## Forecasting Financial Time Series with Correlation Matrix Memories for Tactical Asset Allocation (1998)

Citations: | 4 - 2 self |

### BibTeX

@TECHREPORT{Kustrin98forecastingfinancial,

author = {Daniel Kustrin},

title = {Forecasting Financial Time Series with Correlation Matrix Memories for Tactical Asset Allocation},

institution = {},

year = {1998}

}

### OpenURL

### Abstract

High frequency forecasts have always been considered difficult to generate and generation of forecast distributions instead of point forecasts has always been desired by the practitioners in asset allocation and investment management fields. This thesis looks at the problem of high frequency forecast generation by extending the traditional nonlinear dynamics technique by Farmer and Sidorowich and implementing it in a new connectionist architecture based on Correlation Matrix Memories. The architecture employs distribution generation and produces point forecasts as maximum probability points. Distributions are generated from nearest neighbour interpolations by a Bayesian technique. Testing of the architecture's utility has been performed by looking at a selection of representative time series including currency, index and commodity series and their forecast implied efficiency which was compared to standard efficiency estimates. Efficiency was measured with respect to Henriksson--Merton ...