Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...

Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...

Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...

This paper considers the performance of different long-memory dynamic models when forecasting volatility in the stock market using implied volatility as an exogenous variable in the information set. Observed volatility is separated into its continuous and jump components in a framework that...

Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...

We investigate intradaily seasonal patterns on the distribution of high frequency financial returns. Using quantile regression we show the expansions and shrinks of the probability law through the day for three years of 15 minutes sampled stock returns. Returns are more dispersed and less...

The paper studies the statistical properties of the evolution of the USD/HKD exchange rate during the period after the separation of strong and weak side convertibility undertakings, when the rate is confined to a specified corridor. We suggest a discrete time Markov model for the exchange rate...

Most financial markets produce inhomogeneous (i.e. unequally spaced) tick-by-tick data at high frequency. Recently developed time series operators can be used to directly compute statistical variables such as volatility from inhomogeneous data. This is not possible with traditional time series...

During the last three decades various models have been proposed by the literature to predict the risk of bankruptcy and of firm insolvency. In this work there is a survey on the methodologies used by the author for the analysis of default risk, taking into account several approaches suggested by...

The globalisation on financial markets and the development of financial derivatives has increased not only chances but also potential risk within the banking industry. Especially market risk has gained major significance since market price variation of interest rates, stocks or exchange rates...