WHAT IS THE ONE FACTOR TO WATCH FOR IN CURRENCIES?

There seem to be so many variables that impact currencies, so much news and data releases to follow, so much to keep track of, that it is easy to get overwhelmed. The more seasoned people talk about Inflation and Central Bank action. But, even these give little information because they do not change on a daily basis. Inflation data, for instance, is available only on a monthly basis and even then with a lag. So, the question is, what are the main factors that impact currency markets? Is there any one main factor to definitely watch while trading currencies?

We should always take a look at the direction of the Spread between the yield on US Treasury Bonds on the one hand and that on bonds of other countries. These Yield Spreads often have a very high correlation with currencies. Here we look at how these Spreads work for the three major currencies, the Euro, Yen and Pound.

FOR EUR-USD

While watching the Euro-Dollar, we should always check the trend in the Yield Spread between the 10Yr German Bunds and 10Yr US T-Bonds (German 10Yr – US 10Yr), plotted on the left hand axis of Chart 1 alongside. This has a strong directional correlation with the Euro-Dollar rate, plotted on the right hand axis.

The Spread has risen from -2.37% (Jan ’17) to -1.72% (6^th Sep ’17) as German yields rose faster than US yields in that period. This was accompanied by a rise in the Euro-Dollar from 1.0405 to 1.2035 on a trend basis. The up-down undulations in the Spread along the way have also been mirrored in the Euro-Dollar rate.

Looking ahead, there is a possibility that the uptrend in the German-US Yield Spread since Jan ’17 may have been broken. The earlier uptrend in the Euro-Dollar since Jan ’17 has also stalled along with the fall in the German-US Yield Spread from -1.72% (6^th Sep ’17) to -1.93% now.  A break below -1.95% on the Spread would confirm the break of the uptrend. If that happens, the Euro would be vulnerable to a break below 1.17.

FOR USD-JPY

Similarly, there is a strong correlation between the 10Yr US T-Bond / 10Yr JGB Yield Spread (US 10Yr – JGB 10Yr, left hand axis) and Dollar-Yen (right hand axis) on Chart 2 alongside.

There was a sharp rise in the Spread from 1.57% (Sep ’16) to 2.51% (Dec ’16) which was accompanied by a rise in Dollar-Yen from 100.40 to 117.89. The

Spread has been ranging sideways between 2.51% and 2.06% thereafter, with a slight downward bias, which has been reflected in the slow appreciation of the Yen from 117.89 (Dec ’16) to 107.84 (6^th Sep ’17). More recently, the Spread has been moving up again to a level of 2.31% now, and Dollar-Yen too has risen to 113.30 along with it.

We have to now see whether the Spread will move up further towards 2.35-2.40% or higher. If so, Dollar-Yen might move up towards 115+.

FOR GBP-USD

Chart 3 plots the Spread between the 10Yr UK Gilt and 10Yr US T-Bond yields (UK-US) on the left hand axis and the Pound-Dollar rate on the right hand axis.

Here too we see the strong correlation between the Spread and the exchange rate, especially since March 2017, except for a brief period in May.

Going forward, the Spread (currently -1.052%) could come down further towards -1.11%. If so, it could pull the Pound (currently 1.3149) down towards 1.30. Thereafter, if the Spread bounces from the trendline Support near 1.11%, the Pound too might be able to find Support near 1.30.

GOING DEEPER

To go deeper, we can try and study the trends in the individual Yield charts – the US T-Bonds, the German Bunds, the Japanese JGBs and the UK Gilts – and try and see where they are each going separately and then to try and pair the individual studies together to arrive at the Spread direction from a different angle. Also, we can study the correlation between the exchange rates and the Spreads at other points in the yield curve, for instance the correlation between the 2Yr Bund-Bond Spread and the Euro-Dollar. These could give us additional insight into the direction of the Yield Spreads and hence into the direction of the currencies as well.

CONCLUSION

Of course, while the correlation between Yield Spreads and currencies is highly reliable most of the times, there are times when, like everything else, it does not work very well. This is to be expected and allowed for. Further, while it is one of the most important factors to watch, it is not the only one. That again is to be understood in the corrective perspective. All said, however, if there is one single factor that should definitely be tracked to figure out currency movements, it is the Yield Spread between countries.

