 0.19

2007 - Q2 2008 (out of sample)Annualised return -0.1% 13.2% 9.0% 7.9%Volatility 5.2% 6.0% 4.2% 4.2%IR -0.01 2.21 2.17 1.89Correlation with trade-weighted USD 0.06 -0.74 -0.92 -0.69Correlation with VXY -0.13 0.60 0.84 0.50

# transactions per month 0.5 15 25 39Max gain (monthly) 5.3% 4.1% 3.0% 3.3%Max loss (monthly) -6.5% -4.1% -2.8% -2.0%Max drawdown -17.6% -7.0% -4.4% -5.8%

Forward carry

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By contrast, all of the Forward Carry baskets tend to bepositively correlated with implied volatility (Table 1 and chart6), a characteristic which makes the approach an attractivecomplement to traditional carry baskets. This patterns stemsfrom two sources. First, Forward Carry can be long or shortthe high-yielders, depending on recent movements in ratesspreads. Second, rate spreads have more momentum whencentral bank uncertainty is high, a backdrop which is alsobullish for FX vol. Consequently, maximum monthly lossesand maximum drawdown are much lower with Forward Carrythan with standard carry.

One constraint with Forward Carry is that it generates moretransactions per month than a standard carry basket, whichhas very little turnover. For a basket of nine USD pairs,Forward Carry generates roughly 15 signals/trades permonth, compared to an average of 1 trade per month with astandard carry model. (Turnover is low with standard modelssince pair selection is based on the rank-order of libor rates,which changes little from month to month). But even net oftransaction costs, the strategy still generates high absoluteand risk-adjusted returns.

As a robustness check, Table 2 provides a heatmap indicat-ing risk-adjusted performance as the three key parameters –reference interest rate, lookback period and rebalancingfrequency – change. The baseline model is daily and tradesoff changes in 1-month rates 3 months forward over the pastmonth. This strategy generates an IR of 0.97 (outlined intable 2). Using alternative interest rates with a daily modeland 1-month lookback does not alter performance much forany of the three currency blocs. Moving from daily to

Chart 6. Forward Carry vs Standard Carry: Correlation of annualreturns with FX volatilitybased on (1) annual returns for on each strategy using Most-liquid G-10 pairsand (2) annual changes in G-10 vol as measured by level changes inJPMorgan VXY index.

Table 2. Forward Carry performance using other reference interestrates, lookback periods and rebalancing frequenciesInformation ratios based on 1992 - 2008 sample period for the three currencyblocs of USD pairs, Most-liquid G-10 pairs and Major G-10 pairs

Source: JPMorgan Source: JPMorgan

weekly or monthly rebalancing results in weaker performance(0.50 for USD pairs). Using longer lookback periods (3, 6 or12 months also worsens performance (IR of 0.19 - 0.42 forUSD pairs).

2. Forward Carry OverlayTrying to time the entry into and exit from carry trades isnothing new. The traditional approach employs so-called riskappetite measures, which are composites – and often

IRUSD pairs1 mo in 1 mo Daily 1 mo 0.771 mo in 3 mos Daily 1 mo 0.973 mos in 3 mos Daily 1 mo 0.871 mo in 3 mos Daily 1 mo 0.971 mo in 3 mos Weekly 1 mo 0.501 mo in 3 mos Monthly 1 mo 0.481 mo in 3 mos Daily 1mo 0.971 mo in 3 mos Daily 3mos 0.421 mo in 3 mos Daily 6mos 0.191 mo in 3 mos Daily 12mos 0.30

Most-liquid G-10 pairs1 mo in 1 mo Daily 1 mo 1.041 mo in 3 mos Daily 1 mo 1.293 mos in 3 mos Daily 1 mo 1.131 mo in 3 mos Daily 1 mo 1.291 mo in 3 mos Weekly 1 mo 0.431 mo in 3 mos Monthly 1 mo 0.411 mo in 3 mos Daily 1mo 1.291 mo in 3 mos Daily 3mos 0.431 mo in 3 mos Daily 6mos 0.281 mo in 3 mos Daily 12mos 0.42

Major G-10 pairs1 mo in 1 mo Daily 1 mo 1.071 mo in 3 mos Daily 1 mo 1.233 mos in 3 mos Daily 1 mo 1.211 mo in 3 mos Daily 1 mo 1.231 mo in 3 mos Weekly 1 mo 0.531 mo in 3 mos Monthly 1 mo 0.511 mo in 3 mos Daily 1mo 1.231 mo in 3 mos Daily 3mos 0.401 mo in 3 mos Daily 6mos 0.281 mo in 3 mos Daily 12mos 0.58

Reference interest rate

Rebalancing frequency Lookback period

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jumbles – of volatility, credit spreads and sometimes com-modity prices. While good at characterizing current marketsentiment — bullish (bearish) on carry when spreads andvolatility are below (above) average — these indicators havetwo shortcomings. Firstly, they are often overfitted,including a factor associated with every previous carry tradeunwind over the past decade (e.g. corporate distress, equitymarket collapse, an emerging markets default). Secondly,they can reverse frequently during market turbulence –imposing high turnover.

Intuition: rate cycles are easier to model thancrisesRather than model the last crisis to anticipate the next carryunwind, an alternative would be to focus on more regularcyclical shifts which undermine carry trades too. That is, ifcurrencies show an empirical tendency to rise and fall withchanges in spread momentum – the conclusion from theprevious Forward Carry analysis – the riskiest carry tradesare those which hold high-yielders where cyclical conditionsare softening, the central bank easing and interest ratesfalling. The safest trades would be holding the high-yielderswhere the economy is accelerating and/or rates rising. Riskswould be balanced in a high-yielder where rates are stable. Ifthis intuition is correct, Forward Carry could provide a usefuloverlay to the standard carry framework.

Strategy: condition carry trades on spreadmovementsA simple application of this principle is to hold high yieldcurrencies only where rates are rising, and to close exposurewhen rate spreads move against the investment currency.Consider the example outlined in chart 7. The standardapproach to constructing carry baskets is to rank currencypairs each month by rate differential and to buy the top-yielding currencies versus the lowest-yielding ones. Ourcarry-to-risk framework ranks currencies by risk-adjustedcarry and invests only in those pairs offering a yield-to-volratio of 0.2 or higher, as we find that imposing some modestthreshold for inclusion in the carry basket tends to generatestronger performance than imposing no threshold. Basketstypically hold four pairs for diversification and arerebalanced monthly, since the rank order of currency pairsdoes not change frequently. This process is illustrated insteps 1 - 4a of the diagram.

Forward Carry Overlay adds an additional filter which onlyholds those currencies where spreads are widening in thehigh-yielder’s favour. If the pair lacks spread momentum, it is

dropped and the process continues until four pairs areidentified. If four pairs do not qualify, the model equallyallocates capital amongst those pairs which fulfill the criteria.This process is described in steps 1 - 5b. In its simplest form,the model applies the same forward carry rule developed inthe previous section – the change in 1-month rates 3 monthsforward over the past month. This overlay could be applieddaily or monthly, but given that Forward Carry performsbetter as a daily than a monthly model – even adjusted forhigher transaction costs – the performance of the overlaymodel should follow a similar pattern.

Performance: higher returns, less drawdownTable 3 compares the performance of daily and monthlyoverlay models and that of the standard carry basket. Duringthe in-sample period (1992 - 2006) the daily overlay modelapplied to the nine USD pairs generates comparable absolutereturns (5.9% p.a.) but has a higher volatility and slightlylower risk-adjusted return (0.73 vs 0.81 on the standardbasket). Higher volatility results from greater concentrationrisk with the overlay model, which sometimes invests in onlyone or two pairs if only that subset meets the inclusioncriteria. However, since these pairs have more fundamentalstrength – they are high-yielders where rates are rising – the

Step 1Rank all currency pairs in descending order of risk-adjusted carry

(carry-to-risk ratio)

Step 3aSelect top 4 pairs for

inclusion in carry basket

Step 3bFor eligible pairs, calculate the direction of spread momentum on the day prior to rebalancing.

Step 4bIf spread momentum moving

against high-yielder, eliminate.

Step 5bRepeat until 4 eligible pairs

identified. Invest equally in each.If < 4 pairs qualify, invest

equally in those.

Step 2Eliminate pairs with carry-to-risk ratio < 0.2

Standard Carry Forward Carry Overlay

Step 4aRebalance monthly

Step 1Rank all currency pairs in descending order of risk-adjusted carry

(carry-to-risk ratio)

Step 3aSelect top 4 pairs for

inclusion in carry basket

Step 3bFor eligible pairs, calculate the direction of spread momentum on the day prior to rebalancing.

Step 4bIf spread momentum moving

against high-yielder, eliminate.

Step 5bRepeat until 4 eligible pairs

identified. Invest equally in each.If < 4 pairs qualify, invest

equally in those.

Step 2Eliminate pairs with carry-to-risk ratio < 0.2

Standard Carry Forward Carry Overlay

Step 4aRebalance monthly

Chart 7. Constructing carry baskets with Forward Carry Overlay

Source: JPMorgan

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strategy’s return distribution avoids the negative skew of astandard carry basket’s returns. Thus, drawdown on thedaily overlay model is half that of the standard carry basket(-8.1% vs -17.6%). Note that we can mitigate the concentra-tion issue by expanding the universe of currencies from thenine USD pairs to the 14 Most-liquid G-10 pairs. On thisbroader basket, volatility is comparable to the standard carrystrategy (5.7%), but absolute and risk-adjusted returns arehigher (IR of 0.98). Drawdown is half that of the standardbasket (-9.6%).

Applying the overlay only once per month has mixed results.The overlay does not improve absolute or risk-adjustedperformance for a basket of USD pairs, but it does lowerdrawdown meaningfully for the broader universe of Most-

liquid G-10 pairs (10.4% vs 20.8%). Daily and monthlyoverlay strategies also raise the return correlation withvolatility, which makes them more conservative carrystrategies. This characteristic also accounts for theunderperformance of the overlay vs standard carry strate-gies during the second half of the sample period (1999 -2006) when volatility was on a trend decline.

3. Forward Momentum OverlayMomentum is the empirical tendency of outperformingassets to outperform again in the future. In FX, the tradi-tional approach trades in the direction of previous spotmovements – buy the currency pair which has rallied – asdetermined by some filter or moving average rule. Despitethe tendency to dismiss these frameworks as overly simplis-

Table 3. Performance of Forward Carry Overlay vs Standard Carry basket, 1992 - 2008Sensitivity to FX volatility is correlation of strategy return with change in JPMorgan’s VXY index. Drawdown is deviation of index from its historic level high.

Source: JPMorgan

Standard Carry (carry-to-risk)

Standard Carry with daily overlay

Standard Carry with monthly overlay

Standard Carry (carry-to-risk)

Standard Carry with daily overlay

Standard Carry with monthly overlay

1992 - 2006 (full sample)Annualised return 5.6% 5.9% 5.0% 4.4% 5.6% 5.5%Volatility 6.9% 8.1% 8.7% 5.6% 5.7% 7.1%IR 0.81 0.73 0.58 0.77 0.98 0.77Correlation with trade-weighted USD -0.19 -0.22 -0.07 -0.17 -0.11 -0.15Correlation with VXY -0.17 0.13 0.13 -0.08 0.12 0.17

1992 - 1998 (1st half)Annualised return 2.2% 6.6% 6.3% 2.1% 6.7% 6.2%Volatility 6.9% 5.6% 6.4% 6.5% 3.2% 5.9%IR 0.31 1.17 0.99 0.33 2.09 1.04Correlation with trade-weighted USD 0.25 0.38 0.34 0.25 0.68 0.52Correlation with VXY -0.41 0.00 -0.05 -0.13 -0.02 0.04

1999 - 2006 (2nd half)Annualised return 8.7% 5.3% 3.8% 6.3% 4.6% 4.8%Volatility 6.7% 10.2% 10.6% 4.7% 7.4% 8.3%IR 1.28 0.52 0.36 1.33 0.63 0.58Correlation with trade-weighted USD -0.18 -0.55 -0.40 -0.41 -0.66 -0.65Correlation with VXY 0.14 0.29 0.32 0.14 0.21 0.30

2007 - Q2 2008 (out of sample)Annualised return -0.1% 9.2% 8.6% -1.8% 4.9% 6.6%Volatility 5.2% 9.7% 10.5% 5.3% 7.1% 8.1%IR -0.01 0.95 0.81 -0.34 0.69 0.81Correlation with trade-weighted USD 0.06 -0.70 -0.59 0.86 0.22 0.09Correlation with VXY -0.13 0.60 0.51 -0.93 -0.41 -0.27

Transactions per month 0.5 2.9 0.9 1.0 6.0 2.0Max gain (monthly) 5.3% 6.5% 6.5% 4.2% 5.3% 6.0%Max loss (monthly) -6.5% -3.9% -4.9% -9.1% -4.0% -5.7%Max drawdown -17.6% -8.1% -17.1% -20.8% -9.6% -10.4%

USD pairs Most-liquid G-10 pairs

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tic, the profits from such a strategy have been decent. Thesimple moving average crossover rules proposed in our FXBarometer four years ago have generated a return-to-risk of0.6 net of transaction costs over the past decade, with nodeterioration in performance in the four years since themodel was launched in 2004.3 This section proposesalternatives based on subsequent JPMorgan research onmomentum strategies (see Investment Strategies list, page24) and on principles from the Forward Carry model justoutlined.

