RaboResearch - Economic Research

Dit artikel is ook beschikbaar in het Nederlands

Latin America: external vulnerabilities and FX pressure valves

Special

Share:

This publication is part of the Latin America after the commodity boom series

Authors: Christian Lawrence and Mauricio Barbosa

  • Latin America currencies have weakened substantially against the US dollar during 2015.
  • While for some countries domestic (political and economic) factors have played their part, it has largely been external forces driving the selling.
  • The prospect of a Fed hike, fallen commodity prices and weaker global demand in general weigh on Latin America currency valuations.
  • Latin Am currencies are most vulnerable to external forces from an interregional comparison, with the Brazilian real standing out.

Currency vulnerability has always been a hot topic of conversation when looking at economies or financial markets, one that economies have faced over many generations and that remains highly pertinent today. Currencies are at the mercy of both domestic and international developments in a zero sum game, with global winners and losers. This has been a particularly important subject of late given the sizeable moves seen across the foreign exchange (FX) market as currency wars intensify and countries attempt to competitively devalue their own currencies at the expense of others. So why has this become such an important theme recently? In a world struggling to grow with a backdrop of low inflation, individual countries need every boost they can get. This is particularly true for those who have already exhausted stimulus from a monetary policy rate perspective.[1] That said, although a weaker currency is generally viewed as desirable in the current environment, it is also true that no central bank wants to see disorderly moves. The more vulnerable a currency is, the more likely we are to see extreme moves. FX vulnerability has been a particularly hot topic of late as markets assess the likely impact of rising US rates on other currencies, particularly those in the emerging market world. Indeed, this topic has continued to dominate headlines since former Fed chairman Bernanke induced the ‘Taper Tantrum’ in 2013.

For Latin America, this is a particularly poignant topic given recent price action. If we look at Latin American currency performance so far this year we see double-digit depreciation against the US dollar (USD) in almost every country. For example, on a spot return basis (not including the returns achieved from the interest rate differential between the two currencies in an FX cross), we see that the Brazilian real (BRL) and Colombian peso (COP) are over 25% weaker while the Chilean (CLP) and Mexican peso (MXN) are nearly 14% weaker. While these moves bode well for exports and for those countries facing low inflationary pressures, the speed of the moves has been uncomfortable for central banks. Indeed, FX volatility has risen markedly of late and some central banks have been employing stability mechanisms aimed at engineering a more orderly depreciation. For example, the Central Bank of Mexico (Banxico) auctions USD 200mn if USD/MXN moves more than 1% away from the previous day’s fix. One thing we should note, however, is that although central banks can try and dampen volatility, they are generally not able to turn a depreciation trend into an appreciation. China might be one exception to that rule given the extreme size of international reserves it holds (USD 3.65trn).

What has triggered the Latin America (and broader emerging markets (EM)) sell-off? For some countries it has been domestic factors, such as BRL, where political woes and a deteriorating macro backdrop have weighed, but largely it has been external forces driving the selling. There is the pending Fed rate hike which is assumed to weigh on EM FX as interest rate differentials to the US narrow, making outflows a risk. Falling commodity prices have weighed heavily, with CLP suffering on the back of falling copper prices and COP on the back of cheaper oil. Of course, falling commodity prices are also a symptom of slowing global growth and weakness in Chinese activity is expected to weigh on EM currencies across the board.

In this chapter we take a more detailed look at FX vulnerability, using two different methodologies to track this across Latin American currencies.

A vulnerability index for Latin American currencies

Our first methodology involves the creation of a simple but clear vulnerability heat map. In this exercise we only look at tradeable currencies within Latin America, giving us a total of
nine currencies to be included in the heat map. We selected seven key variables (in brackets is the short-hand coding used in the tables below) which are all widely touted as affecting currency vulnerability, these being:

  1. Market beta (‘Correlation’), which is another way of saying how closely linked a currency is to broad-based, general market moves. We proxy this by looking at the correlation of each currency to the VIX index (a tradeable index which reflects a market estimate of future volatility of the S&P US equity index – this is known colloquially as the ‘fear’ or ‘risk’ index).
  2. The current-account balance to GDP ratio (‘CA/GDP’).
  3. The budget balance to GDP ratio (‘BB/GDP’), which we use as a proxy for fiscal strength.
  4. Consumer price inflation (‘CPI’), which we use as a measure of the store of value and central bank credibility.
  5. International reserves as a share of GDP (‘IR/GDP’), which we use to show the amount of ‘firepower’ a central bank has to provide support for its currency.
  6. External debt to GDP (‘ED/GDP’), the more external debt a country has the higher its servicing cost when the domestic currency depreciates.
  7. The public-debt-to-GDP ratio (‘PD/GBP’).

