FLANN Based Forecasting of S&P 500 Index

By Banshidhar Majhi, Hasan Shalabi, M. Fathi. 2005

22 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ajit Kumar Rout
2. Pradipta Kishore Dash
3. Rajashree Dash
4. A. Raj
5. T. Patra
6. S. Chakravarty
7. Puspanjali Mohapatra
8. Omer Berat Sezer

Citations in the corpus

• Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach (2015, background): “But it possesses a higher rate of convergence and lesser computational load than those of a MLP structure (Majhi et al., 2005; Chakravarty and Dash, 2009).”
• Forecasting stock market indices using hybrid network (2009, background): “In such a scenario, intelligent and efficient tools are needed to rise up to the challenge of forecasting stock market.”
• Indian Stock Market Prediction Using Differential Evolutionary Neural Network Model (2012, background): “Financial time series[1][2][3][4] is highly noisy, irregular, random, non-linear, non-seasonal and chaotic in nature.”