Intuition: investors consistently underreact, creat-ing trendsIn principle, no trend-following strategy should generateconsistent profitability if markets are efficient. However,even the strongest proponents of market efficiency acknowl-edge its limitations due to market segmentation (whichimpedes capital flows into mispriced markets) or behaviouralbiases (which impede instantaneous responses to newinformation). Momentum strategies benefit from two, well-documented behavioural biases of underreaction andoverreaction. Underreaction reflects investors inability orunwillingness to adjust views and positions quickly; eitherbecause they await fuller information to make a decision, orbecause they are reluctant to appear non-consensus.Accordingly, prices adjust slowly towards a market’sfundamental value, in the process producing short-termtrends. Overreaction is also based on cognitive biases.Although most investors adjust their expectations fully,some extrapolate this positive news into the future, thusleading prices to overshoot fundamental value.

Though both behavioural biases are well-known, theypersist. As an example of underreaction, consider the mannerin which economists adjust macro forecasts. Each month theBlue Chip survey publishes Wall Street economists’ consen-sus estimate on key macro variables such as growth,inflation and the Fed funds rate. Economists’ forecasts arereasonable proxies for investors’ views since both campsemploy similar frameworks in their decision-making. Ifeconomists/investors indeed reacted instantaneously to newinformation (such as the impact of a credit crunch), theirprojections would move in a stepwise fashion, perhaps froma forecast of 3% growth this year to a forecast of 1% growth.

Chart 8. Foward Overlay vs standard carry: excess returns indexindex level, calculated for basket of Most-liquid G-10 pairs

Source: JPMorgan

Chart 9. Forward Overlay vs standard carry: Correlation of annualreturns with FX volatilitybased on (1) annual returns for each strategy using Most-liquid G-10 pairs and(2) annual changes in G-10 vol as measured byJPMorgan VXY

Source: JPMorgan

In practice, forecasts move incrementally – by roughly aquarter point per month over several months – before fullydiscounting the new cyclical scenario (chart 10). Serialcorrelation in forecast changes is so strong that a down-grade to growth forecasts this month has a 70% likelihood ofbeing followed by another downgrade the following month(Table 4). An upgrade to growth forecasts have a 67%likelihood of being followed by a similar move the nextmonth. Since incremental changes in views typically promptincremental changes in positions, this tendency tounderreact creates trends in asset markets. (For a fullerdiscussion of the relationship between expectational shiftson macro variables and asset markets, see Which Trade?Choosing tactical positions across asset classes, J.Normand, Jan 2004).

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3. Following standard approaches, the crossover rule calculated a short-term moving average for eachcurrency pair (between 5 and 60 days) and a long-term moving average (10 and 200 days). It alsoimposed a four-week filter rule which compared the daily close (London 5PM price) to spot’s four-weekhigh and low. The trading rule was to open a position when two conditions are met: buy (sell) when 1)the shorter-term moving average is above (below) the longer-term moving average; and 2) the 4-weekhigh (low) is exceeded.

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The simple strategyMomentum in expectations provides the theoretical under-pinning for trend-following strategies; the issue is how bestto model it. Typical frameworks involve two parameters: themomentum measure (simple price momentum, exponentially-weighted moving average) and the rebalancing frequency.

• The momentum measure can be based on simplemomentum, which calculates performance over a previouslookback period, or an exponentially-weighted movingaverage, which places more emphasis on recent observa-tions. We test four lookback periods for simple pricemomentum (the past 1, 3, 6 and 12 months) and theirequivalent decay factor for exponentially-weightedmoving averages.

• The rebalancing frequency can be of any length – intra-day, daily, weekly, monthly. For simplicity, and to fit theapproach of most investment managers, we focus on daily,weekly and monthly models rather than on intra-day onesmore common to algorithmic accounts.

The underlying return series can be based on spot or totalreturns. Spot momentum is easiest to observe, so is most-widely referenced in technical models. Total return momen-tum – spot return plus accrued carry over the same horizon –is not used by FX technicians but is commonly referenced inmomentum models in other asset markets. The rationale isthat high-performing assets often attract investor flows, thusextending trends. An FX momentum model which only tracksspot returns thus ignores a key driver of realised return – theaccrued carry – which may motivate flows and additionalspot gains.

Applying these parameters to a basket of nine USD pairssuggests the following:

• Simple price momentum still generates a decent return-to-risk over various sample periods but mainly if based onmedium-term trends (longer lookbacks). For example withspot momentum, IRs tend to rise with the lookbackhorizon for daily and monthly models, with the highest IR(0.60) realised for models based on price trends measuredover the past year (table 5 and charts 11). There arenotable exceptions such as the performance trend of theweekly model, but the generalisation still holds. Thisfinding is consistent with previous JPMorgan research onmomentum in commodities which found the strongest and

Chart 10: Monthly changes in consensus estimate for US growth inthe year ahead, 1990 - 2007

Source: JPMorgan, Blue Chip Economic Indicators monthly survey

Table 4: Conditional probabilities on consensus forecast revisions forUS growth and inflation, 1990 - 2007probability of forecast revision in period t+1 given change in period t

Growth Period t+1Period t Up Down

Up 0.67 0.33Down 0.31 0.69

Inflation Period t+1Period t Up Down

Up 0.65 0.35Down 0.17 0.83

Source: JPMorgan, Blue Chip Economic Indicators monthly survey

-0.7%

-0.5%

-0.3%

-0.1%

0.1%

0.3%

0.5%

89 91 93 95 97 99 01 03 05 07

most consistent performance to be based on medium-termtrends (see Momentum in Commodities, Ribeiro, Loeysand Normand, September 2006).

• Momentum in total returns barely outperforms momen-tum in spot returns for most combinations of rebalancingfrequencies and lookback periods (chart 12 and table 6).The degree of outperformance is small but is consistentwith the view that trends in total return are a betterpredictor of future performance, as they capture theattraction of carry for some investors.

• We find no evidence that exponentially-weighted movingaverages outperform simple price momentum measures,whether applied to spot or total returns (performancetables available on request).

10



Refinements on the simple strategy: Conditionprice momentum on rate momentumAs refinements on the simple strategy, we examine threeadditional parameters: pair selectivity, weighting schemeand overlay.

• Pair selectivity would trade only those currencies whichexhibit the most momentum, rather than all pairs within agive universe (nine USD pairs or 14 most-liquid G-10 pairs,for example). A simple rule would buy only the top one,two or three currencies based on their performance overthe lookback period. Currencies could be ranked byabsolute or risk-adjusted performance, the latter to avoidsystematically choosing high-vol pairs.

• Weighting scheme refers to capital allocation within thebasket of chosen currencies. Equal capital allocation is thesimplest approach, but previous JPMorgan research hasfound that using Markowitz (optimised) weights improvesperformance in commodities markets (see OptimizingCommodities Momentum, Ribeiro and di Pietro, April2008).

• Overlay is a conditioning variable used to confirm aninitial price momentum signal. In technical analysis, theoverlay typically comes from either a filter rule (breaking anew high or low) or shorter-term moving average(confirming a long-term trend), such as those used in theFX Barometer price momentum model. In this paper weexplore a more fundamental overlay of Forward Carry. Thistrading rule would buy a currency only when it exhibitspositive price momentum and when forward interest ratespreads are moving in the direction of the appreciatingcurrency. The objective is to counterbalance the noise ofprice signals with fundamental information from the ratesmarket.

Applying these refinements to the nine USD pairs leads toseveral initial conclusions.

• Selectivity improves performance. As noted in theprevious section, a decent baseline model trades curren-cies based on momentum over the past 12 months. Such amodel applied to spot returns for the nine USD pairs andrebalanced daily or monthly generates a return-to-risk ofclose to 0.6 (tables 4 and 5). If we rank each pair fromhighest to lowest momentum and choose only the top oneor two pairs, absolute performance rises but volatility rises

by more due to lack of diversification, leading to a declinein IR to 0.5 (charts 13 and 14, Appendix tables 1 and 2).Performance improves, however, if we choose the topthree or four pairs (IR of 0.7), suggesting some benefitfrom selectivity.

Results are similar whether we rank currencies by absoluteor risk-adjust returns, and whether we use spot or totalreturns as the underlying series. Choosing top performersfrom even broader baskets of the 14 most-liquid G-10 pairsor the 22 major G-10 pairs also generates higher risk-adjusted returns than trading the entire basket (Appendixtables 3 -6).

• The is little evidence that optimised weights within abasket of top performers improves risk-adjusted returns.IRs are roughly comparable with both methods (figuresavailable on request).

• Overlaying price momentum with rate spread momentumimproves performance materially. The simple strategy ofbuying a pair only when it exhibits both positive pricemomentum and rate spread momentum – the ForwardCarry principle – raises absolute returns, lowers volatilityand raises risk-adjusted returns for almost all spot andtotal return momentum models (Appendix tables 7 and 8).As a summary, consider charts 15 and 16, which trace outthe IR for various momentum models with and without theoverlay. For a daily spot model, IRs rise from a range of 0 -0.60 to a range of 0.50 to 0.96 (chart 15). For a daily totalreturn model, IRs rise from a range of 0.12 to 0.61 to arange of 0.54 to 1.06 (chart 16).

• The overlay strategy also outperforms traditional momen-tum strategies in range-trading markets. During periodswhen the dollar is in a range – defined by a monthly moveof +/-1% in the trade-weighted USD – a basic spotmomentum strategy generates profits in only 54% of thosemonths (chart 17). Using the overlay, which allows for noposition-taking unless rate momentum confirms spotmomentum, the percentage of profitable months duringrange-trading environments rises to 60% (chart 18).

ConclusionsThe enhancements discussed are hardly revolutionary. Theyare simple modifications to conventional approaches whichleverage the other key relationship between FX and interestrates: that currencies respond as much to spread changes as

11



Chart 11. Price momentum: Spot returns for USD pairs, 1990 - 2006 Chart 12. Price momentum: Total returns for USD pairs, 1990 - 2006

Chart 13. Best-of momentum baskets, USD pairs 1990 - 2006

Source: JPMorgan

Chart 14. Best-of momentum baskets, Most-liquid G-10 pairs 1990 - 2006

Chart 15. Forward Momentum Overlay on spot returns, USD pairs,1990 - 2006

Chart 16. Forward Momentum Overlay on total returns, USD pairs,1990 - 2006

0.0

0.2

0.4

0.6

0.8

1mo 3mos 6mos 12moslookback period

IR

Spot, daily rebalanceSpot, w eekly rebalanceSpot, monthly rebalance

-0.2

0.0

0.2

0.4

0.6

0.8

1mo 3mos 6mos 12mos

lookback period

IR

Total return, daily rebalanceTotal return w eekly rebalanceTotal return, monthly rebalance

0.0

0.2

0.4

0.6

0.8

1.0


IR

Spot momentum (daily )Spot momentum w ith ov erlay (daily )Spot momentum (w eekly )Spot momentum w ith ov erlay (w eekly )

-0.2

0.0

0.2

0.4

0.6

0.8

1.0


IR

Total return momentum (daily )Total return momentum w ith ov erlay (daily )Total return momentum (w eekly )Total return momentum w ith ov erlay (w eekly )

0.2

0.4

0.6

0.8

1.0

All 1 2 3 4 5number of pairs

IR

Spot momentum (absolute)Spot momentum (v ol-adjusted)Total return momentum (absolute)Total return momentum (v ol-adjusted)

0.2

0.4

0.6

0.8

1.0

All 1 2 3 4 5number of pairs

IR

Spot momentum (absolute)Spot momentum (v ol-adjusted)Total return momentum (absolute)Total return momentum (v ol-adjusted)

12



Tabl

e 5. P

rice m

omen

tum

: Bas

ed on

spot

retu

rns f

or U

SD pa

irs w

ith va

rious

reba

lancin

g fre

quen

cies (

daily

, wee

kly, m

onth

ly) an

d lo

okba

ck p

erio

ds (1

mo,

3mo,

6mo,

12m

o)

1 mo

3 mos

6 mos

12 m

os1 m

o3 m

os6 m

os12

mos

1 mo

3 mos

6 mos

12 m

os19

92 -

2006

(ful

l sam

ple)

Annu

alise

d retu

rnn.a

.0.6

%0.1

%0.2

%3.9

%1.6

%3.2

%1.8

%0.0

%3.4

%1.5

%1.2

%3.6

%Vo

latilit

yn.a

.5.5

%5.4

%6.1

%6.7

%4.5

%5.0

%6.0

%6.0

%5.6

%4.3

%5.2

%6.4

%IR

n.a.

