It has been frequently discussed, that returns are not normally distributed. Liquidity costs, measuring market liquidity, are similarly non-normally distributed displaying fat tails and skewness. Liquidity risk models either ignore this fact or use the historical distribution to empirically...

Despite their importance in modern electronic trading, virtually no systematic empirical evidence on the market impact of incoming orders is existing. We quantify the short-run and long-run price effect of posting a limit order by proposing a high-frequency cointegrated VAR model for ask and bid...

We examine intra-day market reactions to news in stock-specific sentiment disclosures. Using pre-processed data from an automated news analytics tool based on linguistic pattern recognition we extract information on the relevance as well as the direction of company-specific news....

In the restructured electric power utility industry, reducing the risk exposure of profit to the highly volatile electricity wholesale price and the fluctuating demand of end users is essential to the financial success of load-serving entities (LSEs). Demand response (DR) programs have been...

With hedgefunds, managers develop risk management models that mainly aim to play on the effect of de correlation.In order to achieve this goal,companies use the correlation coefficient as an indicator for measuring dependencies existing between(i)the various hedge funds strategies and share...

To match the stylized facts of high frequency financial time series precisely and parsimoniously, this paper presents a finite mixture of conditional exponential power distributions where each component exhibits asymmetric conditional heteroskedasticity. We provide weak stationarity conditions...