Distribution forecasting of high frequency time series
نویسندگان
چکیده
The availability of high frequency data sets in finance has allowed the use of very data intensive techniques using large data sets in forecasting. An algorithm requiring fast k-NN type search has been implemented using AURA, a binary neural network based upon Correlation Matrix Memories. This work has also constructed probability distribution forecasts, the volume of data allowing this to be done in a nonparametric manner. In assistance to standard statistical error measures the implementation of simulations has allowed actual measures of profit to be calculated. D 2003 Elsevier B.V. All rights reserved.
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عنوان ژورنال:
- Decision Support Systems
دوره 37 شماره
صفحات -
تاریخ انتشار 2004