0.11

0.01

0.02

0.59

0.37

0.65

0.30

-0.01

0.60

0.34

0.24

0.56

Corre

lation

with

trad

e-we

ighted

USD

n.a.

0.10

-0.09

-0.16

-0.04

-0.12

-0.06

0.08

0.17

0.12

-0.19

-0.14

-0.09

Corre

lation

with

VXY

n.a.

0.31

0.31

0.20

0.39

-0.09

0.55

0.49

0.37

0.25

0.25

0.35

0.41

1992

- 19

98 (1

st h

alf)

Annu

alise

d retu

rnn.a

.-0

.2%0.8

%-0

.6%4.6

%2.9

%2.6

%-0

.3%-2

.0%4.5

%1.1

%0.8

%3.7

%Vo

latilit

yn.a

.3.9

%4.7

%4.7

%3.7

%4.2

%2.7

%4.8

%3.4

%5.5

%2.6

%4.8

%3.4

%IR

n.a.

-0.05

0.17

-0.13

1.25

0.69

0.95

-0.06

-0.61

0.82

0.44

0.16

1.10

Corre

lation

with

trad

e-we

ighted

USD

n.a.

0.39

0.01

-0.40

0.13

-0.12

-0.06

0.08

0.17

0.12

0.03

-0.11

0.25

Corre

lation

with

VXY

n.a.

0.40

0.42

0.00

0.57

-0.09

0.55

0.49

0.37

0.49

0.41

0.35

0.60

1999

- 20

06 (2

nd h

alf)

Annu

alise

d retu

rn2.3

%1.3

%-0

.6%0.8

%3.3

%0.5

%3.8

%3.7

%1.7

%2.3

%1.8

%1.6

%3.5

%Vo

latilit

y7.7

%6.8

%6.2

%7.4

%8.7

%4.6

%6.5

%6.6

%7.3

%5.8

%5.6

%5.8

%8.5

%IR

0.30

0.19

-0.09

0.11

0.37

0.11

0.58

0.56

0.24

0.41

0.31

0.28

0.42

Corre

lation

with

trad

e-we

ighted

USD

-0.43

0.14

-0.32

-0.26

-0.18

-0.08

-0.37

-0.26

-0.39

0.01

-0.28

-0.28

-0.20

Corre

lation

with

VXY

0.13

0.35

0.24

0.40

0.38

-0.19

0.33

0.18

0.19

0.08

0.24

0.45

0.45

2007

- Q2

2008

(out

of s

ampl

e)An

nuali

sed r

eturn

7.8%

-0.9%

-2.6%

4.9%

6.6%

-6.8%

5.5%

3.2%

5.6%

0.5%

2.4%

8.3%

8.3%

Volat

ility

6.4%

5.7%

5.5%

6.0%

6.8%

5.1%

4.5%

5.5%

5.1%

4.1%

3.5%

5.2%

5.5%

IR1.2

1-0

.16-0

.470.8

30.9

8-1

.331.2

40.5

91.1

00.1

20.7

11.6

01.5

1Co

rrelat

ion w

ith tr

ade-

weigh

ted U

SD-0

.960.2

3-0

.40-0

.96-0

.920.6

3-0

.47-0

.85-0

.93-0

.69-0

.56-0

.96-0

.95Co

rrelat

ion w

ith V

XY0.8

9-0

.300.2

60.9

30.8

4-0

.670.2

90.7

90.8

50.7

30.5

90.9

30.9

0

Tran

sacti

ons p

er m

onth

2.118

.610

.87.8

4.47.7

4.23.0

1.84.3

2.41.6

0.9Ma

x gain

(mon

thly)

5.1%

5.5%

4.9%

4.5%

6.4%

3.5%

3.7%

4.5%

3.7%

5.3%

4.6%

4.6%

6.5%

Max l

oss (

month

ly)-1

1.4%

-4.7%

-4.2%

-4.4%

-6.0%

-4.2%

-4.2%

-4.0%

-4.4%

-4.5%

-5.3%

-4.9%

-5.7%

Max d

rawd

own

-14.1

%-1

4.1%

-14.2

%-1

7.1%

-15.9

%-1

7.2%

-9.3%

-11.3

%-1

4.8%

-9.5%

-16.0

%-1

6.0%

-10.9

%

FX B

arom

eter

met

hod

(mov

ing

aver

age

cros

sove

r)

Mont

hly r

ebala

nce

Look

back

hor

izon

Daily

reba

lance

Look

back

hor

izon

Wee

kly re

balan

ceLo

okba

ck h

orizo

n

Sour

ce: J

PMor

gan

13



Tabl

e 6. P

rice m

omen

tum

: Bas

ed on

tota

l ret

urns

for U

SD pa

irs w

ith va

rious

reba

lancin

g fre

quen

cies (

daily

, wee

kly, m

onth

ly) an

d lo

okba

ck p

erio

ds (1

mo,

3mo,

6mo,

12m

o)

1 mo

3 mos

6 mos

12 m

os1 m

o3 m

os6 m

os12

mos

1 mo

3 mos

6 mos

12 m

os19

92 -

2006

(ful

l sam

ple)

Annu

alise

d ret

urn

n.a.

1.1%

0.8%

0.7%

4.1%

1.8%

3.5%

0.8%

-0.4%

3.3%

1.9%

1.7%

3.7%

Volat

ility

n.a.

5.7%

5.7%

6.2%

6.7%

4.5%

5.2%

5.9%

5.1%

5.1%

4.3%

5.5%

6.6%

IRn.

a.0.

190.

140.1

20.6

10.4

10.

680.

14-0

.07

0.64

0.44

0.31

0.56

Corre

lation

with

trad

e-we

ighte

d USD

n.a.

0.15

-0.0

2-0

.17-0

.03-0

.090.

05-0

.16

0.08

0.14

-0.1

0-0

.16

-0.08

Corre

lation

with

VXY

n.a.

0.27

0.38

0.27

0.33

0.00

0.55

0.33

0.31

0.26

0.21

0.31

0.33

1992

- 19

98 (1

st h

alf)

Annu

alise

d ret

urn

n.a.

0.1%

1.5%

0.4%

4.4%

3.2%

3.2%

-1.7

%-1

.6%4.3

%1.

7%1.

2%3.8

%Vo

latilit

yn.

a.3.

9%3.

7%4.

4%3.

5%4.8

%3.

3%4.

3%1.3

%4.8

%2.

9%4.

6%3.3

%IR

n.a.

0.02

0.42

0.08

1.27

0.66

0.95

-0.4

0-1

.25

0.90

0.57

0.25

1.15

Corre

lation

with

trad

e-we

ighte

d US

Dn.

a.0.

450.

01-0

.150.1

0-0

.090.

05-0

.16

0.08

0.22

-0.0

2-0

.11

0.15

Corre

lation

with

VXY

n.a.

0.37

0.48

0.15

0.48

0.00

0.55

0.33

0.31

0.53

0.31

0.25

0.42

1999

- 20

06 (2

nd h

alf)

Annu

alise

d ret

urn

2.3%

2.0%

0.2%

1.1%

3.7%

0.7%

3.9%

3.1%

0.7%

2.3%

2.1%

2.2%

3.6%

Volat

ility

7.7%

7.0%

7.3%

7.7%

8.9%

4.2%

6.7%

6.3%

6.9%

5.4%

5.4%

6.5%

8.9%

IR0.

300.

290.

030.1

40.4

20.1

60.5

80.

490.1

00.4

30.

380.

340.4

1Co

rrelat

ion w

ith tr

ade-

weigh

ted

USD

-0.4

30.

24-0

.18

-0.31

-0.18

-0.14

-0.3

3-0

.32

-0.5

00.0

2-0

.19

-0.2

7-0

.22Co

rrelat

ion w

ith V

XY0.

130.

300.

380.4

60.3

4-0

.190.

370.

180.1

60.0

80.

210.

450.4

1

2007

- Q2

2008

(out

of s

ampl

e)An

nuali

sed r

etur

n7.

8%-1

.3%

-3.1

%5.

0%6.

8%-7

.6%4.

0%2.

4%8.2

%1.2

%2.

4%8.

3%8.2

%Vo

latilit

y6.

4%5.

8%5.

5%6.

3%7.

0%5.3

%4.

5%5.

6%5.6

%4.2

%3.

4%5.

2%5.4

%IR

1.21

-0.2

2-0

.57

0.80

0.97

-1.44

0.90

0.43

1.46

0.29

0.69

1.59

1.51

Corre

lation

with

trad

e-we

ighte

d US

D-0

.96

0.34

-0.2

0-0

.93-0

.900.5

5-0

.60

-0.8

2-0

.92

-0.52

-0.7

7-0

.95

-0.94

Corre

lation

with

VXY

0.89

-0.4

20.

060.8

80.8

2-0

.610.

450.

740.8

20.5

40.

770.

920.8

9

Tran

sacti

ons p

er m

onth

2.117

.510

.17.

13.

97.

64.2

3.3

1.8

4.22.

31.

50.

9M

ax ga

in (m

onth

ly)5.

1%5.

5%4.

9%4.

5%6.

4%3.5

%4.

2%4.

5%3.6

%5.0

%4.

6%4.

6%6.5

%M

ax lo

ss (m

onth

ly)-1

1.4%

-4.9

%-3

.5%

-4.7

%-6

.0%

-4.2%

-4.2

%-3

.9%

-4.4%

-4.5%

-5.3

%-4

.9%

-5.7%

Max

dra

wdow

n-1

4.1%

-13.6

%-1

5.2%

-15.

8%-2

3.8%

-17.

1%-7

.8%

-15.

7%-1

5.7%

-8.3%

-14.

4%-1

3.4%

-12.

2%

FX B

arom

eter

met

hod

(mov

ing

aver

age

cros

sove

r)

Daily

reba

lance

Wee

kly re

balan

ceMo

nthl

y reb

alanc

eLo

okba

ck h

orizo

nLo

okba

ck h

orizo

nLo

okba

ck h

orizo

n

Sour

ce: J

PMor

gan

14



to spread levels, given the cyclical factors captured byspread moves. As a stand-alone strategy, Forward Carry’schief advantages over carry is its lower drawdown andpositive correlation with changes in volatility. These sameadvantages extend to its use as an overlay to basic carry andmomentum models, both of which have traditionally relied oncomplicated risk-appetite filters or additional (and endog-enous) price filters to time entry and exit.

Some of these strategies have been previewed in previousJPMorgan research, and this paper provides more compre-hensive backtesting across a range of parameters andcurrency blocs. Recommendations from these models andperformance statistics are reported regularly in theInvestable Indices & Alpha Strategies section ofJPMorgan’s FX Markets Weekly.

Chart 17. Return on spot momentum vs moves in trade-weighted USDmonthly data

-6%

-4%

-2%

0%

2%

4%

6%

8%

-4% -2% 0% 2% 4% 6%

Trade-w eighted USD (monthly returns)

mom

entu

m m

odel

(mon

thly

retu

rns)

-6%

-4%

-2%

0%

2%

4%

6%

8%

-4% -2% 0% 2% 4% 6%

Trade-w eighted USD (monthly returns)

mom

entu

m m

odel

(mon

thly

retu

rns)

Chart 18. Returns on spot momentum with overlay vs moves intrade-weighted USDmonthly data

Source: JPMorgan

Source: JPMorgan

Related publications on www.morganmarkets.com

JPMorgan Tradeable Currency Indices (TCIs),J. Normand July 2, 2007.

Bloomberg ticker ALLX JPMQ

Introducing the JPMorgan VXY™ & EM-VXY™,J. Normand and A. Sandilya, Dec 11, 2006.

