Assessing the Market Risk on the Government Debt of Kazakhstan and Bulgaria in Conditions of Turbulence

Abstract

The purpose of this publication is to quantify and compare the market risk on the external government debt of Kazakhstan and Bulgaria in the conditions of COVID-19, the emerging energy crisis, and the coup attempt in the first country. In particular, the authors invest the market risk of sovereign bonds issued on global financial markets. Market risk is assessed both as a single issue and at a portfolio level using the Value-at-risk approach. Sixteen samples with historical observations of all issues of Kazakhstan’s and Bulgarian Sovereign Bonds issued on the international financial markets were formed. The duration method was used in the calculation of Delta normal bond VaR and CVaR. It was found that with the same credit rating, similar portfolio duration levels, similar GDP per capita, Debt (% of GDP), and Debt Per Capita, the market risk on their portfolio differed significantly. The comparison of risk levels between the two portfolios was made by six indicators–two indicators measuring linearly the sensitivity of bond prices to changes in market interest rates (Weighted average Macaulay duration and Weighted average modified duration) and four downside indicators (Undiversified VaR, Diversified VaR, Undiversified CVaR, amd Diversified CVaR). The return/risk performance of both portfolios was assessed by the Sharpe ratio in three variants (SR Undiversified VaR, SR Diversified VaR, and SR Diversified CVaR). When evaluating the bond portfolio VaR and CVaR, a practical version of the Duration method was proposed, which allows the use of an unlimited number of assets, taking into account the correlations between yield returns and historical price volatility.

Empirical Testing of Models of Autoregressive Conditional Heteroscedasticity Used for Prediction of the Volatility of Bulgarian Investment Funds

“…The yield is an uncertain quantity due to the presence of the risk of a change in its value in a negative aspect for the investment community. In the 1980s, the financial world created, implemented and patented models for quantifying risk attribution (Em et al 2022). Although autoregressive conditional heteroskedasticity models are more than forty years old, they continue to occupy a leading position in a number of empirical studies in the field of risk management.…”

Financial aspects of socio-economic rejection in Ukraine in conditions of economic turbulence

“…Turbulence can also be understood as a complex trajectory of development of the world (tera-mega economy), national economy (macroeconomics) or an individual firm (microeconomics) in the process of transformations. Turbulence means the extreme degree of instability of the global economic system and the national economy, when there is the greatest probability of reaching the point of bifurcation or breaking (Reshetylo, 2006;Em et al, 2022;Matyushenko et al, 2020;Jarmusevica et al, 2019). In conditions of economic turbulence, the traditional logic and sequence of many economic processes is disrupted.…”