PS:

You can track our ongoing daily forecasts on Yield Spreads and Currencies in our free Morning Briefing report.

Forecasts? Everyone needs one.

 “Nobody can forecast currencies” is an oft heard statement.  This is a popular perception, perpetuated by academic literature of the time as well as statements from people in positions of power and responsibility.

Isn’t it strange, therefore, that everybody in the currency market wants to know where different currencies will go, whether they will strengthen or weaken? The simple fact is that it is a basic human need, even an essential business need, to want to know what the future holds.

Forecasts are needed by everybody, everywhere, not only in the currency markets. Everyone makes forecasts about everything and everyone wants to know the forecast about everything. Without forecasts, the business world and the financial markets would come to a stop. In the financial markets, traders closely track the forecasts made by the central banks, the forecasts or “guidance” made by companies and the forecasts made by the financial institutions on the quarterly results of the companies. Market prices react strongly when these “expectations”,  which are nothing other than forecasts, are missed.

In the business world, the entire annual and quarterly budgeting process is an exercise in forecasting, without which it would be difficult to conduct operations efficiently. While budgeting, the businesses want to have an idea of what the demand scenario is going to be like, what will be the state of the economy, what will be the levels of interest rates and exchange rates in the next quarter, 2 quarters away, 1 year away or even 3 years away, how will commodity prices move? Forecasts are needed for all of these.

Where do we come in? We take on the “impossible” task of trying to forecast the currency markets and then even go further to take care of our Clients’ foreign exchange risks with the goal of reducing volatility and saving money for the Clients.

What makes our forecast valuable for our clients?

Our philosophy and approach to forecasting is what makes our forecast valuable to clients.

Synthesis is the cornerstone of our forecasting philosophy, in essence drawing strength from the “many”.  There are many factors affecting a financial instrument in this intricately connected global financial market.  We check all the factors that we know of closely and select the most pertinent ones. Nothing is unimportant unless it is proved worthless. Every month, we study some 50+ variables very systematically as part of our research process while making our monthly Dollar-Rupee forecasts.

We also synthesize many techniques within Technical Analysis – classical charting, trendlines, moving averages and Elliot Waves – while forecasting. In fact, we also synthesize three supposedly diverse techniques – Fundamental, Technical and Statistical analysis – to try and arrive at a more holistic forecast.

Our endeavour is to try and study the underlying ocean currents, so that we may better understand the waves on the surface.  Most of the times, the underlying forces that drive the markets remain out of sight. To identify those forces and understand their implications is our primary target. In order to be able to do that, we not only study market variables themselves, but we also do a lot of inter-market and ratio analysis, correlation studies and regression studies.

Interestingly, we have also recently started studying the pattern of our own past errors to see if they can give us advance warnings of unanticipated market movements.

In short, we try and leave no stone unturned while trying to arrive at our forecasts.

Trying to minimize surprises

To think of it, why do forecasts tend to go wrong? A gross beginner’s forecasts tend to go wrong simply because he is new to the craft. Later on, a forecaster with 2-5 years of experience might go wrong because he might not have exercised the required due diligence. Even after rising further in experience, a more seasoned forecaster might end up making mistakes if he happens to succumb to his biases. It is to control all these factors that the need for more rigorous analysis starts being felt. And in fact, if these are dealt with there is a good chance that the forecaster may start to achieve reliability in the 55-57% region, maybe even in the 60-62% region.

Therefore, if all these factors are taken care of, a forecast would go wrong only if surprises happen to hit the market. So, to increase reliability levels to 70% and beyond that to 75-80%, the effort has to be to try and be as informed as possible, so as to minimize the chances of being surprised. In effect, this is the same as taking a look at as many factors as you can, in as many ways as you can, so that you leave no stone unturned.

In other words, a wide ranging study of variables and an approach of synthesis (as opposed to reliance on any one or two methods of analysis) is merely an enlightened survival technique.

Going into the next level

Thinking ahead, perhaps the way to pull forecast reliability above the 75-80% threshold would be to actively study the times when we have gone wrong, when we have been surprised, and to study the instances when correlations, that are normally seen to work in the market, happen to fail.

We intend to start working on these. There will surely be hurdles to cross, mistakes to be made, frustrations to be endured. However, at the end of it, hopefully we will be able to move our forecasting reliability to the next higher level.

Inshallah.