Bloomberg tickers JPMVXYG7 and JPMVXYEM

15



Appendix Table 1. Baskets of top performers based on spot momentum for USD pairs12-mo lookback, monthly rebalancing, equal weights on each pair

Appendix Table 2. Baskets of top performers based on total return momentum, USD pairs12-mo lookback, monthly rebalancing, equal weights on each pair

Source: JPMorgan

Appendix tables

1 2 3 4 5 1 2 3 4 51992 - 2006 (full sample)Annualised return 3.7% 3.6% 4.4% 4.4% 4.8% 4.3% 6.3% 6.3% 5.3% 4.4% 4.6%Volatility 6.6% 10.2% 7.4% 5.7% 6.2% 6.6% 10.3% 7.0% 5.4% 6.8% 6.5%IR 0.56 0.36 0.60 0.77 0.76 0.65 0.61 0.90 0.99 0.66 0.71Correlation with trade-weighted USD -0.08 -0.31 -0.28 -0.12 -0.20 -0.15 -0.20 -0.19 -0.12 -0.17 -0.15Correlation with VXY 0.33 0.10 0.37 0.31 0.30 0.35 0.16 0.20 0.32 0.35 0.42

1992 - 1998 (1st half)Annualised return 3.8% 0.1% 2.4% 3.7% 4.0% 4.1% 4.7% 4.6% 4.7% 3.8% 4.9%Volatility 3.3% 5.7% 4.1% 3.3% 1.4% 2.2% 8.7% 2.7% 2.5% 3.2% 2.0%IR 1.15 0.02 0.58 1.13 2.94 1.88 0.54 1.69 1.91 1.18 2.49Correlation with trade-weighted USD 0.15 -0.13 0.00 0.09 -0.06 0.00 -0.31 -0.19 0.06 0.04 0.04Correlation with VXY 0.42 0.03 0.40 0.37 0.37 0.43 0.02 0.08 0.30 0.41 0.56

1999 - 2006 (2nd half)Annualised return 3.6% 6.8% 6.2% 5.1% 5.4% 4.5% 7.7% 7.8% 5.9% 5.0% 4.4%Volatility 8.9% 12.3% 9.2% 7.4% 8.7% 9.1% 11.9% 9.2% 7.2% 9.0% 9.0%IR 0.41 0.55 0.67 0.68 0.62 0.49 0.65 0.86 0.81 0.55 0.48Correlation with trade-weighted USD -0.22 -0.20 -0.28 -0.26 -0.24 -0.24 -0.01 -0.03 -0.12 -0.30 -0.30Correlation with VXY 0.41 0.30 0.53 0.35 0.40 0.42 0.43 0.44 0.47 0.42 0.44

2007 - Q2 2008 (out of sample)Annualised return 8.2% 0.5% 4.6% 4.9% 8.0% 8.6% 7.8% 2.6% 5.8% 10.3% 9.4%Volatility 5.4% 12.0% 10.3% 9.7% 8.1% 7.2% 11.8% 8.7% 7.1% 7.1% 7.2%IR 1.51 0.05 0.53 0.69 1.14 1.20 0.66 0.30 0.81 1.46 1.30Correlation with trade-weighted USD -0.94 -0.23 -0.44 -0.42 -0.63 -0.80 -0.68 -0.06 -0.59 -0.73 -0.82Correlation with VXY 0.89 0.07 0.25 0.22 0.45 0.66 0.55 -0.13 0.42 0.59 0.69

# transactions per months 0.9 0.4 0.7 0.8 0.9 1.0 0.4 0.7 0.8 0.9 1.0Max gain (monthly) 6.5% 7.2% 8.2% 7.3% 6.5% 6.4% 7.1% 6.9% 6.4% 6.4% 6.4%Max loss (monthly) -5.7% -15.3% -9.1% -8.9% -8.1% -6.2% -8.5% -7.9% -5.6% -6.6% -6.7%Max drawdown -12.2% -22.8% -17.3% -16.0% -13.8% -13.8% -19.2% -13.7% -12.6% -13.6% -11.8%

Aggregate basket (9 USD pairs)

Absolute price momentum baskets (number of pairs shown in column)

Vol-adjusted price momentum baskets (number of pairs shown in column)


1992 - 1998 (1st half)Annualised return 3.7% 4.7% 2.2% 3.3% 5.0% 4.8% 6.6% 5.0% 4.9% 4.4% 4.7%Volatility 3.4% 6.5% 4.2% 2.9% 2.6% 3.1% 7.7% 4.9% 3.8% 3.4% 3.3%IR 1.10 0.71 0.53 1.16 1.94 1.57 0.86 1.01 1.29 1.29 1.45Correlation with trade-weighted USD 0.25 -0.09 -0.07 0.06 0.09 0.12 -0.21 -0.07 0.12 0.11 0.09Correlation with VXY 0.60 0.20 0.39 0.48 0.56 0.69 0.09 0.42 0.58 0.64 0.72


2007 - Q2 2008 (out of sample)Annualised return 8.3% -1.1% 0.6% 4.0% 5.3% 7.6% 4.4% 2.0% 6.3% 8.7% 8.5%Volatility 5.5% 12.1% 11.1% 9.9% 8.3% 7.5% 12.1% 9.5% 7.2% 7.3% 7.3%IR 1.51 -0.09 0.07 0.55 0.73 1.05 0.37 0.21 0.87 1.19 1.17Correlation with trade-weighted USD -0.95 -0.44 -0.32 -0.53 -0.70 -0.80 -0.58 -0.35 -0.77 -0.87 -0.87Correlation with VXY 0.90 0.28 0.12 0.33 0.53 0.66 0.43 0.15 0.64 0.76 0.76

# transactions per month 0.9 0.4 0.7 0.8 0.9 1.0 0.4 0.7 0.9 1.0 1.0Max gain (monthly) 6.5% 7.2% 8.2% 7.3% 6.5% 7.4% 7.2% 6.9% 6.4% 6.4% 7.4%Max loss (monthly) -5.7% -9.9% -8.9% -8.9% -8.1% -6.2% -8.5% -6.5% -5.9% -6.2% -5.8%Max drawdown -10.9% -25.4% -16.7% -14.8% -15.0% -13.2% -20.5% -14.5% -14.1% -13.5% -14.9%

Aggregate basket (9 USD pairs)



16



Appendix Table 3. Baskets of top performers based on spot momentum, 14 Most-liquid G-10 pairs12-mo lookback, monthly rebalancing, equal weights on each pair

Appendix Table 4. Baskets of top performers based on total return momentum, 14 Most-liquid G-10 pairs14 Most-liquid G-10 pairs, 12-mo lookback, monthly rebalancing, equal weights on each pair

Source: JPMorgan

Appendix tables


1992 - 1998 (1st half)Annualised return 3.1% 3.6% 3.3% 2.9% 3.8% 4.7% 4.5% 4.1% 4.4% 4.4% 5.0%Volatility 1.8% 7.4% 3.5% 3.3% 3.6% 3.8% 6.3% 4.0% 2.8% 1.5% 2.4%IR 1.72 0.48 0.95 0.86 1.07 1.23 0.72 1.04 1.55 2.90 2.11Correlation with trade-weighted USD 0.06 0.17 0.05 0.07 0.14 0.09 0.11 -0.15 -0.07 -0.10 0.03Correlation with VXY 0.43 0.43 0.54 0.41 0.48 0.52 0.78 0.45 0.49 0.47 0.56


2007 - Q2 2008 (out of sample)Annualised return 5.1% -1.1% 1.4% 3.6% 4.8% 7.4% 2.2% 3.5% 5.9% 7.6% 9.1%Volatility 4.0% 12.1% 10.9% 9.9% 8.4% 7.6% 11.2% 8.9% 6.9% 6.7% 6.6%IR 1.26 -0.10 0.16 0.52 0.72 1.13 0.20 0.39 0.87 1.13 1.39Correlation with trade-weighted USD -0.93 -0.49 -0.35 -0.34 -0.51 -0.77 -0.45 -0.53 -0.71 -0.77 -0.84Correlation with VXY 0.87 0.34 0.16 0.12 0.31 0.63 0.28 0.36 0.55 0.65 0.73



Vol-adjusted price momentum baskets (number of pairs shown in column)Aggregate basket (14 most-

liquid G-10 pairs)


1992 - 1998 (1st half)Annualised return 2.9% 0.9% 2.7% 3.4% 3.3% 4.2% 3.9% 3.7% 5.1% 4.1% 4.0%Volatility 2.4% 7.2% 4.8% 5.1% 4.5% 3.1% 5.9% 1.6% 1.5% 3.4% 3.0%IR 1.18 0.12 0.57 0.66 0.73 1.36 0.66 2.41 3.49 1.23 1.33Correlation with trade-weighted USD 0.05 0.17 0.11 0.09 0.18 0.04 0.04 -0.12 -0.08 -0.05 0.05Correlation with VXY 0.22 0.38 0.27 0.30 0.36 0.31 0.76 0.38 0.38 0.25 0.33


2007 - Q2 2008 (out of sample)Annualised return 5.5% 0.9% 3.3% 5.3% 7.5% 8.8% 5.6% 1.4% 4.7% 6.4% 7.9%Volatility 3.7% 12.0% 10.1% 9.9% 8.7% 7.2% 10.9% 8.3% 6.3% 6.4% 6.6%IR 1.46 0.08 0.40 0.84 1.18 1.34 0.51 0.17 0.74 1.00 1.20Correlation with trade-weighted USD -0.93 -0.35 -0.24 -0.31 -0.58 -0.66 0.15 0.08 -0.33 -0.57 -0.72Correlation with VXY 0.87 0.19 0.04 0.10 0.38 0.48 -0.37 -0.28 0.15 0.41 0.57



Vol-adjusted price momentum baskets (number of pairs shown in column)Aggregate basket (14 most-

liquid G-10 pairs)

17



Appendix Table 5. Baskets of top performers based on spot momentum, 22 Major G-10 pairs12-mo lookback, monthly rebalancing, equal weights on each pair

Appendix Table 6. Baskets of top performers based on total return momentum, 22 Major G-10 pairs22 Major G-10 pairs, 12-mo lookback, monthly rebalancing, equal weights on each pair

Source: JPMorgan

Appendix tables

1 2 3 4 5 1 2 3 4 51992 - 2006 (full sample)Annualised return 2.8% 5.7% 5.1% 4.6% 5.0% 5.3% 5.9% 5.3% 5.1% 6.0% 4.5%Volatility 3.6% 8.0% 8.1% 7.5% 7.4% 7.4% 9.3% 7.5% 6.5% 5.2% 5.7%IR 0.79 0.72 0.62 0.62 0.68 0.72 0.63 0.71 0.79 1.16 0.80Correlation with trade-weighted USD -0.04 -0.10 -0.05 -0.01 0.08 0.08 -0.01 0.11 -0.03 0.00 0.00Correlation with VXY 0.08 0.10 0.13 0.10 0.08 0.05 0.36 0.32 0.28 0.21 0.15

1992 - 1998 (1st half)Annualised return 2.5% 4.9% 4.8% 4.0% 4.1% 4.4% 5.2% 6.9% 5.2% 6.1% 4.6%Volatility 3.5% 7.9% 9.1% 8.0% 7.7% 7.6% 8.1% 5.7% 4.3% 4.5% 4.4%IR 0.70 0.62 0.52 0.50 0.54 0.57 0.63 1.21 1.21 1.35 1.03Correlation with trade-weighted USD -0.02 -0.03 -0.10 -0.06 0.15 0.11 0.05 -0.19 -0.13 -0.19 -0.14Correlation with VXY -0.15 -0.06 -0.06 -0.06 -0.09 -0.10 0.37 0.28 0.32 0.18 0.07

1999 - 2006 (2nd half)Annualised return 3.2% 6.5% 5.3% 5.2% 5.8% 6.1% 6.5% 3.9% 5.0% 5.9% 4.5%Volatility 3.8% 8.6% 7.8% 7.5% 7.7% 7.6% 10.8% 9.0% 8.2% 6.0% 6.9%IR 0.83 0.75 0.68 0.70 0.76 0.81 0.61 0.44 0.61 0.99 0.65Correlation with trade-weighted USD -0.11 -0.13 -0.11 -0.05 0.04 0.05 0.05 -0.05 -0.15 -0.01 -0.06Correlation with VXY 0.30 0.34 0.37 0.28 0.24 0.20 0.45 0.38 0.31 0.29 0.27

2007 - Q2 2008 (out of sample)Annualised return 3.5% 0.1% 3.5% 3.5% 6.0% 6.4% 7.9% 1.8% 2.6% 4.1% 6.7%Volatility 4.8% 14.2% 12.6% 12.5% 11.5% 10.5% 14.3% 11.4% 8.7% 8.8% 8.0%IR 0.73 0.00 0.31 0.40 0.68 0.80 0.55 0.16 0.30 0.47 0.84Correlation with trade-weighted USD -0.58 0.61 -0.12 -0.04 -0.16 -0.16 -0.45 0.20 0.38 0.40 -0.32Correlation with VXY 0.40 -0.76 -0.09 -0.17 -0.07 -0.08 0.29 -0.39 -0.57 -0.59 0.12

# transactions per months 2.5 1.6 3.0 4.1 4.8 5.4 0.4 0.8 1.1 1.3 1.6Max gain (monthly) -4.2% -9.7% -8.7% -9.3% -10.7% -11.8% -9.7% -8.7% -7.1% -7.0% -6.6%Max loss (monthly) 3.3% 9.8% 8.2% 7.3% 6.5% 6.3% 7.5% 6.3% 6.2% 5.9% 5.9%Max drawdown -11.0% -18.2% -21.8% -25.5% -24.2% -22.2% -17.9% -17.7% -14.4% -13.4% -15.4%

