Goldman Sachs: Preferring Long BRL/HUF/MXN/ZAR; EUR/SEK/THB as Funding Currencies

Overview

Published by Goldman Sachs, this report aims to reassess and optimize FX carry trade strategies in a market environment characterized by falling implied volatility and flat USD performance. By constructing different FX carry baskets (long/short, long-only, short-only) and analyzing their one-year performance, combined with analysis of terms of trade, risk sensitivity, and local fundamentals, the report offers specific currency selection recommendations. The core conclusion is that investors should select a few high-yielding currencies for long positions and pair them with specific low-yield currencies for funding, thereby securing high carry while reducing exposure to energy price and risk sentiment volatility.

Core views

Carry Strategy Performance Diverges; Leaner Baskets Outperform Over the past year, FX carry strategies have generally performed well, though with significant internal divergence. Data shows that carry baskets with fewer currencies (e.g., 2-3) outperformed those with more currencies (4-5) in spot returns. Furthermore, long/short strategies slightly outperformed long-only strategies, particularly when considering total return including carry income. This is mainly because, against a backdrop of USD depreciation, the appreciation of traditional funding currencies (such as JPY and CHF) offset some gains, but the long/short structure mechanically provided a higher carry level. Preferred Long Currencies: BRL, HUF, MXN, ZAR Goldman Sachs recommends comprehensively evaluating carry levels, relative changes in terms of trade, and event-driven factors when selecting long currencies. Specific recommendations are as follows: 1. BRL (Brazilian Real): Offers the highest real rates among emerging markets and benefits from improved terms of trade and positive risk Beta. While election asymmetry is less attractive than earlier in the year, market focus has not yet fully concentrated on this issue. 2. HUF (Hungarian Forint): A medium-term favorite, benefiting from major shifts in economic policy after the general election (involving EU funds and potential Euro adoption), offering a more attractive carry-volatility ratio versus the Euro. 3. MXN (Mexican Peso): Provides leveraged exposure to US cyclical performance. Given US growth resilience, its carry returns are expected to stabilize. Banxico is projected to complete its final rate cut. 4. ZAR (South African Rand): A top pick for long positions under scenarios of continued easing. It not only lagged behind other high-Beta currencies previously but also features constructive fiscal and monetary policy prospects; SARB is expected to hike rates by 50 basis points this year. In contrast, Goldman Sachs maintains a cautious view on COP (Colombian Peso) due to pre-election noise before the May 31 presidential vote and central bank decisions influenced by politics. The firm remains bearish on Asian high-yielding currencies (IDR, PHP, INR) as they have limited exposure to global risk sentiment and face negative external balance impacts from high energy prices. Optimizing Funding Currencies: EUR, SEK, THB For a long basket composed of BRL, HUF, MXN, and ZAR, the report analyzes the impact of different funding currencies. USD-funded baskets currently reflect the highest risk appetite and show the strongest negative correlation with oil prices (i.e., falling oil prices benefit the portfolio). To neutralize this exposure to energy prices and risk sentiment, Goldman Sachs recommends using EUR, SEK, and THB as funding currencies. These currencies not only offer higher carry returns (with SEK providing an especially better carry-volatility ratio) but also enhance the portfolio's resilience to energy price shocks. For investors seeking a more defensive expression, CLP (Chilean Peso) funding is also a reasonable choice, particularly for Latin American long positions.

Analysis framework

The report employs a combination of quantitative backtesting and qualitative fundamental analysis. First, it constructs FX carry baskets of varying sizes (2-5 currencies) and directions (long/short, long-only, short-only) to backtest their one-year spot and total returns, identifying the superiority of 'fewer but better' strategies. Second, it incorporates terms of trade and risk Beta as screening dimensions to explain the performance differences between high-carry currencies (mostly energy exporters) and low-carry funding currencies (mostly energy importers) under different macroeconomic environments. Finally, regression analysis calculates the long basket's sensitivity to various funding currencies (specifically Beta against S&P 500, US Treasury real yields, oil prices, and copper prices), quantifying the role of different funding currencies in achieving risk neutrality and return enhancement, ultimately deriving optimized currency pairing recommendations.

Methodology notes

• Industry/Sector Analysis FrameworkOthers

  Construction and Optimization of FX Carry Trades

  A strategy earning interest rate differentials by borrowing low-interest currencies (funding currencies) and buying high-interest currencies (invested currencies). This report not only focuses on the size of the differential but also optimizes the choice of funding currencies through regression analysis to control portfolio sensitivity to oil prices and risk sentiment.

