Title :
Predicting the impact of anticipatory action on US stock market - an event study using ANFIS (a neural fuzzy model)
Author :
Cheng, P. ; Mah, ML ; Quek, C.
Author_Institution :
Guangdong Kingold Bus. Manage. Sch., Guangzhou, China
Abstract :
A financial event - an announcement of corporate earnings, fed is expected to announce a change in the interest rate, and others - that is about to occur would have an impact on the stock market in terms of price movements and volume traded. Based on the expected impact of the event on the market, investors would take positions attempting to profit from the expected movements of the market upon the announcement of the event. The objective of this study is to help investors to make a more informed decision under the circumstances by providing three predictions, (1) the action day - the day when the market takes an anticipatory position before a financial event occurs, (2) the change in the indices and (3) the change in volume on the day the event occurs, as compared to the indices and the volume on the action day.
Keywords :
artificial intelligence; forecasting theory; fuzzy neural nets; inference mechanisms; pricing; stock markets; ANFIS; US stock market; anticipatory action; corporate earnings; financial event; neural fuzzy model; price movements; Computational intelligence; Economic indicators; Engineering management; Financial management; Fuzzy systems; IEEE news; Job shop scheduling; Predictive models; Stock markets; Technology management;
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
DOI :
10.1109/CEC.2005.1555029