Aggregate basket (22 major G-10 pairs)



1 2 3 4 5 1 2 3 4 51992 - 2006 (full sample)Annualised return 2.5% 5.5% 4.9% 3.7% 4.5% 4.9% 6.5% 4.7% 5.3% 5.5% 4.9%Volatility 3.3% 9.8% 9.1% 8.5% 7.4% 7.1% 9.4% 8.1% 7.5% 5.9% 5.6%IR 0.75 0.56 0.54 0.44 0.60 0.68 0.69 0.58 0.70 0.93 0.87Correlation with trade-weighted USD -0.04 -0.14 -0.06 -0.05 0.01 0.01 0.12 0.15 -0.01 0.04 0.03Correlation with VXY 0.17 0.21 0.22 0.19 0.23 0.22 0.39 0.40 0.35 0.28 0.26

1992 - 1998 (1st half)Annualised return 2.6% 4.9% 6.4% 3.5% 5.0% 5.5% 7.8% 7.0% 6.0% 6.1% 4.8%Volatility 3.1% 11.0% 9.1% 8.7% 6.8% 6.0% 7.5% 4.1% 5.7% 4.8% 3.9%IR 0.84 0.45 0.70 0.40 0.73 0.91 1.03 1.70 1.06 1.26 1.21Correlation with trade-weighted USD -0.07 -0.05 -0.25 -0.13 -0.10 -0.10 0.01 -0.12 -0.15 -0.20 -0.12Correlation with VXY 0.04 0.11 0.07 0.08 0.14 0.13 0.35 0.40 0.30 0.23 0.29

1999 - 2006 (2nd half)Annualised return 2.4% 6.0% 3.6% 4.0% 4.1% 4.3% 5.4% 2.7% 4.6% 5.0% 5.0%Volatility 3.7% 9.5% 9.5% 9.0% 8.4% 8.4% 11.2% 10.4% 9.2% 7.1% 7.1%IR 0.64 0.63 0.38 0.44 0.49 0.52 0.48 0.26 0.50 0.71 0.71Correlation with trade-weighted USD -0.09 -0.15 -0.19 -0.12 -0.06 -0.02 0.17 0.01 -0.05 0.05 0.11Correlation with VXY 0.35 0.43 0.43 0.35 0.37 0.35 0.51 0.47 0.46 0.38 0.31

2007 - Q2 2008 (out of sample)Annualised return 2.3% -0.4% 0.7% 2.2% 3.9% 4.5% 4.6% 1.1% 3.5% 4.4% 7.4%Volatility 5.0% 14.1% 13.2% 12.3% 11.0% 10.4% 13.3% 10.9% 9.0% 8.7% 8.1%IR 0.46 -0.03 0.07 0.24 0.45 0.56 0.35 0.10 0.39 0.50 0.92Correlation with trade-weighted USD -0.65 0.21 -0.36 -0.27 -0.62 -0.55 -0.65 -0.29 -0.59 -0.35 -0.73Correlation with VXY 0.47 -0.39 0.20 0.07 0.45 0.35 0.53 0.13 0.44 0.18 0.59

# transactions per months 2.7 0.5 0.8 1.0 1.2 1.4 0.4 0.8 1.1 1.3 1.5Max gain (monthly) -4.3% -11.5% -8.7% -8.8% -10.7% -7.4% -7.7% -8.7% -7.1% -7.0% -6.6%Max loss (monthly) 3.3% 9.8% 8.3% 7.3% 8.5% 7.5% 9.8% 6.3% 6.2% 6.4% 5.8%Max drawdown -8.5% -27.7% -19.2% -23.4% -19.5% -16.2% -22.1% -26.9% -18.6% -15.8% -15.5%

Aggregate basket (22 major G-10 pairs)



18



Appe

ndix

Tabl

e 7. F

orwa

rd M

omen

tum

Ove

rlay a

pplie

d to

spot

retu

rns,

USD

pairs

Sour

ce: J

PMor

gan

Appendix tables1m

o3m

os6m

os12

mos

1mo

3mos

6mos

12m

os1m

o3m

os6m

os12

mos

1mo

3mos

6mos

12m

os1m

o3m

os6m

os12

mos

1mo

3mos

6mos

12m

os

1992

- 200

6 (fu

ll sam

ple)

Annu

alise

d re

turn

0.6%

0.1%

0.2%

3.9%

2.1%

2.2%

2.0%

3.8%

1.6%

3.2%

1.8%

0.0%

2.3%

2.1%

2.3%

3.3%

3.4%

1.5%

1.2%

3.6%

3.0%

2.0%

2.0%

3.3%

Volat

ility

5.5%

5.4%

6.1%

6.7%

4.2%

4.1%

4.4%

4.0%

4.5%

5.0%

6.0%

6.0%

4.4%

4.4%

3.7%

4.4%

5.6%

4.3%

5.2%

6.4%

5.3%

4.7%

4.0%

5.0%

IR0.1

10.0

10.0

20.5

90.

500.

540.

460.

960.

370.

650.

30-0

.010.

520.4

70.6

30.7

50.

600.3

40.2

40.5

60.

570.4

30.

490.

66Co

rrelat

ion w

ith tr

ade-

weigh

ted U

SD0.1

0-0

.09

-0.1

6-0

.04

0.03

-0.0

3-0

.14

-0.05

-0.12

-0.0

60.

080.

170.

12-0

.21-0

.23

0.18

0.12

-0.1

9-0

.14

-0.0

90.

19-0

.02

0.01

0.04

Corre

lation

with

VXY

0.31

0.31

0.20

0.39

0.33

0.34

0.31

0.47

-0.09

0.55

0.49

0.37

0.51

0.39

0.28

0.53

0.25

0.25

0.35

0.41

0.51

0.45

0.55

0.62

1992

- 199

8 (1s

t half

)An

nuali

sed

retur

n-0

.2%0.

8%-0

.6%4.

6%2.0

%3.4

%2.0

%4.4

%2.

9%2.

6%-0

.3%

-2.0

%4.4

%3.5

%3.2

%4.

6%4.

5%1.

1%0.

8%3.

7%5.4

%3.

5%3.4

%5.

2%Vo

latilit

y3.

9%4.

7%4.

7%3.

7%3.5

%3.5

%3.0

%3.5

%4.

2%2.

7%4.

8%3.

4%3.2

%3.6

%2.9

%3.

4%5.

5%2.

6%4.

8%3.

4%6.3

%4.

9%3.5

%4.

8%IR

-0.0

50.1

7-0

.13

1.25

0.59

0.97

0.66

1.27

0.69

0.95

-0.06

-0.61

1.36

0.96

1.12

1.38

0.82

0.44

0.16

1.10

0.85

0.72

0.99

1.09

Corre

lation

with

trad

e-we

ighte

d USD

0.39

0.01

-0.4

00.1

30.

310.

12-0

.13

0.20

-0.12

-0.0

60.

080.

170.

310.0

2-0

.20

0.06

0.12

0.03

-0.1

10.2

50.

270.3

50.

150.

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ith V

XY0.4

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520.

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550.

490.

370.

520.4

50.2

80.5

10.

490.4

10.3

50.6

00.

720.6

10.

650.

75

1999

- 200

6 (2n

d ha

lf)An

nuali

sed

retur

n1.

3%-0

.6%

0.8%

3.3%

2.2%

1.2%

2.0%

3.3%

0.5%

3.8%

3.7%

1.7%

0.4%

0.8%

1.6%

2.2%

2.3%

1.8%

1.6%

3.5%

1.0%

0.7%

0.7%

1.7%

Volat

ility

6.8%

6.2%

7.4%

8.7%

5.0%

4.6%

5.5%

4.6%

4.6%

6.5%

6.6%

7.3%

4.1%

4.3%

4.3%

4.7%

5.8%

5.6%

5.8%

8.5%

3.4%

4.4%

4.2%

4.9%

IR0.1

9-0

.09

0.11

0.37

0.43

0.26

0.37

0.73

0.11

0.58

0.56

0.24

0.11

0.19

0.36

0.46

0.41

0.31

0.28

0.42

0.30

0.17

0.17

0.34

Corre

lation

with

trad

e-we

ighte

d USD

0.14

-0.3

2-0

.26

-0.1

8-0

.04

-0.3

2-0

.32

-0.31

-0.08

-0.3

7-0

.26-0

.39-0

.20-0

.35-0

.43

-0.4

90.

01-0

.28

-0.2

8-0

.20

-0.38

-0.4

8-0

.53

-0.47

Corre

lation

with

VXY

0.35

0.24

0.40

0.38

0.27

0.17

0.34

0.39

-0.19

0.33

0.18

0.19

0.25

0.27

0.38

0.42

0.08

0.24

0.45

0.45

0.26

0.32

0.52

0.55

2007

- Q2 2

008 (

out o

f sam

ple)

Annu

alise

d re

turn

-0.9%

-2.6

%4.

9%6.

6%5.6

%4.7

%8.6

%9.5

%-6

.8%

5.5%

3.2%

5.6%

2.3%

1.6%

5.5%

6.2%

0.5%

2.4%

8.3%

8.3%

3.9%

4.7%

7.6%

7.3%

Volat

ility

5.7%

5.5%

6.0%

6.8%

4.7%

5.0%

5.4%

5.9%

-6.8

%4.

5%5.

5%5.

1%4.8

%5.2

%5.5

%5.

9%4.

1%3.

5%5.

2%5.

5%3.9

%3.

6%4.5

%4.

4%IR

-0.1

6-0

.47

0.83

0.98

1.18

0.94

1.59

1.62

-1.33

1.24

0.59

1.10

0.48

0.31

1.00

1.05

0.12

0.71

1.60

1.51

1.00

1.30

1.68

1.64

Corre

lation

with

trad

e-we

ighte

d USD

0.23

-0.4

0-0

.96

-0.9

2-0

.81

-0.9

2-0

.95

-0.94

0.63

-0.4

7-0

.85-0

.93-0

.61-0

.77-0

.94

-0.9

1-0

.69-0

.56

-0.9

6-0

.95

-0.90

-0.9

0-0

.95

-0.94

Corre

lation

with

VXY

-0.3

00.2

60.9

30.8

40.

720.

840.

920.

88-0

.670.

290.

790.

850.

500.6

50.8

90.8

30.

730.5

90.9

30.9

00.

880.8

80.

910.

90

Tran

sacti

ons p

er m

onth

18.6

10.8

7.84.4

15.2

12.2

10.8

9.4

7.74.2

3.01.8

4.0

2.0

2.0

4.04.

32.

41.

60.

94.

32.4

1.6

0.9M

ax g

ain (m

onth

ly)5.

5%4.

9%4.

5%6.

4%4.2

%3.9

%3.9

%3.9

%3.

5%3.

7%4.

5%3.

7%2.7

%3.3

%3.3

%3.

3%5.

3%4.

6%4.

6%6.

5%4.7

%5.

3%5.3

%5.

3%M

ax lo

ss (m

onthl

y)-4

.7%-4

.2%

-4.4%

-6.0%

-5.1%

-3.2

%-2

.0%

-2.6

%-4

.2%

-4.2%

-4.0

%-4

.4%

-2.9

%-2

.9%

-2.9

%-2

.9%

-4.5%

-5.3%

-4.9%

-5.7%

-2.7

%-2

.9%-2

.7%

-3.0

%M

ax d

rawd

own

-14.

1%-1

4.2%

-17.

1%-1

5.9%

-9.3%

-7.0

%-7

.3%

-6.0

%-1

7.2%

-9.3%

-11.

3%-1

4.8%

-9.4

%-9

.2%

-9.4

%-6

.0%

-9.5%

-16.0

%-1

6.0%

-10.9

%-5

.1%

-11.

9%-1

0.6%

-5.7

%

Mont

hly r

ebala

ncin

g

Spot

mom

entu

mSp

ot m

omen

tum

with

ove

rlay

Spot

mom

entu

mSp

ot m

omen

tum

with

ove

rlay

Daily

reba

lancin

gW

eekly

reba

lancin

g

Spot

mom

entu

mSp

ot m

omen

tum

with

ove

rlay

19



Appe

ndix

Tabl

e 8. F

orwa

rd M

omen

tum

Ove

rlay a

pplie

d to

tota

l ret

urns

, USD

pair

s

Sour

ce: J

PMor

gan

Appendix tables1m

o3m

os6m

os12

mos

1mo

3mos

6mos

12m

os1m

o3m

os6m

os12

mos

1mo

3mos

6mos

12m

os1m

o3m

os6m

os12

mos

1mo

3mos

6mos

12m

os

1992

- 20

06 (f

ull s

ampl

e)An

nuali

sed r

eturn

1.1%

0.8%

0.7%

4.1%

2.4%

2.7%

2.5%

4.2%

1.8%

3.5%

0.8%

-0.4%

2.3%

2.1%

2.6%

3.7%

3.3%

1.9%

1.7%

3.7%

2.9%

2.2%

2.3%

3.4%

Volat

ility

5.7%

5.7%

6.2%

6.7%

4.4%

4.2%

4.5%

3.9%

4.5%

5.2%

5.9%

5.1%

4.2%

4.6%

3.9%

4.2%

5.1%

4.3%

5.5%

6.6%

5.0%

4.5%

4.2%

4.8%

IR0.1

90.1

40.1

20.6

10.5

40.6

60.5

61.0

60.4

10.6

80.1

4-0

.070.5

40.4

60.6

60.

