## Saturday, March 25, 2017

### Markets | The Most Peculiar Positioning Build Up Since US Election

Last week's S&P sell-off was apparently a big news. We had some serious analyses why it happened like here and of course the usual noise about end of Trump trade and reflation trade. Also the indomitable cottage industry of the permabears quickly felt a sense of vindication. However, the real surprise was why it took so long for S&P 500 to suffer a 1% down day. If we have only one 1% down day since October (roughly say 100 trading days), it is equivalent to an approx 7% annualized vol. VIX has been near record low, but at the 12-13 handle, looks quite rich given this 7% realized (or a bit over 8% if the standard deviation of daily returns is used to calculate the annualized vol). In fact the realized volatilities are very very timid and just barely off the historical lows.

In this light one the most interesting development that I suspect few has noticed is the curious build up of S&P option positioning. CFTC publishes the participant-wise positioning data at both futures and combined levels. The combined data is calculated by adding the futures equivalent option positioning (delta equivalent) to the futures data. So the difference between these two shows us the net option positions in delta equivalent terms. And as the chart below shows, it has never been more peculiar.

Among the major categories in CFTC reports, asset managers at present have a historically large short positions in options, against the dealers and the CTA/ leveraged  money managers. This is a remarkable build-up of positions since the US presidential election. It is interesting to note the usual trading incentives of these major players. The dealers are mostly market makers and their positions are in general reflective of other players' views. Leveraged/ CTA funds, to a large extent, are momentum driven. The asset managers on the other hands perhaps represent the most discretionary part, although most of them will be long-only players. In fact they as a group have built up a combined long position after the US election results - no surprise there. Along with this particularly interesting short build up in options space - quite unexpectedly.

The large short delta equivalent option positions from asset managers can be built in two ways. Buying puts - which is a common hedging strategy for the asset managers, or selling (covered) call - which is again a very standard income strategy. But their impact on the market dynamics are quite different. We do not have enough information above to see which one is more dominant. So to do that we look at what the behavior of S&P 500 price itself tells us.

From the chart above, we see the dealers positioning mirrors that of the asset managers. If the asset managers are mostly long puts, that will mean dealers are short puts and hence short gamma. On the other hands if the asset managers are net short delta equivalent in options through short calls, the dealers will be net long gamma (long calls). And since the dealers, as market makers, will tend to run a hedged book - this will lead to some expected gamma signature in the market dynamics. When the dealers are net long gamma, they will tend to sell in a rally and buy in a sell-off (sticky gamma). This will have a stabilizing effect on S&P. The reverse is true when they are net short gamma (slippery gamma), a move reinforcing itself away from stability. We compute an approximate measures of this relationship. First we see the how much the open to low move is reversed by low to close move for each day in a given time period (20 days) for S&P 500. Then we use least square regression to estimate a beta between these two moves. This beta signifies how likely in a given day, a down move will witness opposing flows to reverse it completely or partially. A high beta signifies a large pressure of opposing flow (beta = 1 means all downside move reversed by day end). The major drivers in this reversal will be the dealers long gamma hedging activities and potentially the buy-the-dip or momentum flows from other players (apart from other flows which we assume to have a zero net effect on the balance over a time periods). We call this beta (kernel-smoothed to capture the trend) downside gamma. The chart below shows this juxtaposed with the above positioning data, as well as S&P 500.

The interesting thing to note that during the last large short delta equivalent option positioning build up by asset managers (following Brexit), the downside gamma measure actually dipped, signifying a net short gamma for the dealers, and hence long put positioning from the asset managers. The current positioning, following the same logic, points to a large short call positioning from the asset managers. In fact there were some noises around this in February as well. As a result of this, the recent moves in S&P has been remarkably resilient. However as of last Tuesday's (21st March) data, it seems this long gamma positioning is coming off from the peak. Which has also coincided with a reduction in net short delta positioning of the asset managers in the option space. Theoretically, this means we can now expect a pick up in realized volatility in S&P. And it is time to shelve the buying-the-dip intraday strategy till the next opportunity comes.

## Wednesday, March 22, 2017

### Off Topic: A Package to Send Text Messages From R

If you often run long processes in R and want to get the results notified to you once finished, but not always around to check it on the terminal, this is a very useful package.

