Myanmar’s Sovereign Risk: A Quantitative Approach to Political and Financial Instability 

Introduction

Myanmar’s political and economic instability has made it one of the highest-risk countries in  Asia. Since the 2021 military coup, the country has faced a severe economic downturn,  international sanctions, and a rapidly depreciating currency. These challenges have weakened investor confidence and raised concerns about Myanmar’s ability to sustain its growing debt burden. Given this financial uncertainty, analyzing Myanmar’s economic trajectory using structured, data-driven methods is essential to assess its risk of sovereign default. 

This study applies implied volatility calculations based on sovereign debt valuation, credit default swap (CDS) spreads, and bond yield differentials to measure Myanmar’s financial risk.  By comparing these findings with past financial crises, notably the 1997 Asian Financial  Crisis, this research evaluates whether Myanmar is on a similar path toward economic collapse.  Implied volatility serves as a key indicator of market uncertainty and investor sentiment,  providing insights into how financial markets perceive Myanmar’s risk exposure. 

Assessing Myanmar’s Sovereign Risk Through Financial Models 

To evaluate Myanmar’s financial instability, this study applies three widely used methods for estimating sovereign risk: the CDS-implied default probability model, the bond yield spread model, and historical GDP volatility. 

CDS spreads reflect investor expectations about a country’s likelihood of default. Myanmar’s five-year CDS spread is 9.91 per cent (NYU Stern, 2024), indicating elevated sovereign risk.  Using a standard probability model, the probability of default is estimated using the formula: 

PD = 1 – e^(- (CDS Spread / (1 – R) × T)) 

Where R = 40 per cent (sovereign debt recovery rate) and T = 5 years. Substituting the values: 

PD = 1 – e^(- (0.0991 / (1 – 0.40) × 5)) 

PD = 1 – e^(- (0.0991 / 0.60) × 5) 

PD = 1 – e^(- 0.8259) 

PD = 1 – 0.4380 

PD = 56.2 per cent 

This suggests that financial markets perceive Myanmar as highly vulnerable to sovereign debt distress. 

A second method for assessing sovereign risk involves comparing Myanmar’s bond yields to risk-free U.S. Treasury bonds. Myanmar’s five-year government bond yield is 9.5 per cent, while the U.S. Treasury rate for the same term is 1.5 per cent (Trading Economics, 2024). The difference, an 8 per cent yield spread, suggests significant financial instability. Applying a  standard sovereign asset volatility formula:

σ_V = Yield Spread × √T 

σ_V = 0.08 × √5 

σ_V = 0.08 × 2.236 

σ_V = 17.89 percent 

This suggests that Myanmar’s sovereign asset volatility is comparable to that of financially unstable states before a crisis. 

Macroeconomic stability is another critical factor in assessing sovereign risk. Myanmar’s GDP growth has fluctuated significantly, from 6.5 per cent in 2018 to -18.0 per cent in 2021 and 3.0 per cent in 2022 (World Bank, 2024). The estimated GDP growth volatility is calculated as the  standard deviation of the log differences of GDP growth rates: 

σ_GDP = StdDev(ln (GDP_t+1 / GDP_t)) 

Using historical growth rates, the estimated GDP volatility is 10.1 per cent. While this is significant, it remains lower than the risk levels suggested by CDS and bond markets. This gap indicates that financial market sentiment and risk perception exceed the level of risk reflected in  Myanmar’s macroeconomic fundamentals. 

Comparing Structural and Market-Based Risk Models 

There are two main ways to measure implied volatility in sovereign risk analysis: structural models and market-based models. Bouchet, Clark, and Groslambert (2020) propose a structural approach that estimates financial instability using a logarithmic asset-to-debt ratio. Their method assumes that sovereign volatility is determined by the ratio of a country’s marketable assets to its outstanding debt (Bouchet, Clark, and Groslambert, 2020). 

Bouchet, Clark, and Groslambert (2020) propose a structural model for sovereign risk based on a country’s asset-to-debt ratio. Their equation is: 

σ_V = (1/T) × ln(V_0 / D) 

where σ_V represents implied sovereign volatility, T is the time to maturity of sovereign debt, V₀ refers to total assets, which are often approximated by GDP, and  D is the outstanding sovereign debt. According to this model, a higher asset-to-debt ratio corresponds to lower volatility and reduced sovereign risk, while an increase in debt relative to assets indicates greater financial instability. 

However, this approach differs from how financial markets measure implied volatility.  Traditional financial models rely on real-time market data, such as CDS spreads and bond yields,  to assess sovereign risk. Unlike asset-to-debt ratio models, market-based indicators capture real-

time investor sentiment and forward-looking expectations. This approach is more responsive to sudden economic shocks, such as currency devaluations, capital flight, or political instability. 

Applying These Models to Myanmar’s Risk Assessment 

Market-based models suggest that Myanmar’s risk is significantly higher than structural models alone indicate. The CDS-implied probability of default is 56.2 per cent, showing extreme market concern. The bond yield spread model estimates sovereign asset volatility at 17.89 per cent, signalling crisis-level financial risk. The historical GDP volatility estimate of 10.1 per cent suggests economic instability, but it does not fully explain the heightened risk perceptions reflected in financial markets. 

This analysis confirms that Myanmar’s sovereign risk is more accurately tracked using market-based models, which capture real-time financial stress more effectively than static asset-to-debt ratio models. 

Limitations and Justification of Methodology 

While this study provides a structured quantitative assessment of Myanmar’s sovereign risk,  certain limitations must be considered. Implied volatility models, whether derived from CDS  spreads, bond yields, or structural equations, rely on assumptions that may not fully reflect  Myanmar’s unique economic and political conditions. CDS spreads, for example, are influenced not only by country-specific risks but also by global investor sentiment, liquidity constraints, and broader emerging market volatility. While helpful in assessing creditworthiness, bond yield differentials may be distorted by government intervention, limited market participation, or capital controls, all of which can cause bond pricing to diverge from actual risk levels. 

The parameters used in this study, including a 40 per cent sovereign debt recovery rate and a five-year maturity period, are based on historical trends observed in emerging markets and previous sovereign debt crises. While these benchmarks provide a realistic and widely accepted framework, actual recovery rates can vary depending on political stability, international debt restructuring efforts, and Myanmar’s specific economic conditions. The five-year horizon aligns with standard sovereign risk models, particularly in CDS pricing, but does not fully capture short-term economic shocks or long-term structural weaknesses. 

Conclusion 

Myanmar’s sovereign risk remains severe, as reflected in its high CDS spreads, bond yield differentials, and volatile economic performance. Traditional sovereign risk assessments often rely on credit ratings or governance indicators, but this study highlights the importance of real-time financial data in assessing sovereign default risk. 

By integrating quantitative financial modelling with political risk analysis, this research provides a more dynamic framework for monitoring financial instability in politically fragile states. These findings are particularly relevant for investors, policymakers, and international financial institutions, as Myanmar’s risk trajectory mirrors patterns observed in previous economic crises, including the 1997 Asian Financial Crisis.

References 

Bouchet, M.H., Clark, E., and Groslambert, B. (2020) Country Risk Assessment: A Guide to  Global Investment Strategy. Wiley Finance. 

NYU Stern (2024) ‘Sovereign CDS spreads’. Sovereign Default Risk Data. Available at:  https://pages.stern.nyu.edu/~adamodar. 

Trading Economics (2024) ‘Myanmar Government Bond Yields’. Available at:  https://tradingeconomics.com/myanmar. 

World Bank (2024) World Development Indicators: Myanmar Economic Data. Available at:  https://data.worldbank.org.