Fraction-of-Time Approach in Predicting Value-at-Risk
The aim of this work is to present a new method of Value-at-Risk calculation using the fraction-of-time probability approach used in signal processing (see e.g Leśkow and Napolitano (2001)). This method allows making statistical type inferences based only on a single observation of phenomenon in time. Such setup is very convenient for time series data in financial analysis, when an assumption of having multiple realization of time series is very seldom realized. Another advantage of this method is the possibility of using it without assumptions on the distributions of returns. The aim of the paper is to present the method as well as application to financial data sets.
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