Forecasting the New York stock exchange composite index with past price and interest rate on condition of volume spike
By William Leigh, Ross Hightower, Naval Modani. 2005
76 citations recorded by the source corpus.
Subfields: Finance, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Fengyi Rong
- Linan Yu
- Tian-Shyug Lee
- Ali Mohammad Kimiagari
- Azizollah Memariani
- Chih-Chou Chiu
- Milad Jasemi
- Chi-Jie Lu
In Management Science and Operations Research
- Fengyi Rong
- Sercan Karaoglu
- Ugur Arpaci
- Linan Yu
- Tian-Shyug Lee
- Ali Mohammad Kimiagari
- Azizollah Memariani
- Serkan Ayvaz
Citations in the corpus
- A Deep Learning Approach for Optimization of Systematic Signal Detection in Financial Trading Systems with Big Data (2017, background): “Recently, many studies suggested using Neural Networks in financial trading systems [24]–[27].”
- Financial time series forecasting using independent component analysis and support vector regression (2009, methodology): “The seven technical indicators, determined by the review of domain experts and literatures [40, 63], are selected as forecasting variables for predicting the TAIEX closing cash index.”
- A modern neural network model to do stock market timing on the basis of the ancient investment technique of Japanese Candlestick (2011, background): “…many other researches like Chenoweth, Obradovic, and Stephenlee (1996), Enke and Thawornwong (2005), Kim and Han (2000), Kuo, Li, Cheng, and Ho (2004), Leigh, Hightower, and Modani (2005), Saad, Prokhorov, and Wunsch (1998) that have utilized various types of NNs for TA and stock market prediction.”
- Financial time series forecasting with machine learning techniques: a survey (2010, unknown): “Money Supply 3 [12], [38], [39] Exchange Rates 3 [15], [18], [41] Gold Price 3 [12], [15], [33] Short & Long Term Interest Rates 6 [5], [15], [25], [26], [35], [39]”
- Stock Market Forecasting Research Based on Neural Network and Pattern Matching (2010, methodology): “And Pattern Matching and Recognition can remedy this deficiency.([2]) The prediction using Pattern Matching and Recognition method has a goodfitting because that the forecasting is done based on a long historical data whose change can reflect various influence factors which are included in the predi”