Texting the message using a third party service like Twilio is a great alternative. They offer a free-tier account (with no expiry as they claim). If you are not a heavy user, my best guess is that will be sufficient in most cases. This package simply wraps the REST API interface from Twilio for the simple text messaging service inside an R package for convenience. All that is needed is signing up for the service and obtain the assigned mobile number, and authentication details and you are good to go. I am not sure about the restrictions on international texts, but this works fine for me for local texts. Results direct to my mobile with insignificant time delay.

You can download the package from here. The installation and usage (pretty straightforward) are in the readme file in the repository.

## Friday, February 24, 2017

### FOMC | The Ides of March

We have quite a bit of built up anticipation for the March FOMC. The Fedspeak analysis of "Fairly Soon" has been interpreted by most as leaning towards a March hike. Some are even claiming the rates markets are underestimating the probability of a March hike.
The chart above shows implied 3-month treasury forward curve term structure since the 2014 (after the highs from 2013 Taper Tantrum). In early 2014 the market estimates of long run equilibrium rates were just about 4 percent. Since then we have come a long way. As we see we have three major clustering of market estimates - one at around sub 2 percent (during Brexit rally), another just above 2 percent (early 2016) and the most common level at just about 3 percent. The sell-off after the US presidential election has just brought us back to this 3 percent level. Coincidentally, after disagreeing with the markets on this long run terminal rate for a long time (erring consistently on the upper side), the FOMC also now more or less agrees with this level. So after quite a while markets and the FOMC seem to have converged in outlook.

Given this background, I think whether the FOMC hikes in March or not is now a far less important question than what it used to be a couple of years or even a year back. Before March FOMC, we have a round of PCE (Fed's favored measure of inflation) as well as employment and GDP data release scheduled. Unless we have a major upward surprise, March probably will be a no-hike meeting. And more importantly, given the improving economy, markets are in a much better position to absorb a hike anyways. The US and global inflation are improving, but it is much tamed than the "reflation trades" coverage makes it sound. Inflation was a worry (on the downside) before, now slowly it is ceasing to be so. There are few signs the FOMC is behind the curve as of now.

What can really take the market off-guard, is however, the question of Fed balance sheet. If and when FOMC plans to reduce its QE-bloated balance sheet, and how they communicate this point. Hiking is a way of tightening. But a controlled balance sheet reduction is also another way. While the former affect the short term rates more (a bear flattening), the later should be more prone to affect the long end rates (bear steepening). A reason why FOMC may actually opt this is to address the historically compressed risk premia - see the left chart below. Even with the recent sell-off, the risk premia remain at a depressed levels. The short end pressure felt on the back of FOMC moves more or less leaned towards a flattening of the curve than any significant correction of risk premia. While the European and Japanese bonds are trading at super-depressed levels, perhaps it is not entirely to the Fed to correct this. But adjusting balance sheet is definitely a direct way to address this.

The most important reason NOT to do this it the unpredictable potential impact. This has the strongest potential to send confusing signal to the market, perhaps resembling a taper tantrum version 2.0. The right-hand chart above shows a quick check to identify the pain points based on the current Fed holdings vis-a-vis supply. The vulnerability is concentrated in the long end, especially if this is adjusted for the duration risk (not shown here). The primary reason this may create unwanted responses is that it is not at all well understood. Balance sheet reduction after a massive QE is a completely new thing for both the Fed and the market. The last FOMC minutes (published last week) discussed this issue explicitly for the first time, if I remember correctly. So it is fair to expect this will definitely come up in the March discussion as well. At present FOMC expects re-investing to continue "until normalization of the level of the federal funds rate is well under way". The most important event for the markets from the March FOMC will be any potential change on this view.

Realistically, this can be the trigger that can bring us back to the 4-handle level of long term equilibrium rates we had at the end of 2013. Trump fiscal push blow ups and run-away inflation seems pretty far-fetched at present. The asymmetric positioning here is bear steepening.

Similarly on the equity and risk assets side, this can have the most unexpected and damaging impact than a regular FOMC hike. Possibly more than even an adverse French elections. The National Front candidate Marine Le Pen, even if elected as the President against all odds, will find it hard to muster enough support in the parliament to call for a national referendum to leave the Euro area. And even if the referendum is held and a majority votes to leave, it is not clear that will actually be followed through - going by the outcome of the 2005 referendum.

all data from Federal Reserve and US Treasury.

