Objective
Predicting volatility is of great importance in pricing financial derivatives, selecting portfolios, measuring and managing investment risk more accurately. Since 1980 volatility forecasting is based on day by day datasets. However, the last decade, the use of ultra-high frequency datasets provided more accurate volatility forecasts. In the case where we are interested in evaluating a method’s forecasting ability, a loss function, which takes into consideration the utility of the forecasts is mainly constructed. Although utility functions are measures of accuracy, which are constructed based upon the goals of their particular application, in the majority of the cases, their statistical properties are unknown. The superiority of a utility function against others must be judged by a statistical-theoretical ground and mot just from its empirical motivation. Even though we cannot investigate the statistical properties of a loss function, we are capable to use it for measuring whether two forecasts have statistically equal forecasting accuracy. The majority of the hypotheses tests, which exist in the forecasting literature, compare the ability of two models in producing accurate predictions. However, the simultaneous comparison of the available forecasts provides a more robust comparison of the competing methods of forecasting. The main research objective is the development of a volatility forecasting evaluation framework which would combine the state-of-the-art findings in financial and statistical literature. We seek to combine a) the recent findings in ultra-high frequency modelling, with b) the techniques of simultaneous multiple model comparison and c) the construction of a utility function (or loss function) whose statistical properties would be known.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP7-PEOPLE-IEF-2008
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Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
PO1 2UP Portsmouth
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.