870.6

40.4

40.3

10.5

60.

570.4

90.5

60.7

0Co

rrelat

ion w

ith tr

ade-

weigh

ted U

SD0.1

5-0

.02-0

.17-0

.030.0

70.0

2-0

.12-0

.01-0

.090.0

5-0

.16

0.08

0.09

-0.1

6-0

.060.

160.1

4-0

.10-0

.16

-0.08

0.19

0.02

0.00

0.05

Corre

lation

with

VXY

0.27

0.38

0.27

0.33

0.30

0.41

0.33

0.44

0.00

0.55

0.33

0.31

0.52

0.42

0.31

0.51

0.26

0.21

0.31

0.33

0.52

0.44

0.52

0.54

1992

- 19

98 (1

st h

alf)

Annu

alise

d retu

rn0.1

%1.5

%0.4

%4.4

%2.1

%4.0

%2.9

%4.9

%3.2

%3.2

%-1

.7%-1

.6%4.2

%3.6

%3.8

%5.1

%4.3

%1.7

%1.2

%3.

8%5.1

%3.

7%3.9

%5.3

%Vo

latilit

y3.9

%3.7

%4.4

%3.5

%3.8

%2.8

%3.4

%2.9

%4.8

%3.3

%4.3

%1.

3%2.9

%4.0

%3.2

%2.7

%4.8

%2.9

%4.6

%3.

3%6.0

%4.

6%3.3

%3.9

%IR

0.02

0.42

0.08

1.27

0.56

1.42

0.86

1.67

0.66

0.95

-0.4

0-1

.251.4

30.8

81.1

91.

890.9

00.5

70.2

51.1

50.

840.8

01.2

01.3

6Co

rrelat

ion w

ith tr

ade-

weigh

ted U

SD0.4

50.0

1-0

.150.1

00.3

80.1

00.0

20.2

1-0

.090.0

5-0

.16

0.08

0.28

0.06

-0.08

0.00

0.22

-0.02

-0.1

10.1

50.

350.3

30.1

40.2

6Co

rrelat

ion w

ith V

XY0.3

70.4

80.1

50.4

80.3

70.5

70.3

20.5

40.0

00.5

50.3

30.3

10.5

30.4

70.2

90.

480.5

30.3

10.2

50.4

20.

730.6

10.5

70.6

7

1999

- 20

06 (2

nd h

alf)

Annu

alise

d retu

rn2.0

%0.2

%1.1

%3.7

%2.5

%1.6

%2.2

%3.6

%0.7

%3.9

%3.1

%0.

7%0.6

%0.9

%1.5

%2.5

%2.3

%2.1

%2.2

%3.

6%1.0

%0.

9%1.0

%1.7

%Vo

latilit

y7.0

%7.3

%7.7

%8.9

%5.1

%5.0

%5.5

%4.8

%4.2

%6.7

%6.3

%6.

9%4.1

%4.3

%4.2

%4.7

%5.4

%5.4

%6.5

%8.

9%3.2

%4.

2%4.6

%5.1

%IR

0.29

0.03

0.14

0.42

0.50

0.32

0.40

0.75

0.16

0.58

0.49

0.10

0.14

0.20

0.36

0.53

0.43

0.38

0.34

0.41

0.31

0.21

0.21

0.33

Corre

lation

with

trad

e-we

ighted

USD

0.24

-0.18

-0.31

-0.18

0.04

-0.26

-0.35

-0.31

-0.14

-0.33

-0.3

2-0

.50-0

.14-0

.35

-0.44

-0.49

0.02

-0.19

-0.2

7-0

.22-0

.38-0

.44-0

.51-0

.47

Corre

lation

with

VXY

0.30

0.38

0.46

0.34

0.24

0.30

0.38

0.36

-0.19

0.37

0.18

0.16

0.26

0.29

0.38

0.42

0.08

0.21

0.45

0.41

0.26

0.31

0.52

0.51

2007

- Q2

200

8 (ou

t of s

ampl

e)An

nuali

sed r

eturn

-1.3%

-3.1%

5.0%

6.8%

5.4%

4.4%

8.7%

9.6%

-7.6%

4.0%

2.4%

8.2%

2.1%

2.1%

5.8%

6.1%

1.2%

2.4%

8.3%

8.2%

4.1%

4.6%

7.5%

7.2%

Volat

ility

5.8%

5.5%

6.3%

7.0%

4.8%

4.9%

5.5%

6.0%

5.3%

4.5%

5.6%

5.6%

4.8%

5.2%

5.6%

5.9%

4.2%

3.4%

5.2%

5.4%

3.9%

3.6%

4.5%

4.4%

IR-0

.22-0

.570.8

00.9

71.1

30.9

01.5

81.6

1-1

.440.9

00.4

31.4

60.4

40.4

11.0

41.

030.2

90.6

91.5

91.5

11.

061.3

01.6

81.6

3Co

rrelat

ion w

ith tr

ade-

weigh

ted U

SD0.3

4-0

.20-0

.93-0

.90-0

.80-0

.89-0

.95-0

.940.5

5-0

.60-0

.82

-0.92

-0.63

-0.8

3-0

.94-0

.88-0

.52-0

.77-0

.95

-0.94

-0.88

-0.91

-0.94

-0.9

4Co

rrelat

ion w

ith V

XY-0

.420.0

60.8

80.8

20.7

10.8

00.9

00.8

8-0

.610.4

50.7

40.8

20.5

20.7

30.8

80.

790.5

40.7

70.9

20.8

90.

850.8

80.9

00.9

0

Tran

sacti

ons p

er m

onth

17.5

10.1

7.13.9

15.1

12.0

10.7

9.27.6

4.23.

31.8

2.01.0

1.01.

04.2

2.31.5

0.94.2

2.31.5

0.9Ma

x gain

(mon

thly)

-4.9%

-3.5%

-4.7%

-6.0%

-5.2%

-2.8%

-2.1%

-2.7%

-4.2%

-4.2%

-3.9%

-4.4%

-2.9%

-2.9%

-2.9

%-2

.9%-4

.5%-5

.3%-4

.9%-5

.7%-2

.7%-2

.9%-3

.0%-3

.0%Ma

x los

s (mo

nthly)

5.5%

4.9%

4.5%

6.4%

4.4%

3.9%

3.9%

3.8%

3.5%

4.2%

4.5%

3.6%

2.7%

3.0%

3.3%

3.3%

5.0%

4.6%

4.6%

6.5%

4.7%

5.3%

5.3%

5.3%

Max d

rawd

own

-13.6

%-1

5.2%

-15.8

%-2

3.8%

-10.4

%-6

.2%-7

.6%-4

.6%-1

7.1%

-7.8%

-15.7

%-1

5.7%

-10.0

%-8

.7%-8

.8%

-6.2%

-8.3%

-14.4

%-1

3.4%

-12.2

%-4

.5%-1

0.1%

-9.2%

-6.7%

Mont

hly r

ebala

ncing

Total

retu

rn m

omen

tum

To

tal r

eturn

with

ove

rlay

Tota

l retu

rn m

omen

tum

To

tal r

eturn

with

ove

rlay

Daily

reba

lancin

gW

eekly

reba

lancin

g

Total

retu

rn m

omen

tum

Tota

l retu

rn w

ith o

verla

y

20



Appendix Chart 1. Annual returns on Standard Carry, USD pairs andMost-liquid G-10 pairs

Appendix Chart 3. Annual returns on Forward Carry Overlay (dailymodel), USD pairs and Most-liquid G-10 pairs

Appendix Chart 4. Annual returns on Forward Carry Overlay (monthlymodel), USD pairs and Most-liquid G-10 pairs

Appendix Chart 2. Annual returns on Forward Carry, USD pairs andMost-liquid G-10 pairs

Appendix Chart 5. Annual returns on spot momentum, 12-molookback, daily model, USD pairs and Most-liquid G-10 pairs

Appendix charts

Appendix Chart 8. Annual returns on total return momentum with overlay,12-mo lookback, daily model, USD pairs and Most-liquid G-10 pairs

Appendix Chart 6. Annual returns on spot momentum with overlay,12-mo lookback, daily model, USD pairs and Most-liquid G-10 pairs

Appendix Chart 7. Annual returns on total return momentum, 12-molookback, daily model, USD pairs and Most-liquid G-10 pairs

Source: JPMorgan

-15%-10%

-5%0%5%

10%15%20%25%30%

92 94 96 98 00 02 04 06 08

USD pairsMost-liquid G-10 pairs

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

92 94 96 98 00 02 04 06 08

US pairsMost-liquid G-10 pairs

-10%

-5%

0%

5%

10%

15%

20%

92 94 96 98 00 02 04 06 08


-10%

-5%

0%

5%

10%

15%

20%

92 94 96 98 00 02 04 06 08


-4%

-2%

0%

2%

4%

6%

8%

10%

12%

92 94 96 98 00 02 04 06 08


-10%

-5%

0%

5%

10%

15%

20%

92 94 96 98 00 02 04 06 08


-10%

-5%

0%

5%

10%

15%

20%

25%

30%

92 94 96 98 00 02 04 06 08


-10%

-5%

0%

5%

10%

15%

20%

25%

30%

92 94 96 98 00 02 04 06 08


21



Appendix Table 9. Model summary for USD pairs

Appendix Table 10. Model summary for Most-liquid G-10 pairs

Source: JPMorgan

Carry model

Standard carry Forward Carry Forward Carry Overlay, daily

Forward Carry Overlay, monthly

Spot momentum (12-mo lookback, daily

rebalance)

Spot momentum (12-mo lookback, monthly

rebalance)

Best-of basket (top 3 pairs, 12-mo lookback,

monthly rebalance)

Forward Momentum Overlay (12-mo lookback,

daily rebalance)


monthly rebalance)

1992 - 2006 (full sample)Annualised return 5.6% 4.0% 5.9% 5.0% 3.9% 3.6% 4.2% 3.8% 3.3%Volatility 6.9% 5.1% 8.1% 8.7% 6.7% 6.4% 6.0% 4.0% 5.0%IR 0.81 0.80 0.73 0.58 0.59 0.56 0.69 0.96 0.66Correlation with trade-weighted USD -0.19 -0.13 -0.22 -0.07 -0.04 -0.09 -0.15 -0.05 0.04Correlation with VXY -0.17 0.16 0.13 0.13 0.39 0.41 0.37 0.47 0.62

1992 - 1998 (1st half)Annualised return 2.2% 4.6% 6.6% 6.3% 4.6% 3.7% 3.3% 4.4% 5.2%Volatility 6.9% 5.5% 5.6% 6.4% 3.7% 3.4% 2.9% 3.5% 4.8%IR 0.31 0.84 1.17 0.99 1.25 1.10 1.16 1.27 1.09Correlation with trade-weighted USD 0.25 0.24 0.38 0.34 0.13 0.25 0.06 0.20 0.29Correlation with VXY -0.41 0.40 0.00 -0.05 0.57 0.60 0.48 0.55 0.75

1999 - 2006 (2nd half)Annualised return 8.7% 3.6% 5.3% 3.8% 3.3% 3.5% 4.9% 3.3% 1.7%Volatility 6.7% 5.1% 10.2% 10.6% 8.7% 8.5% 8.0% 4.6% 4.9%IR 1.28 0.70 0.52 0.36 0.37 0.42 0.62 0.73 0.34Correlation with trade-weighted USD -0.18 -0.11 -0.55 -0.40 -0.18 -0.20 -0.19 -0.31 -0.47Correlation with VXY 0.14 0.03 0.29 0.32 0.38 0.45 0.41 0.39 0.55

2007 - Q2 2008 (out of sample)Annualised return -0.1% 13.2% 9.2% 8.6% 6.6% 8.3% 4.0% 9.5% 7.3%Volatility 5.2% 6.0% 9.7% 10.5% 6.8% 5.5% 9.9% 5.9% 4.4%IR -0.01 2.21 0.95 0.81 0.98 1.51 0.55 1.62 1.64Correlation with trade-weighted USD 0.06 -0.74 -0.70 -0.59 -0.92 -0.95 -0.53 -0.94 -0.94Correlation with VXY -0.13 0.60 0.60 0.51 0.84 0.90 0.33 0.88 0.90

