Binary gravity search algorithm and support vector machine for forecasting and trading stock indices

被引：9

作者：

Kang, Haijun ^{[1
]}

Zong, Xiangyu ^{[2
]}

Wang, Jianyong ^{[3
]}

Chen, Haonan ^{[4
]}

机构：

[1] Fuzhou Univ Int Studies & Trade, Sch Finance & Accounting, Fuzhou, Peoples R China

[2] Zhongnan Univ Econ & Law, Sch Finance, Wuhan, Peoples R China

[3] Xiamen Natl Accounting Inst, Xiamen, Peoples R China

[4] Sun Yat Sen Univ, Sch Business, Guangzhou, Peoples R China

来源：

INTERNATIONAL REVIEW OF ECONOMICS & FINANCE | 2023年 / 84卷

关键词：

Finance; Support vector machine; Binary gravity search algorithm; Stock indices; Forecasting; ARTIFICIAL NEURAL-NETWORKS; GENETIC ALGORITHMS; REGRESSION; PREDICTION;

D O I：

10.1016/j.iref.2022.11.009

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

A hybrid Support Vector Machine (SVM) model is proposed and applied to the task of forecasting the daily returns of five popular stock indices in the world, including the S&P500, NKY, CAC, FTSE100 and DAX. The originality of this work is that the Binary Gravity Search Algorithm (BGSA) is utilized, in order to optimize the parameters and inputs of SVM. The results show that the forecasts made by this model are significantly better than the Random Walk (RW), SVM, best predictors and Buy-and-Hold. The average accuracy of BGSA-SVM for five stock indices is 52.87%. In general, this study proves that a profitable trading strategy based on BGSA-SVM prediction can be realized in a real stock market.

引用

页码：507 / 526

页数：20

共 50 条

[31] FORECASTING REPAIR AND MAINTENANCE SERVICES OF MEDICAL DEVICES USING SUPPORT VECTOR MACHINE
Liao, Hao-Yu
Cade, Willie
Behdad, Sara
PROCEEDINGS OF THE ASME 2021 16TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE (MSEC2021), VOL 1, 2021,
[32] Traffic safety forecasting method by particle swarm optimization and support vector machine
Ren Gang
Zhou Zhuping
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (08) : 10420 - 10424
[33] Forecasting performance of support vector machine for the Poyang Lake's water level
Lan, Yingying
WATER SCIENCE AND TECHNOLOGY, 2014, 70 (09) : 1488 - 1495
[34] Support Vector Machine with PSO Algorithm in Short-term Load Forecasting
Gao Rong
Liu Xiaohua
2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 1140 - 1142
[35] Forecasting Repair and Maintenance Services of Medical Devices Using Support Vector Machine
Liao, Hao-yu
Cade, Willie
Behdad, Sara
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2022, 144 (03):
[36] A stock selection algorithm hybridizing grey wolf optimizer and support vector regression
Liu, Meng
Luo, Kaiping
Zhang, Junhuan
Chen, Shengli
EXPERT SYSTEMS WITH APPLICATIONS, 2021, 179
[37] Railway Passenger Volume Forecasting Based on Support Vector Machine and Genetic Algorithm
Chen, Xiaogang
2009 ETP INTERNATIONAL CONFERENCE ON FUTURE COMPUTER AND COMMUNICATION (FCC 2009), 2009, : 282 - 284
[38] Forecasting stock volatility process using improved least square support vector machine approach
Gong, Xiao-Li
Liu, Xi-Hua
Xiong, Xiong
Zhuang, Xin-Tian
SOFT COMPUTING, 2019, 23 (22) : 11867 - 11881
[39] A developed stock price forecasting model using support vector machine combined with metaheuristic algorithms
Armin Mahmoodi
Leila Hashemi
Milad Jasemi
Soroush Mehraban
Jeremy Laliberté
Richard C. Millar
OPSEARCH, 2023, 60 : 59 - 86
[40] Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm
Li, Ling-Ling
Zhao, Xue
Tseng, Ming-Lang
Tan, Raymond R.
JOURNAL OF CLEANER PRODUCTION, 2020, 242 (242)

← 1 2 3 4 5 →