Topology Regressive Distributed Model for Financial Time Series Prediction
Ni He · 2009
Financial time series prediction has long been one of popular research areas for monetary policy makers, market participants and researchers. Inspired from the principle of self-organizing map, the author propose a topological regressive distributed model, which inherits the topology reserving advantage of self-organizing map and the simplicity of the normal autoregressive model. Comparison studies show the proposed method outperforms neural network based local model approaches and traditional autoregressive model on non-stationary financial time series (e.g. exchange rate, stock price).