## Saturday, January 14, 2017

### Markets | Quick Take on Presidential Inauguration

Next week's Presidential Inauguration is a much awaited phenomenon - for general public as well as for the financial markets across the globe. Dow 20K is mostly an arbitrary mark for a market index designed for pre-computer era (and some equally arbitrary Theoretical Dow has already crossed the benchmark). But it appears the entire market is somewhat directionless at present. Since the election, it has made certain assumptions on the policies of the upcoming government and has shown some very strong move across asset classes (see here, here and here). However, we still have very little in terms of concrete policy direction to rely upon. The latest press conference did not quite live up to the expectation of details on policies. A strong guidelines on future policy in the inauguration can provide a new direction to the market one way or the other. And this can kick start the next phase in the market.

The charts below show the market impact of Presidential inauguration since the post-war era (excluding first term of Barack Obama, which was in many ways an outlier). The X-axis is the number of business days from the inauguration day. The chart on the right shows normalized moves of the S&P 500 Index from 3 month before to 3 month after for each inauguration. The chart on the left shows the median line and the uncertainty around it. It appears more often than not, the markets usually rallies in to the inauguration, experiences a slight correction going in to the exact date, and tops out  around 1 or 2 weeks after the actual date before picking up its own course. (Note we have not corrected for the usually positive trends for the markets in general and hence we should not focus much on the trends here but change in the direction of the trends instead.) However we have quite an amount of uncertainties around this. Looking closely at the right hand side chart we see this pattern was more or less followed by around 10 or 11 times out of last 17 cases. (The legends on the right chart are initials of the presidents followed by a digit signifying the term, if required)

Overall positioning-wise, we have nothing extreme in either way. Post elections the leveraged funds (CTAs and hedge funds) and asset managers have increased their long (from CFTC reports). The dealers have become slightly short the markets - but all well within range. On VIX, however the dealers and asset managers remain long against the leveraged players.

This, and trend analysis of the recent intraday movement of S&P 500 suggests the street (i.e. the players who hedge) is mostly long gamma at this point. See the chart below (and see here for interpretation). This means a large sell-off is quite unlikely in the short term. On top of this, we have the asymmetric scenario on the policy clarity. If President-elect Trump does announce clear guidelines on his policies, this will likely confirm the market assumptions (very low chance of a major negative surprise) and market can have the next leg of rally. On the other hands, impact of rhetorics and vagueness will most likely be muted as there is always the next time. This suggests a long positioning for the equities. However the case of dollar is quite different. We have a very strong long dollar positioning from the leveraged players and any disappointment can be felt quite hard in the dollars.

Finally, while you can't miss the obvious market reaction to Trump's win, it is fairly easy to miss - what I think the most dramatic - real economy reaction. The NFIB small business optimism and outlook went over the top following the election, much more than the overall business outlook and optimism measures. The charts shows the standardized measure and the spread.

I think in itself, this is quite significant. Historically, we have only two similar situations when the business indicators were significantly positive and small business optimism outperformed overall measures. Once was during the recovery of early 90s and secondly during the recovery of early 2000s. While we have too few data points to draw any statistical conclusion, in both cases we had sustained economic improvement and overall positive market performance. Of course small business optimism does not necessarily mean it will be realized, nor what is good for small businesses is also necessarily good for overall markets. But perhaps we have too many people bracing for a crash now?

## Wednesday, January 4, 2017

### Systematic Trading: Back-testing Classical Technical Patterns

Following up from my last post on systematic pattern identification in time series, here is the part on identifying and back-testing classical technical analysis patterns. This is based on the classic paper by Lo, Mamaysky and Wang (2000). The major improvement added here lies in defining local extrema in terms of perceptually important points (as opposed to the kernel regression based slope change technique proposed in the paper). In my view, the kernel method can be too noisy and much less robust with real data.

The R package techchart has two functions for identifying classical technical patterns. The function find.tpattern will sweep through the entire time series and find all pattern matches. It takes in the time series as the first parameter (an xts object), a pattern definition to search for, and a couple of tolerance parameters. The first one is used for matching the pattern itself. The second one pip.tolerance is used for finding the highs and the lows (perceptually important points) on which the pattern matching is based. These tolerance numbers are in terms of multiple of standard deviation. Below is an example:

x <- getSymbols("^GSPC", auto.assign = F)
tpattern <- find.tpattern(x["2015"], tolerance = 0.5, pip.tolerance = 1.5)
chart_Series(x["2015"])


add_TA(tpattern$matches[[1]]$data, on=1, col = alpha("yellow",0.4), lwd=5)


Apart from returning the pattern matches, it also returns some descriptions and characteristics of the match. As below:

summary(tpattern)

## ------pattern matched on: 2015-06-23 --------
## type: complete
## move: 1.49 (percentage annualized)
## threshold: 2079.52
## duration: 57 (days)


While this is useful, you already must have spotted the catch. As this function looks at all available data at once to find a pattern, future prices influences past patterns. While this is useful for looking at a time series we need another function for rigorous back-testing. The second function available, find.pattern is to be used for this purpose. This function takes in similar arguments. It returns matched patterns. The match is based on either a completed pattern, or a forming one. A forming pattern is extracted by bumping the last closing price up or down by 1 standard deviation in the next bar and checking if it completes the pattern.