• Industry/Sector Analysis FrameworkOthers

  Terms of Trade and Exchange Rate Linkages

  Refers to the ratio of a country's export prices to its import prices. The report notes that high-carry currencies often correspond to energy-exporting nations (e.g., BRL, COP), where exchange rates benefit from high energy prices; funding currencies are mostly energy-importing nations. Analyzing changes in terms of trade helps assess medium-term exchange rate trends.

• Quantitative/Factor/Portfolio TheoryBeta/alpha analysis

  Currency Pair Risk Asset and Commodity Beta Sensitivity

  Calculates Beta values of currency portfolios against factors such as the S&P 500 and oil prices via regression analysis. For example, USD-funded carry baskets exhibit high positive risk Beta and negative oil Beta, meaning they perform best when stock markets rise and oil prices fall. Selecting different funding currencies can adjust these Beta exposures.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• BRL (Brazilian Real)

  Top long pick, benefiting from high real rates and improving terms of trade

  Strengths

  Highest real rates among emerging markets, beneficiary of favorable terms of trade, positive risk Beta

  Weaknesses

  Election asymmetry weaker than at start of year

  Comparison

  Superior to COP, which faces more pressing election noise

  Risks

  Sudden sharp deterioration in global risk sentiment

• HUF (Hungarian Forint)

  Medium-term preferred long, benefiting from policy shifts

  Strengths

  Major shift in post-election economic policy, improved EU relations, potential Euro adoption

  Weaknesses

  -

  Comparison

  More attractive carry-volatility ratio relative to EUR

  Risks

  Relapse into tension with EU relations

• MXN (Mexican Peso)

  Long position, linked to US cyclical performance

  Strengths

  US growth resilience, strong US asset performance, relatively insulated from energy price shocks

  Weaknesses

  Net energy importer

  Comparison

  More resilient to high energy prices than ZAR

  Risks

  US economic recession

• ZAR (South African Rand)

  Top long pick under de-escalation scenarios

  Strengths

  Constructive domestic fiscal and monetary policy outlook, expected 50bp rate hike

  Weaknesses

  Previously underperformed vs. high-Beta peers

  Comparison

  Outperforms MXN in environments of falling oil prices

  Risks

  Renewed tension in geopolitical situations

• COP (Colombian Peso)

  Cautious / Bearish

  Strengths

  Appreciation over the past year supported spot returns

  Weaknesses

  Eroded undervaluation signals, rising election noise

  Comparison

  Less attractive risk-return profile than BRL

  Risks

  Non-market-friendly results from May 31 election

• INR (Indian Rupee)

  Bearish

  Strengths

  -

  Weaknesses

  Negative terms of trade shock, limited exposure to global risk sentiment

  Comparison

  Part of the group of bearish Asian high-yielding currencies

  Risks

  Further deleveraging leading to policy focused on rebuilding reserves rather than appreciation

Key data

• SARB Rate Hike Forecast50bpGoldman Sachs forecasts the South African Reserve Bank will hike rates by 50 basis points this year, supporting ZAR moves
• COP Election DateMay 31, 2026Colombian presidential election, bringing short-term policy uncertainty
• Banxico Rate Cut ExpectationFinal CutBanxico is expected to complete its final rate cut this week, stabilizing MXN carry returns

Impact & implications

For investors, the current market environment is suitable for repositioning FX carry positions. Solely pursuing high interest rate differentials may entail significant exchange rate volatility risks, particularly reversals driven by energy prices and global risk sentiment. By adopting a 'selective long + optimized funding' strategy, investors can maintain high carry income while significantly reducing portfolio volatility and tail risk. Especially for investors concerned about oil price rebounds or risk asset pullbacks, substituting USD with EUR, SEK, or THB as funding currencies serves as an effective hedging tool.

Risks

• Sudden reversal of global risk sentiment
• Significant fluctuation in energy prices
• Non-market-friendly outcome from Colombia's May 31 election
• Central bank policy paths deviating from expectations

What to watch

• Results of Colombia's May 31 presidential election and subsequent policy developments
• Whether Banxico completes its final rate cut this week
• Pace of SARB rate hikes
• Trends in implied volatility
• Oil price trajectory and its impact on terms of trade