# transactions per month 0.5 15 2.9 0.9 4.4 0.9 0.8 9.4 0.9Max loss (monthly) 5.3% 4.1% 6.5% 6.5% 6.4% 6.5% 7.3% 3.9% 5.3%Max gain (monthly) -6.5% -4.1% -3.9% -4.9% -6.0% -5.7% -8.9% -2.6% -3.0%Max drawdown -17.6% -7.0% -8.1% -17.1% -15.9% -10.9% -14.8% -6.0% -5.7%

Forward Carry models Momentum models

Carry model

Standard carry Forward Carry Forward Carry Overlay, daily

Forward Carry Overlay, monthly

Spot momentum (12-mo lookback, daily

rebalance)

Spot momentum (12-mo lookback, monthly

rebalance)

Best-of basket (top 3 pairs, 12-mo lookback,

monthly rebalance)


daily rebalance)


monthly rebalance)

1992 - 2006 (full sample)Annualised return 4.4% 3.7% 5.6% 5.5% 2.6% 2.6% 3.9% 2.6% 2.2%Volatility 5.6% 3.3% 5.7% 7.1% 4.8% 4.2% 6.0% 2.6% 3.6%IR 0.77 1.10 0.98 0.77 0.54 0.61 0.65 1.01 0.61Correlation with trade-weighted USD -0.17 -0.21 -0.11 -0.15 -0.02 -0.06 -0.15 -0.14 0.05Correlation with VXY -0.08 0.14 0.12 0.17 0.32 0.37 0.35 0.38 0.57

1992 - 1998 (1st half)Annualised return 2.1% 4.3% 6.7% 6.2% 3.3% 3.1% 2.9% 2.9% 3.7%Volatility 6.5% 3.6% 3.2% 5.9% 2.5% 1.8% 3.3% 1.7% 3.1%IR 0.33 1.20 2.09 1.04 1.36 1.72 0.86 1.78 1.21Correlation with trade-weighted USD 0.25 0.23 0.68 0.52 -0.04 0.06 0.07 0.11 0.34Correlation with VXY -0.13 0.35 -0.02 0.04 0.37 0.43 0.41 0.42 0.69

1999 - 2006 (2nd half)Annualised return 6.3% 3.2% 4.6% 4.8% 1.9% 2.1% 4.7% 2.3% 0.9%Volatility 4.7% 3.2% 7.4% 8.3% 6.3% 5.7% 7.7% 3.3% 3.7%IR 1.33 0.97 0.63 0.58 0.30 0.36 0.61 0.71 0.24Correlation with trade-weighted USD -0.41 -0.23 -0.66 -0.65 -0.20 -0.20 -0.22 -0.40 -0.49Correlation with VXY 0.14 0.05 0.21 0.30 0.38 0.48 0.42 0.41 0.55

2007 - Q2 2008 (out of sample)Annualised return -1.8% 9.0% 4.9% 6.6% 3.3% 5.1% 3.6% 5.9% 4.5%Volatility 5.3% 4.2% 7.1% 8.1% 5.1% 4.0% 9.9% 4.2% 3.2%IR -0.34 2.17 0.69 0.81 0.66 1.26 0.52 1.38 1.44Correlation with trade-weighted USD 0.86 -0.92 0.22 0.09 -0.81 -0.93 -0.34 -0.89 -0.93Correlation with VXY -0.93 0.84 -0.41 -0.27 0.69 0.87 0.12 0.79 0.88

# transactions per month 1.0 25 6.0 2.0 8.3 1.7 0.9 15.8 1.8Max loss (monthly) 4.2% 3.0% 5.3% 6.0% -3.9% 4.1% 7.3% -2.9% -2.6%Max gain (monthly) -9.1% -2.8% -4.0% -5.7% 4.1% -3.9% -8.6% 3.0% 2.8%Max drawdown -20.8% -4.4% -9.6% -10.4% -11.1% -8.5% -14.8% -3.8% -5.0%

Forward Carry models Momentum models

22



Investable Indices & Alpha Strategies is available onwww.morganmarkets.com, by subscription and in FXMarkets Weekly.

This weekly publication provides performance statistics onJPMorgan’s passive/benchmark products in currencies andcommodities, and recommendations from alpha strategies.The report has six components:

1. List of index products on implied volatility for G-10 andemerging markets (VXYTM, VXY-EMTM); carry-adjusted,trade-weighted currency indices (Tradeable CurrencyIndices); and commodity markets (JPMorgan CommodityCurve Index).

2. List of alpha strategies such as carry (G-10 and EM),Forward Carry, Forward Carry Overlay and Momentum

3. JPMorgan investable products giving access to indicesand alpha strategies, where available.

4. Current recommendations for alpha strategies.

5. P&L for each index and alpha strategy. For indices, P&Lassumes the investor is long, though each of the indicescan also be sold short for bearish trades.

6. Metrics and performance charts for indices and strategies.6

3

2

1

4

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Global FX StrategyJ.P. Morgan Securities Ltd.June 27, 2008

• Currency indicesDuring the week G-10 implied vol rose 0.2% in contrast toEM vol which fell 0.1%. YTD the G-10 vol index is roughlyflat while the EM index up 0.9%.

JPY was the strongest performing currency last week -gaining 0.6% (up 2.1% YTD). Following weak economicdata, this week’s weakest performer was NZD which fell0.7%. GBP remains the largest decliner YTD (-5.4%) .

• Currency alpha strategiesAll three carry baskets rose last week; the G-10 carrybasket gained 0.2% and both the G-10 carry with overlaybasket and the EM carry basket were up 0.3%. YTD the G-

Index & Alpha Strategy Update

Source: JPMorgan www.morganmarkets.com

The certifying analyst is indicated by an AC. See page 3 for analyst certification and important legal and regulatory disclosures.

Table 1. Performance of indices and alpha strategies in currencies and commodities

10 carry basket is down 3% while the G-10 overlay and EMcarry baskets are up 3.6% and 1.9% respectively. Theforward carry indices had contrasting performances lastweek; The USD pairs index declined 0.4% and is now up8.8% YTD while the Major pairs index rose 0.1% and is up4.9% YTD.

• Commodity indicesThe aggregate index gained 2.2% last week following therise in energy and is up 37.9% YTD.

• Commodity alpha strategiesThe long-only momentum index fell 0.7% last week but isup 23.8% YTD. The Optimax (market neutral) index rose0.8% and is up 1.3% YTD.

John NormandAC (44-20) [email protected]

Kartik Ghia (44-20) [email protected]

Current

Product Positions level 1W 1M 3M 12M YTD

FOREIGN EXCHANGE

Indices/Benchmarks

G-10 implied volatility VXYTM

NA 10.1% 0.2% -0.1% -2.3% 3.9% 0.1%

EM implied volatility EM-VXYTM

NA 9.3% -0.1% -0.9% -1.3% 2.5% 0.9%

USD trade-weighted* USD TCI NA 79.4 -0.4% 0.4% 0.5% -8.4% -3.6%

EUR trade-weighted EUR TCI NA 143.1 0.5% 0.6% 0.7% 10.6% 5.1%

GBP trade-weighted* GBP TCI NA 92.3 -0.2% -0.1% 0.1% -11.6% -5.4%

JPY trade-weighted JPY TCI NA 83.9 0.6% -1.8% -6.8% 9.4% 2.1%

AUD trade-weighted AUD TCI NA 136.9 0.3% -0.1% 6.3% 6.1% 6.5%

NZD trade-weighted* NZD TCI NA 131.8 -0.7% -3.4% -4.4% -9.2% -5.3%

CNY trade-weighted CNY TCI NA 103.9 -0.1% 1.5% 4.5% 3.2% 3.5%

TCIs also available for NOK, CHF, CAD, SEK, MXN, HKD, KRW, SGD & TWD.

Alpha strategies

G-10 carry IncomeFX Long GBP/USD, NZD/USD, EUR/CHF, AUD/USD 98.8 0.2% -0.6% 1.1% -13.2% -3.0%

NA Long EUR/USD, EUR/CHF and EUR/JPY 294.4 0.3% 0.2% 0.8% -0.5% 3.6%

Emerging Markets carry IncomeEM 109.6 0.3% 2.6% 7.2% 8.7% 1.9%

Forward Carry (USD pairs) NA 240.3 -0.4% -0.6% 1.9% 15.3% 8.8%

Forward Carry (Major pairs) NA 244.2 0.1% 1.0% 3.0% 6.4% 4.9%

COMMODITIES

Indices/Benchmarks

Aggregate (35 commodities) JPMCCI NA 367.7 2.2% 7.4% 20.8% 55.2% 37.9%

Alpha strategies

Momentum - Long only C-IGAR 163.3 -0.7% 5.8% 10.0% 43.4% 23.8%

Momentum - Long/Short C-IGAR L/S 151.2 0.9% 6.9% 11.5% 35.2% 21.9%

Optimax 103.04 0.8% 0.6% 4.3% 7.5% 1.3%

* Although TCI returns in the table assume the investor is long the index, the product can also be sold to express a bearish view on the currency against major trading partners.

G-10 carry with Forward Overlay

Change (VXY, EM-VXY) or Returns (all others)

Short USD/PHP, USD/TRY and USD/MXN; Long USD/HKD and

USD/CNY

As above, plus long EUR vs NOK, GBP SEK, CHF and JPY; Short

JPY vs CAD, NOK, GBP, AUD and long JPY vs NZD; Long AUD vs

CAD, NZD; long NOK/SEK

Brent, WTI, Gas Oil, Gasoline, Heating Oil, Silver, Gold, Copper,

Soybean, Red Wheat, Corn, Cocoa

Long as above, plus short Zinc, Nickel, Lead, Aluminium, Sugar,

Feeder Cattle

Long Brent,WTI,Gas Oil,Silver,Lead,Copper,Lead,Coffee; Short

Gasoline,Heating Oil,Natural Gas,Gold,Zinc,Nickel,

Aluminium,Wheat,Sugar

Short USD vs CAD and EUR; Long USD vs NOK, GBP, SEK, CHF,

AUD, JPY and NZD

Momentum - Optimax (Market

Neutral)

2

13

5

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Global FX StrategyIndex & Alpha Strategy Update


Kartik Ghia (44-20) [email protected]

Chart 1. Carry-to-risk rankings for G-10 currenciesCarry-to-risk = 1mo libor differentials/annualised daily spot vol over past 12

months. First currency listed is the long leg.

Chart 2. Carry-to-risk rankings for Emerging Markets currenciesCarry-to-risk = 1-mo implied rate differential from NDF or forward/annualised

daily vol of forward outright rate over past 3 months. First currency listed is

the long leg.

Chart 3. VXYTM vs EM-VXYTM indices of implied volatility%, based on 3mo ATMF options

Source: JPMorgan

Source: JPMorgan

Source: JPMorgan

Chart 5. JPMCCI vs Commodity IGAR (Long-only, Long/Short andConditional Long/Short momentum)indexed, Jan 2008 = 100, excess returns

Source: JPMorgan

Chart 6. JPMCCI sector returnsindexed, Jan 2008 = 100, excess returns

Source: JPMorgan

Chart 4. Performance of FX alpha strategiesYTD performance

0

0.1

0.2

0.3

0.4

0.5

GB

P v

s U

SD

NZ

D v

s U

SD

EU

R v

s C

HF

AU

D v

s U

SD

NO

K v

s U

SD

EU

R v

s JP

Y

NO

K v

s E

UR

EU

R v

s U

SD

SE

K v

s U

SD

US

D v

s JP

Y

GB

P v

s E

UR

CA

D v

s U

SD

SE

K v

s E

UR

US

D v

s C

HF

0.0

0.5

1.0

1.5

2.0

PH

P v

s $

$ vs

HK

D

TR

Y v

s $

MX

N v

s $

$ vs

CN

Y

BR

L vs

$

ZA

R v

s $

INR

vs

$

CO

P v

s $

HU

F v

s $

RU

B v

s $

PLN

vs

$

SG

D v

s $

AR

S v

s $

CLP

vs

$

$ vs

TW

D

SK

K v

s $

ILS

vs

$

CZ

K v

s $

KR

W v

s $

4

6

8

10

12

14

16

Jan-06 Jun-06 Nov-06 Apr-07 Sep-07 Feb-08

VXY

EM-VXY

85

90

95

100

105

110

Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08

G-10 carry

Emerging markets carry

G-10 carry with Forward Overlay

Forward Carry

80

85

90

95

100

105

110

115

120

125

130


JPMCCI

C-IGAR Long-only

C-IGAR L/S

Optimax (Market Neutral)

80

90

100

110

120

130

140

150

160


Energy Precious metals

Industrial metals Agriculture

6

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Analyst certification: The research analyst(s) denoted by an “AC” on the cover of this report (or, where multiple research analysts are primarily responsible for this report, the researchanalyst denoted by an “AC” on the cover or within the document individually certifies, with respect to each security or issuer that the research analyst covers in this research) that:(1) all of the views expressed in this report accurately reflect his or her personal views about any and all of the subject securities or issuers; and (2) no part of any of the research analyst’scompensation was, is, or will be directly or indirectly related to the specific recommendations or views expressed by the research analyst(s) in this report. Explanation of Ratings:Ratings System: JPMorgan uses the following sector/issuer portfolio weightings: Overweight (over the next three months, the recommended risk position is expected to outperformthe relevant index, sector, or benchmark), Neutral (over the next three months, the recommended risk position is expected to perform in line with the relevant index, sector, or benchmark),and Underweight (over the next three months, the recommended risk position is expected to underperform the relevant index, sector, or benchmark). JPMorgan’s Emerging Marketresearch uses a rating of Marketweight, which is equivalent to a Neutral rating. Valuation & Methodology: In JPMorgan’s credit research, we assign a rating to each issuer(Overweight, Underweight or Neutral) based on our credit view of the issuer and the relative value of its securities, taking into account the ratings assigned to the issuer by creditrating agencies and the market prices for the issuer’s securities. Our credit view of an issuer is based upon our opinion as to whether the issuer will be able service its debt obligationswhen they become due and payable. We assess this by analyzing, among other things, the issuer’s credit position using standard credit ratios such as cash flow to debt and fixed chargecoverage (including and excluding capital investment). We also analyze the issuer’s ability to generate cash flow by reviewing standard operational measures for comparablecompanies in the sector, such as revenue and earnings growth rates, margins, and the composition of the issuer’s balance sheet relative to the operational leverage in its business.Analysts’ Compensation: The research analysts responsible for the preparation of this report receive compensation based upon various factors, including the quality and accuracyof research, client feedback, competitive factors and overall firm revenues. The firm’s overall revenues include revenues from its investment banking and fixed income business units.

