Introducing iFlow PointEstimate• iFlow PointEstimate approximates flows into

market events, such as FOMC meetings

• Applied to the performance of hypotheticalcontrarian Perfect Foresight Managers,iFlow PointEstimate signals added value,particularly before the Fed tightening cycle

• We expect iFlow PointEstimate performanceto improve as FOMC easing advances

Daniel TenengauzerHead of Markets Strategy andInsights

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The Aerial ViewMorning Briefing

In this note we introduce iFlow PointEstimate, a BNY Mellon model that seeks to providethe best estimate of a flow parameter into any given financial, macro or policymakingevent.

In order to provide a practical demonstration of the tool and its potential value, in thispiece we will suggest and outline a simple application for this model: overlay a flowsignal into FOMC meetings using iFlow PointEstimate and examine the results.

Abstract

Our methodology was to first estimate the USD trading performance of hypotheticalperfect foresight managers (PFMs) around FOMC meetings since 2010, based on 75observations.

Then, with the help of our iFlow PointEstimate models, our analysis found that even themost experienced Fed watchers may improve performance trading USD exposurearound FOMC events. Since 2010, for example, PFMs overlaying iFlow PointEstimate totheir decision-making process would have improved returns from trading USD into Fedmeetings, particularly by saving in transaction costs.

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In fact, iFlow PointEstimate signals would have reduced transactions by a third whilekeeping returns unchanged at 3.5%. The Sharpe ratio of contrarian managers wouldhave improved from 0.079 to 0.12 (see Table A).

Using PFMs as a control group, we found that contrarian managers would have enjoyedgreatest success before 2015, while the Fed was neutral or easing, assuming contrarianPFMs entered positions only if flows into the event did not coincide with their projections.For instance, managers projecting a hawkish Fed would only buy USD into thecorresponding FOMC meeting if iFlow PointEstimate showed the market not to bebuying USD into the event.

Our results show that contrarian managers using iFlow PointEstimate would haveperformed better while Fed policy was neutral or easing. This is likely becausemeaningfully widening rate differentials dominate alternative trading signals, such aspositioning and flow.

Contrarian signals would help PFMs win in most FOMC events. Since 2010, PFMs havehad a 37/38 win/loss ratio. PFMs using the iFlow PointEstimate signal as a contrarianfilter would have had a 26/24 win/loss ratio. By comparison, managers using iFlowPointEstimate signal to enter positions with market flow would have an 11/14 win/lossratio.

Looking ahead, we believe contrarian iFlow PointEstimate strategies may startoutperforming as the Fed easing cycle advances and forward rates converge backagain.

Defining the Perfect Foresight Manager

We begin by defining the Perfect Foresight Manager. PFMs are managers that predictFOMC outcomes with 100% accuracy. In other words, regardless of the outcome, dovishor hawkish, PFMs will always be able to perfectly predict whether Fed Fund Futurescontracts will steepen or flatten.

PFMs therefore have an edge in forecasting FOMC outcomes. We define an FOMCoutcome as the differential between the first and second Fed Fund Futures contract pricefollowing the meeting.

For example, following hawkish outcomes the second contract will sell-off in relation tothe near contract as markets price out additional cuts. We roll these differentials overone week of trading days. On the day of the FOMC meeting we take the differentialbetween average prices of the five trading sessions following the meeting against theaverage of the five trading sessions prior to the meeting.

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Chart 1 shows fairly consistent outcomes up until Q2 2015. Subsequently, FOMCoutcomes have been consistently hawkish against the market and Fed Futuresconsequently steepened. More recently the Fed has sought to steer outcomes awayfrom the hawkish stance observed up until Q1 of 2019. This new bias has not been fullyabsorbed by the market: between July and August 2019 volatility in Fed Fund Futurescontracts increased substantially.

Given these two stances, we tested our iFlow PointEstimate exposure indicator overboth periods, first through 2010-2015, as the Fed maintained a neutral to dovish posture.Committee concerns during this period yielded small changes in the stance signal, witheach meeting more about calibration than actual policy change expectations. As a result,outcomes changed within a tight -3/+3 basis point range.

More recently outcome ranges have been as low as -20bp to as high as +40bp becauseeach meeting could have delivered a 25bp+ change.

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Control Group Results: PFMs Trade Well Into the FOMC

Our control group is an environment where the PFMs predict with 100% accuracy eachFOMC meeting outcome. We define a PFM prediction as the direction in which thespread changes between first and second Fed Fund Futures. Following hawkishmeetings the price of the second Fed Fund Future will decline in relation to the price offirst future. Expectations of interest rates increases in the US will drive these managersto buy USD.

When the PFMs predict a hawkish Fed, they will enter a USD bullish position, and viceversa. In our exercise we have chosen to buy and sell the Fed Broad Trade-WeightedUSD index. Table B shows the results of our control group trading strategy since 2010.

We found that PFMs were able to extract positive P/L in both hawkish and dovishoutcomes since 2015. Between 2010 and 2014, however, PFMs were not able to extractpositive returns from dovish meetings but were quite successful buying USD on hawkishoutcomes.

