Design and implementation of NN5 for Hong Kong stock price forecasting

Philip M. Tsang; Paul Kwok; S. O. Choy; Reggie Kwan; S. C. Ng; Jacky Mak; Jonathan Tsang; Kai Koong; Tak Lam Wong

doi:10.1016/j.engappai.2006.10.002

Design and implementation of NN5 for Hong Kong stock price forecasting

Philip M. Tsang
, Paul Kwok
, S. O. Choy
, Reggie Kwan
, S. C. Ng
, Jacky Mak
, Jonathan Tsang
, Kai Koong
, Tak Lam Wong

Hong Kong Metropolitan University

Research output: Contribution to journal › Article › peer-review

71 Citations (Scopus)

Abstract

A number of published techniques have emerged in the trading community for stock prediction tasks. Among them is neural network (NN). In this paper, the theoretical background of NNs and the backpropagation algorithm is reviewed. Subsequently, an attempt to build a stock buying/selling alert system using a backpropagation NN, NN5, is presented. The system is tested with data from one Hong Kong stock, The Hong Kong and Shanghai Banking Corporation (HSBC) Holdings. The system is shown to achieve an overall hit rate of over 70%. A number of trading strategies are discussed. A best strategy for trading non-volatile stock like HSBC is recommended.

Original language	English
Pages (from-to)	453-461
Number of pages	9
Journal	Engineering Applications of Artificial Intelligence
Volume	20
Issue number	4
DOIs	https://doi.org/10.1016/j.engappai.2006.10.002
Publication status	Published - Jun 2007

Keywords

AI engineering application
NN5
SVM

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10.1016/j.engappai.2006.10.002

Cite this

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title = "Design and implementation of NN5 for Hong Kong stock price forecasting",

abstract = "A number of published techniques have emerged in the trading community for stock prediction tasks. Among them is neural network (NN). In this paper, the theoretical background of NNs and the backpropagation algorithm is reviewed. Subsequently, an attempt to build a stock buying/selling alert system using a backpropagation NN, NN5, is presented. The system is tested with data from one Hong Kong stock, The Hong Kong and Shanghai Banking Corporation (HSBC) Holdings. The system is shown to achieve an overall hit rate of over 70\%. A number of trading strategies are discussed. A best strategy for trading non-volatile stock like HSBC is recommended.",

keywords = "AI engineering application, NN5, SVM",

author = "Tsang, \{Philip M.\} and Paul Kwok and Choy, \{S. O.\} and Reggie Kwan and Ng, \{S. C.\} and Jacky Mak and Jonathan Tsang and Kai Koong and Wong, \{Tak Lam\}",

year = "2007",

month = jun,

doi = "10.1016/j.engappai.2006.10.002",

language = "English",

volume = "20",

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AU - Tsang, Philip M.

AU - Kwok, Paul

AU - Choy, S. O.

AU - Kwan, Reggie

AU - Ng, S. C.

AU - Mak, Jacky

AU - Tsang, Jonathan

AU - Koong, Kai

AU - Wong, Tak Lam

PY - 2007/6

Y1 - 2007/6

N2 - A number of published techniques have emerged in the trading community for stock prediction tasks. Among them is neural network (NN). In this paper, the theoretical background of NNs and the backpropagation algorithm is reviewed. Subsequently, an attempt to build a stock buying/selling alert system using a backpropagation NN, NN5, is presented. The system is tested with data from one Hong Kong stock, The Hong Kong and Shanghai Banking Corporation (HSBC) Holdings. The system is shown to achieve an overall hit rate of over 70%. A number of trading strategies are discussed. A best strategy for trading non-volatile stock like HSBC is recommended.

AB - A number of published techniques have emerged in the trading community for stock prediction tasks. Among them is neural network (NN). In this paper, the theoretical background of NNs and the backpropagation algorithm is reviewed. Subsequently, an attempt to build a stock buying/selling alert system using a backpropagation NN, NN5, is presented. The system is tested with data from one Hong Kong stock, The Hong Kong and Shanghai Banking Corporation (HSBC) Holdings. The system is shown to achieve an overall hit rate of over 70%. A number of trading strategies are discussed. A best strategy for trading non-volatile stock like HSBC is recommended.

KW - AI engineering application

KW - NN5

KW - SVM

UR - https://www.scopus.com/pages/publications/33947153808

U2 - 10.1016/j.engappai.2006.10.002

DO - 10.1016/j.engappai.2006.10.002

M3 - Article

AN - SCOPUS:33947153808

SN - 0952-1976

VL - 20

SP - 453

EP - 461

JO - Engineering Applications of Artificial Intelligence

JF - Engineering Applications of Artificial Intelligence

IS - 4

ER -

Design and implementation of NN5 for Hong Kong stock price forecasting

Abstract

Keywords

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