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on Financial Markets |
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Issue of 2011‒03‒05
four papers chosen by |
| By: | Ansgar Belke; Christian Gokus |
| Abstract: | This study is motivated by the development of credit-related instruments and signals of stock price movements of large banks during the recent financial crisis. What is common to most of the empirical studies in this field is that they concentrate on modeling the conditional mean. However, financial time series exhibit certain stylized features such as volatility clustering. But very few studies dealing with credit default swaps account for the characteristics of the variances. Our aim is to address this issue and to gain insights on the volatility patterns of CDS spreads, bond yield spreads and stock prices. A generalized autoregressive conditional heteroscedasticity (GARCH) model is applied to the data of four large US banks over the period ranging from January 01, 2006, to December 31, 2009. More specifically, a multivariate GARCH approach fits the data very well and also accounts for the dependency structure of the variables under consideration. With the commonly known shortcomings of credit ratings, the demand for market-based indicators has risen as they can help to assess the creditworthiness of debtors more reliably. The obtained findings suggest that volatility takes a significant higher level in times of crisis. This is particularly evident in the variances of stock returns and CDS spread changes. Furthermore, correlations and covariances are time-varying and also increased in absolute values after the outbreak of the crisis, indicating stronger dependency among the examined variables. Specific events which have a huge impact on the financial markets as a whole (e.g. the collapse of Lehman Brothers) are also visible in the (co)variances and correlations as strong movements in the respective series. |
| Keywords: | bond markets, credit default swaps, credit risk, financial crisis, GARCH, stock markets, volatility |
| JEL: | C53 G21 G24 |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwwpp:dp1107&r=fmk |
| By: | Jean-Marie Dufour; René Garcia; Abderrahim Taamouti |
| Abstract: | In this paper, we provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage effect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and implied volatility, and find that implied volatilities are essential for assessing the volatility feedback effect. The leverage hypothesis asserts that return shocks lead to changes in conditional volatility, while the volatility feedback effect theory assumes that return shocks can be caused by changes in conditional volatility through a time-varying risk premium. On observing that a central difference between these alternative explanations lies in the direction of causality, we consider vector autoregressive models of returns and realized volatility and we measure these effects along with the time lags involved through short-run and long-run causality measures proposed in Dufour and Taamouti (2010), as opposed to simple correlations. We analyze 5-minute observations on S&P 500 Index futures contracts, the associated realized volatilities (before and after filtering jumps through the bispectrum) and implied volatilities. Using only returns and realized volatility, we find a strong dynamic leverage effect over the first three days. The volatility feedback effect appears to be negligible at all horizons. By contrast, when implied volatility is considered, a volatility feedback becomes apparent, whereas the leverage effect is almost the same. These results can be explained by the fact that volatility feedback effect works through implied volatility which contains important information on future volatility, through its nonlinear relation with option prices which are themselves forward-looking. In addition, we study the dynamic impact of news on returns and volatility. First, to detect possible dynamic asymmetry, we separate good from bad return news and find a much stronger impact of bad return news (as opposed to good return news) on volatility. Second, we introduce a concept of news based on the difference between implied and realized volatilities (the variance risk premium) and we find that a positive variance risk premium (an anticipated increase in variance) has more impact on returns than a negative variance risk premium. <P> |
| Keywords: | Volatility asymmetry, leverage effect, volatility feedback effect, risk premium, variance risk premium, multi-horizon causality, causality measure, high-frequency data, realized volatility, bipower variation, implied volatility., |
| JEL: | G1 G12 G14 C1 C12 C15 C32 C51 C53 |
| Date: | 2011–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:cir:cirwor:2011s-27&r=fmk |
| By: | Matt P. Dziubinski (Aarhus University and CREATES) |
| Abstract: | We introduce the Simplified Component GARCH (SC-GARCH) option pricing model, show and discuss sufficient conditions for non-negativity of the conditional variance, apply it to low-frequency and high-frequency financial data, and consider the option valuation, comparing the model performance with similar models from the literature. Two volatility components in our model allow us to model time structure of volatility. |
| Keywords: | Stochastic volatility, volatility components, GARCH, option pricing. |
| JEL: | G12 C32 |
| Date: | 2011–05–28 |
| URL: | http://d.repec.org/n?u=RePEc:aah:create:2011-09&r=fmk |
| By: | Kay Pilz; Erik Schlogl (School of Finance and Economics, University of Technology, Sydney) |
| Abstract: | This paper presents a methodf or calibrating a multi currency lognormal LIBOR Market Model to market data of at–the–money caps, swaptions and FX options. By exploiting the fact that multivariate normal distributions are invariant under orthonormal transformations, the calibration problem is decomposed into manageable stages, while maintaining the ability to achieve realistic correlation structures between all modelled market variables. |
| Keywords: | currency options; LIBOR market model; exchange rate risk; interest rate risk |
| Date: | 2010–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:uts:rpaper:286&r=fmk |