Price cointegration between sovereign CDS and currency option markets in the financial crises of 2007–2013

Impacts of Credit Default Swaps on Volatility of the Exchange Rate in Turkey: The Case of Euro

“…Another study looking at the Eurozone belongs to [18]. Different from other studies, Hui and Fong [18] tries to answer the question of how CDS spreads affect the currency of economies known as safe heavens, such as USA., Japan, Switzerland and Eurozone. In this regard, they analyze the long and short term interaction between CDS spread differentials, currency options and other macroeconomic variables.…”

“…We obtain monthly data belonging to five-year sovereign CDS spreads of the Eurozone calculated as a single premium for the whole area and Turkey from September 2009 to October 2015. Although there are numerous CDS premiums in different maturities, it is common to use CDS with five-year maturities to reflect risk in the related literature [17][18][19][20]. As exchange rate reflects the rate of exchange between two economies' currencies, CDS spreads are thus expressed as the differences between the CDS spreads of the Turkish and Eurozone economies (the CDS spread of the Turkish economy minus the CDS spread of the Eurozone) (hereafter, CDS differential).…”

“…For credit protection, buyers pay a fixed premium called the CDS spread. The CDS market offers the opportunity to reduce credit risk [18] (p. 174). The protection seller would have the opportunity to earn income without having to fund the position.…”

“…The growth of the CDS market makes it a useful tool to understand notions of financial markets. A change in the credit risk of a sovereign borrower reflected in its sovereign CDS spread would be considered as a "signal" of the country's economic-political stability, which is ultimately linked to country specific macroeconomic variables (such as output growth, foreign exchange reserves, budget deficit, real effective exchange rate deviation and foreign direct investment) [18] (p. 174). Moreover, the changes in credit risk premiums of sovereign markets which translate into changes in sovereign CDS spreads do not emanate from changes in the fundamentals of the underlying economies.…”

Advances in financial risk management and economic policy uncertainty: An overview

“…forecasting value-at-risk using block structure multivariate stochastic volatility models (Asai, Caporin and McAleer, 2014), the time-varying causality between spot and futures crude oil prices: a regime switching approach (Balcilar, Gungor and Hammoudeh, 2014), a regimedependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates (Balcilar, Hammoudeh and Fru Asaba, 2014), a practical approach to constructing price-based funding liquidity factors (Bouwman, Buis, PieterseBloem and Tham, 2014), realized range volatility forecasting: dynamic features and predictive variables (Caporin and Velo, 2014), modelling a latent daily tourism financial conditions index (Chang, 2014), bank ownership, financial segments and the measurement of systemic risk: an application of CoVaR (Drakos and Kouretas, 2014), model-free volatility indexes in the financial literature: a review (Gonzalez-Perez, 2014), robust hedging performance and volatility risk in option markets: application to Standard and Poor's 500 and Taiwan index options (Han, Chang, Kuo and Yu, 2014), price cointegration between sovereign CDS and currency option markets in the financial crises of 2007-2013(Hui and Fong, 2014, whether zombie lending should always be prevented (Jaskowski, 2014), preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the global financial crisis (Lean, McAleer and Wong, 2014), managing financial risk in Chinese stock markets: option pricing and modeling under a multivariate threshold autoregression (Li, Ng and Chan, 2014), managing systemic risk in The Netherlands (Liao, Sojli and Tham, 2014), mean-variance portfolio methods for energy policy risk management (Marrero, Puch and Ramos-Real, 2014), on robust properties of the SIML estimation of volatility under micro-market noise and random sampling (Misaki and Kunitomo, 2014), ALRIGHT: Asymmetric LaRge-Scale (I)GARCH with Hetero-Tails (Paolella and Polak, 2014), the economic fundamentals and economic policy uncertainty of Mainland China and their impacts on Taiwan and Hong Kong (Sin, 2014), prediction and simulation using simple models characterized by nonstationarity and seasonality 5 (Swanson and Urbach, 2014), and volatility forecast of stock indexes by model averaging using high frequency data (Wang and Nishiyama, 2014).…”