Regime dependent determinants of China s sovereign CDS spread

Transcription

1 Regime dependent determinants of China s sovereign CDS spread Zongxin Qian 1 Qian Luo 2 1 School of Finance, Renmin University of China 2 Finance Department, General Research Institute for Nonferrous Metals January 9, 2014

2 Overview 1 Introduction 2 Data and Methodology 3 Main finding

3 Motivation Recently, there is a rising concern about China s sovereign credit risk. China s gov. debt-to-gdp ratio reached 45% and the gov. deficit-to-gdp ratio reached 10% by Contingent debt from financial sector bailout cost is likely to be huge but difficult to precisely estimate. The stock of total social financing has increased by 60% of GDP since Real GDP growth was 10.4% in It then declines to 9.3% in 2011, and then 7.8% in Reinhart and Rogoff (2009) argue that a declining real GDP growth accompanied by increasing leverage in the financial sector usually leads to a financial crisis.

4 Motivation Recently, there is a rising concern about China s sovereign credit risk. China s gov. debt-to-gdp ratio reached 45% and the gov. deficit-to-gdp ratio reached 10% by Contingent debt from financial sector bailout cost is likely to be huge but difficult to precisely estimate. The stock of total social financing has increased by 60% of GDP since Real GDP growth was 10.4% in It then declines to 9.3% in 2011, and then 7.8% in Reinhart and Rogoff (2009) argue that a declining real GDP growth accompanied by increasing leverage in the financial sector usually leads to a financial crisis.

5 Motivation The aforementioned rising concern leads to a surge in the trading of China s sovereign CDS. According to the Financial Times, In 2009, the market for China CDS was only the world s 227th largest CDS market. But By Oct. 2011, it has become the world s 10th largest, bigger than those for Portugal and Bank of America. In this context, it is interesting to know how the market perceives the sovereign credit risk in China and how China s sovereign CDS spread is determined.

6 What have been done? Longstaff et al. (2011) studied the determinants of sovereign CDS spreads of a broad cross-section of countries, including China. They find that global factors matter a lot. Other studies find similar results in European countries (Dieckmann and Plank, 2011; Fontana and Scheicher, 2010).

7 What we add to the literature? First, we introduce potential contagion into the empirical model. Here contagion is defined as Intensification of global factors impacts across different regimes (Forbes and Rigobon, 2002; Dungey et al. 2005). The empirical impacts of the global factors on sovereign CDS spreads found by the previous literature may be spurious due to a reverse causality: as a signal of changes in the sovereign risk, changes in the sovereign CDS spread can affect financial indicators related to economic fundamentals. We investigate whether the impacts remain if we controlling for such a reversed effect.

8 Data and Methodology Data Sample period: 2008/9/ /10/10 All raw data are from the datastream. Methodology Markov regime switching model with endogenous variables(kim, 2009).

9 Main results No evidence for contagion from other sovereign CDS markets (US, EU, Japan), but strong evidence for cross-asset-class contagion. More specifically, we find two regimes with different volatility, a tranquil regime with low volatility and a turbulent regime with high volatility. The impacts of the US treasury bond yield and the US investment-grade corporate bond spread intensified in the turbulent regime. A major driver of the regime switching is the rising jump risk in the global stock market. Domestic and foreign policy reactions to financial crises are also important drivers.

10 Table : Regime switching model results turbulent tranquil constant (0.011) (0.001) CDS(-1) 0.137*** 0.128*** (0.031) (0.028) sdri * (0.746) (0.069) sv *** (1.760) (0.189) gstock *** (0.211) (0.058) gbond *** *** (15.920) (1.529) ivbond ** 1.023*** (5.674) (0.392) hybond (0.138) (0.012) pe ** (2.241) (0.140) tp *** (3.567) (0.502) vp (0.006) (0.002) σ ω p ii

11 Drivers of regime switching pfilter JR