The process of identification of pattern is decoupled from the process of extracting patterns from the data - as proposed in the Lo et al (2000). The pattern defining function in the package is pattern.db.  This follows a similar implementation as here by Systematic Investor Blog, with some added features. The implementation of pattern.db in the package techchart contains some basic patterns - head and shoulder (HS), inverse head and shoulder (IHS), broadening top (BTOP) and broadening bottom (BBOT) - the default in the above functions being HS. However it is trivial to define any pattern (as long as it can be expressed in terms of local highs and lows) and customize this pattern library.

With this framework, it becomes quite straightforward to test and analyze pattern performance, run back-test on pattern based strategies and/ or combine patterns along with other indicators to devise trading strategies at any given frequency.

Here is a straightforward implementation of such a back-test, using the quantstrat package. The strategy is quite straightforward. For a given underlying, we scan data for a head-and-should (or inverse head-and-shoulder) match. Once we find a match, we enter a short (long) position if a short term moving average is below (above) a long term one. Once we enter in to a short (long) position, we hold it for at least 5 days, and exit on or after that if a short term moving average is above (below) a long term one. We apply this strategy across S&P500, DAX, Nikkei 225 and KOSPI. The chart below shows the strategy performance.

The thick transparent purple line is the average performance across these underlying indices.  The performance metrics are as below. It also has (not shown here) a strong positive skew characteristics.

 Performance metrics S&P DAX NKY KOSPI ALL Annualized Return 0.0566 0.0536 0.0678 0.0528 0.0639 Annualized Std Dev 0.1233 0.0982 0.1413 0.1205 0.0692 Annualized Sharpe (Rf=0%) 0.4591 0.546 0.4797 0.4382 0.9234

Not spectacular, but nonetheless interesting. The R code for this back-test is here. Apart from techchart, you would need to install quantmod and quantstrat (and associated packages) to run this. Please note, running this pattern finding algorithm can take considerable time depending on the length of the time series and system characteristics.

## Monday, December 26, 2016

### Macro | 2017 - The Year Ahead

2016 has been the year of surprises - The Brexit, the US Presidential election, the Italian referendum, the massive de-monitization in India, the Nobel prize in literature - you name it. But perhaps the real surprise was how the markets shrugged off each of these supposedly to catastrophic events.

As discussed earlier, this year has been the year of the dollar. The chart below on the left compares volatilities across asset classes in terms of cumulative daily moves greater than 1.5x the daily standard deviation. The dollar has been the clear winner. But also notice the sharp pick up in rates (US 30y here) late this year, reflecting the sell-off after the US election. The chart on the right shows the reversal and continuation of trends across asset classes during the year. The solid performance of risk assets after the sell-off early in the year, in spite of the dollar rally, increase in yields and continued weakness in the Chinese Yuan, has been nothing short of unexpected.

Going in to the next year, however, much of it depends on the performance of the US economy - more specifically the continued strength of the private consumption components and the much expected revival of the investment expenditure. The charts below show what to expect in each of these going in to 2017. A simple linear model points to the strong dependence of the house prices, real rate and labor productivity. The biggest risk to this component of GDP from rising rate is the house price, which has been strong in 2016. The upside risk is of course a much awaited improvement of the productivity (without a runway inflationary pressure).

The investment expenditure, on the other hand, is largely driven by the inflation (NOT real rate, based on this empirical AR(1) model) and expectation about the economy (here represented by the Conference Board leading Index for the US). This part will be crucially determined by the policies of the new administration. The built-up expectation about fiscal spending and its impact on keeping the US growth engine running I think is a bit over-rated. In fact fiscal stimulus in an economy with tight labor market can be more inflationary than expected. The biggest upside may possibly be in the private investments front, which has been running remarkably low for a recovery compared to past episodes. A judicious mix of policy can change this. An improvement in tax regime and infrastructure spending may make US assets attractive not only for domestic, but also for overseas investors. On the other hand, the storm kicked up over trades and foreign policies can be unsettling for long term investments. This is too early to conclude in either way - but this will definitely be the major source of risks, either good or bad. And if this hypothesis is true, this will mean a decoupling of the movement of rates, risk assets and dollars, conditional on no extraordinary increase in inflation or inflation expectation.