Other Disclosures: JPMorgan is the global brand name for J.P. Morgan Securities Inc. (JPMSI) and its non-US affiliates worldwide. Options related research: If the informationcontained herein regards options related research, such information is available only to persons who have received the proper option risk disclosure documents. For a copy of theOption Clearing Corporation’s Characteristics and Risks of Standardized Options, please contact your JPMorgan Representative or visit the OCC’s website at http://www.optionsclearing.com/publications/risks/riskstoc.pdf. Legal Entities Disclosures: U.S.: JPMSI is a member of NYSE, FINRA and SIPC. J.P. Morgan Futures Inc. is a memberof the NFA. JPMorgan Chase Bank, N.A. is a member of FDIC and is authorized and regulated in the UK by the Financial Services Authority. U.K.: J.P. Morgan Securities Ltd. (JPMSL)is a member of the London Stock Exchange and is authorised and regulated by the Financial Services Authority. Registered in England & Wales No. 2711006. Registered Office125 London Wall, London EC2Y 5AJ. South Africa: J.P. Morgan Equities Limited is a member of the Johannesburg Securities Exchange and is regulated by the FSB. Hong Kong:J.P. Morgan Securities (Asia Pacific) Limited (CE number AAJ321) is regulated by the Hong Kong Monetary Authority and the Securities and Futures Commission in Hong Kong.Korea: J.P. Morgan Securities (Far East) Ltd, Seoul branch, is regulated by the Korea Financial Supervisory Service. Australia: J.P. Morgan Australia Limited (ABN 52 002 888011/AFS Licence No: 238188) is regulated by ASIC and J.P. Morgan Securities Australia Limited (ABN 61 003 245 234/AFS Licence No: 238066) is a Market Participant withthe ASX and regulated by ASIC. Taiwan: J.P.Morgan Securities (Taiwan) Limited is a participant of the Taiwan Stock Exchange (company-type) and regulated by the Taiwan Securitiesand Futures Bureau. India: J.P. 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Ltd is a member of the Karachi Stock Exchange and regulated by the Securities and Exchange Commission of Pakistan. Country and Region SpecificDisclosures: U.K. and European Economic Area (EEA): Issued and approved for distribution in the U.K. and the EEA by JPMSL. Investment research issued by JPMSL has beenprepared in accordance with JPMSL’s Policies for Managing Conflicts of Interest in Connection with Investment Research which outline the effective organisational and admin-istrative arrangements set up within JPMSL for the prevention and avoidance of conflicts of interest with respect to research recommendations, including information barriers,and can be found at http://www.jpmorgan.com/pdfdoc/research/ConflictManagementPolicy.pdf. This report has been issued in the U.K. only to persons of a kind described inArticle 19 (5), 38, 47 and 49 of the Financial Services and Markets Act 2000 (Financial Promotion) Order 2005 (all such persons being referred to as “relevant persons”). Thisdocument must not be acted on or relied on by persons who are not relevant persons. Any investment or investment activity to which this document relates is only available to relevantpersons and will be engaged in only with relevant persons. In other EEA countries, the report has been issued to persons regarded as professional investors (or equivalent) in theirhome jurisdiction Germany: This material is distributed in Germany by J.P. Morgan Securities Ltd. Frankfurt Branch and JPMorgan Chase Bank, N.A., Frankfurt Branch who areregulated by the Bundesanstalt für Finanzdienstleistungsaufsicht. Australia: This material is issued and distributed by JPMSAL in Australia to “wholesale clients” only. JPMSALdoes not issue or distribute this material to “retail clients.” The recipient of this material must not distribute it to any third party or outside Australia without the prior written consentof JPMSAL. For the purposes of this paragraph the terms “wholesale client” and “retail client” have the meanings given to them in section 761G of the Corporations Act 2001. HongKong: The 1% ownership disclosure as of the previous month end satisfies the requirements under Paragraph 16.5(a) of the Hong Kong Code of Conduct for persons licensed by orregistered with the Securities and Futures Commission. (For research published within the first ten days of the month, the disclosure may be based on the month end data from twomonths’ prior.) J.P. Morgan Broking (Hong Kong) Limited is the liquidity provider for derivative warrants issued by J.P. Morgan International Derivatives Ltd and listed on TheStock Exchange of Hong Kong Limited. An updated list can be found on HKEx website: http://www.hkex.com.hk/prod/dw/Lp.htm. Japan: There is a risk that a loss may occur dueto a change in the price of the shares in the case of share trading, and that a loss may occur due to the exchange rate in the case of foreign share trading. In the case of share trading,JPMorgan Securities Japan Co., Ltd., will be receiving a brokerage fee and consumption tax (shouhizei) calculated by multiplying the executed price by the commission rate whichwas individually agreed between JPMorgan Securities Japan Co., Ltd., and the customer in advance. Financial Instruments Firms: JPMorgan Securities Japan Co., Ltd., Kanto LocalFinance Bureau (kinsho) No. [82] Participating Association / Japan Securities Dealers Association, The Financial Futures Association of Japan. Korea: This report may have beenedited or contributed to from time to time by affiliates of J.P. Morgan Securities (Far East) Ltd, Seoul branch. 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Information has been obtained from sourcesbelieved to be reliable but JPMorgan Chase & Co. or its affiliates and/or subsidiaries (collectively JPMorgan) do not warrant its completeness or accuracy except with respect to anydisclosures relative to JPMSI and/or its affiliates and the analyst’s involvement with the issuer that is the subject of the research. All pricing is as of the close of market for the securitiesdiscussed, unless otherwise stated. Opinions and estimates constitute our judgment as of the date of this material and are subject to change without notice. Past performance is notindicative of future results. This material is not intended as an offer or solicitation for the purchase or sale of any financial instrument. The opinions and recommendations herein donot take into account individual client circumstances, objectives, or needs and are not intended as recommendations of particular securities, financial instruments or strategies toparticular clients. The recipient of this report must make its own independent decisions regarding any securities or financial instruments mentioned herein. JPMSI distributes in theU.S. research published by non-U.S. affiliates and accepts responsibility for its contents. Periodic updates may be provided on companies/industries based on company specificdevelopments or announcements, market conditions or any other publicly available information. Clients should contact analysts and execute transactions through a JPMorgansubsidiary or affiliate in their home jurisdiction unless governing law permits otherwise. “Other Disclosures” last revised June 30, 2008. Copyright 2008 JPMorgan Chase & Co.All rights reserved. This report or any portion hereof may not be reprinted, sold or redistributed without the written consent of JPMorgan.

24



24. Trading Credit Volatility, Saul Doctor and Alex Sbityokov,August 2006

25. Momentum in Commodities, Ruy Ribeiro, Jan Loeys andJohn Normand, September 2006

26. Equity Style Rotation, Ruy Ribeiro, November 2006

27. Euro Fixed Income Momentum Strategy, Gianluca Salford,November 2006

28. Variance Swaps, Peter Allen, November 2006

29. Relative Value in Tranches I, Dirk Muench, November2006

30. Relative Value in Tranches II, Dirk Muench, November2006

31. Exploiting carry with cross-market and curve bondtrades, Nikolaos Panigirtzoglou, January 2007

32. Momentum in Money Markets, Gianluca Salford, May2007

33. Rotating between G-10 and Emerging Markets Carry,John Normand, July 2007

34. A simple rule to trade the curve, Nikolaos Panigirtzoglou,August 2007

35. Markowitz in tactical asset allocation, Ruy Ribeiro andJan Loeys, August 2007

36. Carry-to-Risk for Credit Indices, Saul Doctor and JonnyGoulden, September 2007

37. Learning Curves – Curve Trading Using Model Signals,Jonny Goulden and Sugandh Mittal, October 2007

38. A Framework for Credit-Equity Investing, JonnyGoulden, Peter Allen and Stephen Einchcomb, November2007

39. Hedge Fund Alternatives, Ruy Ribeiro and Vadim diPietro, March 2008

40. Optimizing Commodities Momentum, Ruy Ribeiro andVadim di Pietro, April 2008

41. Momentum in Global Equity Sectors, Vadim di Pietro andRuy Ribeiro, May 2008

42. Cross-momentum for EM equity sectors, Vadim di Pietroand Ruy Ribeiro, May 2008

43. Trading the US curve, Grace Koo and NikolaosPanigirtzoglou, May 2008

44. Momentum in Emerging Markets Sovereign Debt, GeraldTan and William Oswald, May 2008

45. Active Strategies for 130/30 Emerging MarketsPortfolios, Gerald Tan and William Oswald, June 2008

46. Hedging Illiquid Assets, Peter Rappoport, July 2008

1. Rock-Bottom Spreads, Peter Rappoport, Oct 2001

2. Understanding and Trading Swap Spreads, LaurentFransolet, Marius Langeland, Pavan Wadhwa, GaganSingh, Dec 2001

3. New LCPI trading rules: Introducing FX CACI, LarryKantor, Mustafa Caglayan, Dec 2001

4. FX Positioning with JPMorgan’s Exchange RateModel, Drausio Giacomelli, Canlin Li, Jan 2002

5. Profiting from Market Signals, John Normand, Mar2002

6. A Framework for Long-term Currency Valuation,Larry Kantor and Drausio Giacomelli, Apr 2002

7. Using Equities to Trade FX: Introducing LCVI, LarryKantor and Mustafa Caglayan, Oct 2002

8. Alternative LCVI Trading Strategies, MustafaCaglayan, Jan 2003

9. Which Trade, John Normand, Jan 2004

10. JPMorgan’s FX & Commodity Barometer, JohnNormand, Mustafa Caglayan, Daniel Ko, NikolaosPanigirtzoglou and Lei Shen, Sep 2004

11. A Fair Value Model for US Bonds, Credit and Equi-ties, Nikolaos Panigirtzoglou and Jan Loeys, Jan 2005

12. JPMorgan Emerging Market Carry-to-Risk Model,Osman Wahid, February 2005

13. Valuing cross-market yield spreads, NikolaosPanigirtzoglou, January 2006

14. Exploiting cross-market momentum, Ruy Ribeiro andJan Loeys, February 2006

15. A cross-market bond carry strategy, NikolaosPanigirtzoglou, March 2006

16. Bonds, Bubbles and Black Holes, George Cooper,March 2006

17. JPMorgan FX Hedging Framework, RebeccaPatterson and Nandita Singh, March 2006

18. Index Linked Gilts Uncovered, Jorge Garayo andFrancis Diamond, March 2006

19. Trading Credit Curves I, Jonny Goulden, March 2006

20. Trading Credit Curves II, Jonny Goulden, March 2006

21. Yield Rotator, Nikolaos Panigirtzoglou, May 2006

22. Relative Value on Curve vs Butterfly Trades, StefanoDi Domizio, June 2006

23. Hedging Inflation with Real Assets, John Normand,July 2006

Investment Strategies SeriesThis series aims to offer new approaches and methods on investing and trading profitably in financial markets.

Fx Strategies

Documents

momentum strategies

jpmorgan forward carry

standard carry strategies

traditional carry trades

standard carry model

momentum trading

performance of momentum

standard approaches