This successful result through hawkish meetings could have happened for two reasons.First, USD trends have been broadly to the upside throughout. Second, when the marketwas exposed to short USD positions, even when the FOMC result was dovish, marketswould quickly turn to lock-in profits.

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In sum, we researched trading USD around 75 FOMC events since 2010. Between 2010and 2015, PFMs would have extracted +1.74% returns from trading the USD around the37 FOMC meetings. Between 2010 and 2014, PFMs would have returned 1.8% in 38FOMC meetings. Through that period PFMs would not have performed well throughdovish meetings, however. The USD did not depreciate as much as expected followingdovish meetings. We show each individual result in a plot chart (Chart 5) in the lastsection of this note.

As shown in the next section, iFlow PointEstimate could have helped PFMs in navigatingFOMC meetings by extracting situations where the market was overbought or oversold.

PFM Results Overlaying iFlow PointEstimate Data

Once computing the control group trading results, we overlaid an iFlow PointEstimateexposure indicator to comb USD trading opportunities. We estimated USD exposure withthe help of a weekly trend of BNY Mellon iFlow PointEstimate aggregate FX flow data.

We calculated a z-score of the data, i.e. the number of standard deviations the flowcurrently stands against its moving average. Chart 4 shows bullish USD demand sincethe beginning of 2019. This followed a bias to reduce the pace of USD demand in H22018.

We tested FOMC USD trades under two distinct scenarios. First, PFMs would bebuying/selling USD through hawkish/dovish FOMC outcomes if iFlow PointEstimateshows market exposure to be long/short. We define long/short as a z-score in USDexposure above/below +/-0.5 standard deviations.

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The results show that the addition of USD position as a factor would worsen returns inUSD trades around FOMC meetings before 2015. In other words, PFMs would havetaken particularly large losses when trading along with market exposure when the Fedpolicy stance was neutral or easing. Going with the flow was not a good option duringthe quantitative easing era, yielding a -3.4% loss.

We found that since 2015, however, this has changed. Managers following USD demandwould have extracted positive returns in the years since 2015 around both hawkish anddovish FOMC meeting. This result is not a strong one, however, since it is based on justtwo observations, as Table C attests.

This result changed when applying a contrarian approach. Contrarian PFMs would onlybuy and sell USD when exposures are not particularly large. We define particularly largeas above the top +0.5 z-score in hawkish meetings and below -0.5 z-score in dovishmeetings. In other words, we applied iFlow PointEstimate to warn managers to avoidtrading the USD when exposures were meaningful in either direction.

We found this filter to be helpful during the period where the Fed was dovish or neutral.Since 2015 contrarian managers also performed well around dovish FOMC outcomes.Altogether, contrarian managers would only have executed 50 trades, compared to 75trades without the iFlow PointEstimate signal. The filter would save the managers one-third of their trading costs.

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Returns would have been almost the same at 3.5% since 2010. Since 2015, however,iFlow PointEstimate signaling would be less helpful. Managers applying an iFlowPointEstimate contrarian filter would have been flat over the period, compared to 1.7%and 1.8% returns for PFMs trading with no iFlow PointEstimate signal or with the iFlowPointEstimate signal.

Conclusion: Edge Helps but Contrarians Outperformed When the Fed was Idle

We studied the returns of perfect foresight managers throughout FOMC meetings since2010.

We found that a contrarian iFlow PointEstimate USD exposure signal would enhance thereturns of such managers into FOMC meetings while the Fed was idle or dovish. Thistrading strategy would have reduced trading costs while keeping returns broadly thesame.

We believe that as the Fed turns increasingly more dovish, managers with an FOMCedge can look to contrarian iFlow PointEstimate USD signals to improve returns.

As a next step, we will be looking to use iFlow PointEstimate to provide insight into anyevent that might have a meaningful implication to USD trading. These might be datareleases such as payroll and PMI or even unexpected social media market pertinentannouncements.

Please direct questions or comments to:

AerialView@BNYMellon.com

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The products and services described herein may contain or include certain “forecast” statements that may reflect possible future events based on current expectations. Forecast statements are neither historical facts nor assurances of future performance. Forecast statements typically include, and are not limited to, words such as “anticipate”, “believe”, “estimate”, “expect”, “future”, “intend”, “likely”, “may”, “plan”, “project”, “should”, “will”, or other similar terminology and should NOT be relied upon as accurate indications of future performance or events. Because forecast statements relate to the future, they are subject to inherent uncertainties, risks and changes in circumstances that are difficult to predict. iFlow® is a registered trademark of The Bank of New York Mellon Corporation under the laws of the United States of America and other countries.

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Currency Administration is provided under and subject to the terms of a definitive agreement between BNY Mellon and the client. BNY Mellon exercises no investment discretion thereunder, but acts solely pursuant to the instructions in such agreement or otherwise provided by the client. Unless provided by definitive agreement, BNY Mellon is not an agent or fiduciary thereunder, and acts solely as principal in connection with related foreign exchange transactions.

All references to dollars are in US dollars unless specified otherwise.

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Morning Briefing September 16 2019bnymellon.comBNY Mellon

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