The last bit about contained inflation is the base case scenario. Over-all 2016 has seen global inflation picking up in the second half of the year. This to a large extent is driven by the recovery in energy prices and commodities in general. We are still to see any thing on the core inflation that will be any cause of concern. In fact global core inflation is down marginally in the second half in 2016, with notable exception of China. The medium to long term inflation forecast remains stable. The recent rally in inflation break-even markets, while impressive, is coming off from a very low level. We have discussed before the weakening relationship of wage pressure and headline inflation. Nevertheless wage growth is least of any concerns. We do have decent growth in wages in the US, but they are hardly extraordinary compared to pre-crisis periods, and elsewhere globally it remains subdued.

2016 has also been remarkable in at least two other aspects. First, we have seen a definite improvement in global PMI, not only limited to the US anymore. And also the significant contraction in US (negative) current account balance since the post-crisis QE world has now turned a corner and we have a marginal expansion in US current account deficit again. This is all the while with an expansion of Chinese current account surplus along with strong Euro area balance and contraction in current account surplus in petro-dollars economies. If the recent recovery of oil prices sustain, we will see the last bit changing in to positive territories again. That leaves the post-crisis anomaly of the very large Euro area surplus. The global imbalance in trade (and alternatively net savings) is shown the chart below on the left. During the 2000s, the US consistently ran an increasing current account deficit and a shrinking interest rate differential (see the right hand chart below, weighted rates differential to Euro and Japan economies). The dollar more or less followed the suit, weakening during most part of early 2000s. If we assume the QE is more or less done for the ECB and in 2017 we will focus back on tapering in the base case scenario, then it is hard to see that rates differential widening any further. Add to this the massive current account imbalance of the Euro area, and 2017 might as well be the turn-around year for the Euro, instead of the consensus long dollar trade (barring political accidents).

Finally, one of the biggest anticipation in 2017 is the great asset rotation, investors fleeing the bonds universe from the rising rate fear and piling in to equities. Again, there is hardly a strong case for that. Firstly, the demographics in the developed world does not allow a strong return to equities. Secondly, the fear about overseas official accounts dumping treasuries is largely unfounded - primarily most of them have been snapped up by the private sectors, and if we have steady energy prices we will see a lot less selling of treasuries by the petro-dollar economies. China, of course remains vulnerable with a steady outflow, but the outcome is unexpected here. A large dumping of treasuries by China, driven by PBoC's need to supply dollar demand in the domestic economy, will mostly be a risk-averse move and will have the opposite effect on US yields than what a large sell-off might suggest (i.e. a flight-to-safety rally instead of a bonds sell-off). As far as the US households are concerned, they started the great rotation a while back already - as the chart below show.

Overall, we can conclude from above that the major macro drivers for 2017 will be 1) US house prices and US fiscal and trade policies 2) Euro area economic indicators, especially credit impulse 3) The uncertain role of the emerging market economies in face of rising rates and dollars and finally 4) The re-balancing of global excess savings. We should expect a limited rise of rates and inflation (and inflation expectation). Also risk assets face no immediate strong head-winds yet as we expect the upside risk to bond yields and inflation limited. Finally, as we near the end of monetary activism and divergence, going forward we will see a higher de-correlation among asset classes. The major tail risks remain the Chinese economy - where expected risks of accident are low (but with a large impact of course). Among idiosyncratic risks, the UK economy may be vulnerable to a dragged-on negotiation on Brexit, which also potentially may have some mirror impact on the Euro area.

Given this, here we list the top macro trades for the coming year. Note these are the major themes and ways to express them, not a fire-and-forget strategy to be executed on the first trading day of the year.

