Showing 1 - 10 of 9,523
Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role …
Persistent link: https://www.econbiz.de/10010295725
Using daily return data from the four major Central and Eastern European stock markets including fourteen highly liquid stocks and ATX (Vienna), PX (Prague), BUX (Budapest), and WIG20 (Warsaw) market indices, we model the value-at-risk using a set of univariate GARCH-type models. Our results...
Persistent link: https://www.econbiz.de/10010322212
The empirical joint distribution of return-pairs on stock indices displays high tail-dependence in the lower tail and low tail-dependence in the upper tail. The presence of tail-dependence is not compatible with the assumption of (conditional) joint normality. The presence of asymmetric-tail...
Persistent link: https://www.econbiz.de/10010292792
characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …
Persistent link: https://www.econbiz.de/10010274140
of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting … errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are … of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility …
Persistent link: https://www.econbiz.de/10010326350
Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this … stochastic volatility models. The empirical analysis on stock returns on the US market shows that 1% and 5 % Value …
Persistent link: https://www.econbiz.de/10010326487
Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...
Persistent link: https://www.econbiz.de/10010324710
Risk neutral densities (RND) can be used to forecast the price of the underlying basis for the option, or it may be used to price other derivates based on the same sequence. The method adopted in this paper to calculate the RND is to firts estimate daily the diffusion process of the underlying...
Persistent link: https://www.econbiz.de/10010295724
The current subprime crisis has prompted us to look again into the nature of risk at the tail of the distribution. In particular, we investigate the risk contribution of an asset, which has infrequent but huge losses, to a portfolio using two risk measures, namely Value-at-Risk (VaR) and...
Persistent link: https://www.econbiz.de/10010288831
Risk diversification is the basis of insurance and investment. It is thus crucial to study the effects that could limit it. One of them is the existence of systemic risk that affects all of the policies at the same time. We introduce here a probabilistic approach to examine the consequences of...
Persistent link: https://www.econbiz.de/10010421271