- author = "Chih-Ming Hsu and Ying-Chi Fu and Yu-Chun Liu and Chun-Yi Peng",
- title = "Forecasting the Prices of TAIEX Options by Using Genetic Programming and Support Vector Regression",
- booktitle = "Proceedings of the International MultiConference of Engineers and Computer Scientists, IMECS 2015",
- year = "2015",
- editor = "S. I. Ao and Oscar Castillo and Craig Douglas and David Dagan Feng and Jeong-A Lee",
- volume = "1",
- pages = "57--62",
- address = "Hong Kong",
- month = "18-20 " # mar,
- publisher = "International Association of Engineers",
- keywords = "genetic algorithms, genetic programming, options, support vector regression, SVM, Black-Scholes model",
- volume = "2215",
- isbn13 = "978-988-19253-2-9",
- ISSN = "2078-0958; 2078-0966",
- bibsource = "OAI-PMH server at doaj.org",
- issue = "1",
- language = "English",
- oai = "oai:doaj.org/article:0d2a7c2d6b6843f498c74cdee8ea0d64",
-
URL = "
http://www.iaeng.org/publication/IMECS2015/IMECS2015_pp57-62.pdf",
- size = "6 pages",
- abstract = "The Black-Scholes (B-S) model is the traditional tool for giving a theoretical estimate of the price of European-style options. However, the basic assumptions on the assets and market made in the B-S model are ideal. Furthermore, a lot of factors which might affect the prices of options have not been considered in the B-S model. In this study, the genetic programming (GP) and support vector regression (SVR) are applied to forecast the prices of stock options by using the six basic factors in the B-S model and the other factors, such as the opening and closing prices, highest and lowest prices, trading volume, open interest etc., as the predictors. The performance of GP and SVR forecasting models are also compared to the B-S pricing model. The feasibility and effectiveness of the proposed approach are demonstrated by forecasting the closing prices of Taiwan Stock Exchange Capitalization Weighted Stock Index Options (TAIEX Options) from April 1, 2010 to March 29, 2013.",
-
notes = "http://www.iaeng.org/publication/IMECS2015/
Department of Business Administration, Minghsin University of Science and Technology, Hsinfong, Hsinchu 304, Taiwan",