## Monday, November 28, 2016

### Macro | How Sustainable is the US Dollar Rally

The dollar rally that started since the conclusion of US presidential election shows not much signs of abatement. 2014 was the year of crude oil, when the fantastic sell-off in crude set much of the moods prevailing in the world economy - from equities to rates. In 2015, this slowly turned over to dollar, partly through the surprise CNY depreciation, and later through Fed rate hike expectation. And without any doubt, despite all the noises around the Brexit and Italian referendum votes (early Dec), the dominating factor for risks is again US dollars. The figure below shows a quantitative look at the cross market risk drivers using Minimum Spanning Tree methodology (based on correlation). It shows clearly the dollar is in the center of the cross market driving force. A very similar situation to what we had back in 2013, but more concentrated role for the dollars to set the market sentiments. We already had a not-so-quite riot in rates following the dollar strength post election. The emerging market currencies and equities have taken significant beatings. And top houses are calling for this dollar strength to be one of the top trades in 2017. Naturally it begs the question how much leg is still left in this dollar rally.

To take a long-term look, the dollar rally is by no means extreme. In nominal terms the broad-based trade weighted dollar index is near its historical highs. However, when we compensate for the inflation differentials between the US and its trade partners, the rally is well within the historical range (still 13% off from the 2002 peak) - as the chart below shows. Note the rally in dollar since 2014 has been almost equal for the real and nominal exchange rate - 17% vs 20%.

But while this rally may not be extreme, it may not be sustainable either. A large part of the recent dollar strength has been on the back of expectation of US policy change, specifically a possible fiscal stimulus. The economic argument behind is that a fiscal stimulus, coupled with a budget deficit will increase interest rates and hence the exchange rate. In fact this is what was observed during early 1980s in the US (although it has not much support from observations in other non-US advanced economies). The actual mechanism is far from clear. There are extensive studies on budget deficit reduction and its impact on exchange rates, but reverse studies are rare. Theoretically, the direct impact (of increasing budget deficit) goes through the interest rate and asset return channel above and lead to a higher exchange rate (as demand for higher interest assets goes up among foreigners). On the other hand, increased budget deficit can increase the long term inflation expectation and hence expectation of future dollar depreciation. The second part of the policy is trade - which is basically a tightening pressure on the US current account deficit - if President-elect Trump follows though his promises. Typically for the US the current account in recent history has been driven to a large extent by demand for financials assets from overseas investors. This means a tightening of current account will have to be matched by reduced demand for US financial assets by foreign investors, resulting in a currency depreciation now (and possibly an appreciation later). In fact the post-crisis dollar weakness has resulted in a significant tightening of current account for the US already. A further sustained tightening in general may not be great for either the US or global economy. The other possible factors, i.e. the overall demand (or GDP differential) or real rate differential with major trading partners are relatively straightforward, an increase in both leading to a stronger dollar.

Looking in to the above set of arguments empirically, we run a quick vector auto-regression estimates with real dollar exchange rate, real rate differential, current account (% GDP), budget balance (% GDP) and GDP differential as endogenous variables (differential with GDP-weighted Euro area and Japan data representing rest of the world). The results are as shown in terms of impulse response - i.e. response of dollar real exchange rate for unit positive move in budget balance (FD), current account balance (ca), real rates differential (rates) and GDP differential (GDP). It seems at least for our data (spanning 1995 to 2014, quarterly), Trumps policy of budget deficit (negative fd) and tightening current account (positive ca) has off-setting impact for dollar real exchange rate. In fact there are good chances the current account tightening impact (negative for dollar in near term, positive long term) can overwhelm. An increase interest rates may make US assets attractive among foreign investors, but without matching trades the flows in to those assets will be difficult to sustain. Among other drivers, while inflation in US has been steady, including wage growth, we have seen some early signs of a come back of inflation in the Euro area. The main thing to look out there is the pick up in Euro area credit growth after a stall start of this year.

Given this ambiguous impact of policy, and hopefully a declining need for policy divergence and a head-room for trade-weighted dollars of only ~13% to reach all time high in real terms, it does not look like the dollar rally has much room left. one of the surprise trigger can come from ECB and/or BoJ in December, with QE in Europe still priced in. And the Dec Fed hike - which is almost a certainty now - will act to defuse this rally.

Interestingly, while from the emerging market point of view, the recent dollar rally was kind of risk-off, it was hardly so for Euro. Euro - which has lately became a funding currency like the Yen, sold off steeply. Arguably there was not much positioning to blame either, so this makes it a very interesting move. The Euro area as a whole has accumulated a huge current account surplus in its glut for savings in the post-crisis period. A substantial change in trade relationship with the US may start to unravel that. If you are positioning for the consensus Euro dollar parity, think again. 2017 may see a major reversal in Euro instead dollar.

Note: all data from the St Louis Fed FRED database.