The values for each country can be found in table 1 below. By the end of last year it turns out the Brazilian real (BRL) was the most exposed currency in our sample despite its relatively strong standing in IR/GDP and ED/GDP. Moreover, the Mexican peso (MXN) took the second place despite relatively strong macro policies as gleaned from its current-account position and inflation performance. Intuitively, this is what we would expect from experience given the way we see these currencies trade. Readers may well now be asking, why is MXN high beta? MXN has a particularly high beta nature (i.e. highly correlated to broad-based market moves) because it is the most liquid and only fully deliverable and convertible currency that is traded 24 hours a day in Latin America. This means that when there is regional or global stress, many market players use MXN as a proxy for the region as a whole.

Table 1: Currency vulnerability heat map 2014
Table 1: Currency vulnerability heat map 2014Source: Bloomberg, IMF WEO, Rabobank

In order to check the robustness of our methodology, we looked at the average of historical heat maps for the nine countries from 2001 to 2014, giving us 126 observations. To that end, we normalised every variable by subtracting the average of the country sample and dividing by its standard deviation, thus creating z-scores for each currency. Some of the seven variables have inverse implications for vulnerability, by which we mean that a high CA/GDP and a high IR/GDP make a currency less vulnerable while high values for all the other variables mean a more vulnerable currency. Therefore, we simply multiply CA/GDP and IR/GDP by -1 before calculating the z-scores.
By construction, therefore, positive figures in the table reflect that the country is in a worse position against the average. Our variable selection limits the heat map to a yearly frequency. The results for the normalised heat map for 2014 are presented in the annex, table 1.

Figure 1: Vulnerability Rank vs Devaluation Rank
Source: Bloomberg, IMF-WEO, RabobankSource: Rabobank

We then compared the vulnerability rankings and price action for each currency during the same year. Our findings show that – although more factors impinge on price action in any given year – there is a positive relationship between our vulnerability rankings and currency performance, with more vulnerable currencies tending to depreciate more (figure 1).

We have found a positive correlation between the vulnerability rank and the devaluation rank. Intuitively this makes sense, but it is interesting to see these results given that FX markets are seemingly driven by an almost unlimited number of potential factors.

In order to see how Latin America in general fits into the global picture with respect to vulnerability, we also created a Global Vulnerability Framework using a similar methodology as our Latin American heat map (the same except we excluded the correlation to the VIX index, mainly because we are more interested in structural variables). It is important to note that adding new countries/regions to the sample will change all z-scores. As the table below shows, Europe Middle East and Africa (EMEA) is broadly on a par with Asia, while Latin America is seen as more vulnerable. This is far from perfect in way of comparison as there are factors outside of the chosen parameters that make a currency more or less vulnerable in the current environment. For example, given the slowdown in China, Latin America currencies are likely more vulnerable than EMEA currencies as trade ties between China and the Latin America region are far greater than between China and Eastern Europe. It is also the case that the denomination of external debt is important. In EMEA external debt tends to be more likely denominated in EUR, while in Latin America it tends to be USD denominated, making the Latin America region more vulnerable to USD appreciation. But as a rough guide we agree with the results that Asia is likely the least vulnerable region, followed by EMEA and then Latin America.

Table 2: Interregional comparison of currency vulnerability 2014
Table 2: Interregional comparison of currency vulnerability 2014Source: Bloomberg, IMF WEO, Rabobank

Pressure gauge

In order to look at Latin America currencies from another perspective, we created an index to gauge pressure on a sample of currencies. We define the sample using monthly averages of USD/Latin America exchange rates for the same currencies we used in the Vulnerability Index. This second methodology is based on the idea that there are some key (more) high-frequency data in financial markets that drive overall shifts in FX as well and some of these are particularly important for Latin America currencies.

We have chosen five series that help picture investor sentiment towards emerging markets (EM) or developed markets (DM):

  1. The DXY USD index (a measure of USD strength relative to 57.6% EUR, 13.6% JPY, 11.9% GBP, 9.1% CAD, 4.2% SEK and 3.6% CHF) – if the USD is appreciating against these currencies then it is likely to be appreciating against EM currencies as well.
  2. VIX index – higher volatility often results in EM FX depreciation as investors seek safe havens, while carry trades become less attractive.
  3. Yields on 10-year US Treasury bonds – EM currencies often depreciate when US rates rise as the interest rate differential becomes less favourable.
  4. The Commodity Research Bureau (CRB) raw materials index – when commodities prices are falling (so we use the negative of CRB RM, ‘-CRB RM’) EM currencies are expected to come under pressure as many EM countries are commodity exporters.
  5. MSCI EM stock market index – if EM stock markets are falling we would expect EM currencies to find themselves under pressure (again, we use the negative MSCI EM, ‘-MSCI EM’).

We ran a Principal Component Analysis (PCA) framework for the period 2009 to 2014, using normalised versions of each series after applying a smoothing technique.[2] As a result of the PCA, we created an index we call the Latin America FX Pressure Gauge (LFPG). The logic behind this series is that when the LFPG is running above its trend (i.e. LFPG >0), FX Latin America currency is under pressure and is expected to be running above its trend. Then, we applied the same smoothing technique to each currency in order to ensure stationarity in the analysis. We then ran a regression between the normalised smoothened currency against our LFPG series, using the same timeframe (2009-2014).

Our main results are shown in table 3 below.

Table 3. Pressure gauge results for currency vulnerability
Table 3. Pressure gauge results for currency vulnerabilitySource: Rabobank

A look at the table above reveals some very clear results. During the 2009 to 2014 period, BRL reacted more aggressively to shifts in median investor sentiment with a beta equal to 0.56. CLP shows a similar picture with a beta of 0.53. On the other hand, the GTQ shows an insignificant beta (note that a lack of liquidity in GTQ makes conclusions less robust). Argentina has a small beta, but constraints on default situation seem to weigh on investors’ appetite for Argentina for a period much longer than from 2009 to 2014.

Conclusions

In summary, Latin America currencies have suffered heavy losses of late but given the global environment, as well as some specific domestic woes, this theme is unlikely to change in the near term. Of course, periods of correction can be expected but these are likely to offer better levels for re-instating Latin America shorts rather than signalling a reversal of fortunes. Given this view, we look to the findings in our Vulnerability Heat Map and LFPG to help us differentiate between individual Latin America currencies and, as such, we remain bearish on BRL. 

Footnotes

[1] As an example, we believe one of the primary reasons for the ECB announcing its QE plan in the eurozone was to try and weaken EUR in order to import higher inflation and in part to boost exports.

[2] We ran a Hodrick-Prescott filter to each series using different lambda values. First, we chose a small value for lambda (10) in order to clean random shocks from each series. Next, we ran the filter with a high lambda (14,400) in order to extract the trend of the series. We then calculated to proportional deviation between the filtered series and its trend.

Annex

Table 1: Normalized currency vulnerability heat map 2014
Table 1: Normalized currency vulnerability heat map 2014Source: Bloomberg, IMF WEO, Rabobank

This publication is part of the Latin America after the commodity boom series

Colophon

This study is a publication of Economic Research of Rabobank.

The views presented in this publication are based on data from sources we consider to be reliable. Among others, these include Macrobond.

This data has been carefully incorporated into our analyses. Rabobank accepts, however, no liability whatsoever should the data or prognoses presented in this publication contain any errors. The information concerned is of a general nature and is subject to change.

No rights may be derived from the information provided. Past results provide no guarantee for the future. Rabobank and all other providers of information contained in this study and on the websites to which it makes reference accept no liability whatsoever for the content or for information provided on or via the websites.

The use of this publication in whole or in part is permitted only if accompanied by an acknowledgement of the source. The user of the information is responsible for any use of the information. The user is obliged to adhere to changes made by the Rabobank regarding the information’s use. Dutch law applies.

Abbreviations for sources: WEO: World Economic Outlook, EIU: Economist Intelligence Unit, IMF: International Monetary Fund, WEF: World Economic Forum, DOTS: Direction of Trade Statistics

Abbreviations used for countries: AR: Argentina, BZ: Belize, BO: Bolivia, BR: Brazil, CL: Chile, CO: Colombia, CR: Costa Rica, EC: Ecuador, SV: El Salvador, GT: Guatemala, GY: Guyana, HN: Honduras, MX: Mexico, NI: Nicaragua, PA: Panama, PY: Paraguay, PE: Peru, SR: Suriname, UY: Uruguay, VE: Venezuela

Economic Research can also be found on the internet: www.rabobank.com/economics

For more information, please call the Economic Research secretariat on tel. +31 (0)30 – 216 2666 or send an email to economics@rn.rabobank.nl

Editors-in-chief: 
Allard Bruinshoofd, head of International Research, Economic Research

Graphics: Selma Heijnekamp and Reinier Meijer

Production coordinator: Alexandra Dumitru and Christel Frentz

Share:
Author(s)

naar boven