TY  - CONF
AV  - none
SP  - 390
PB  - Institute of Electrical and Electronics Engineers Inc.
EP  - 395
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112429036&doi=10.1109%2fICCOINS49721.2021.9497157&partnerID=40&md5=b4b84f9716a29cf42b23d92f7c1023c5
N1  - cited By 0; Conference of 6th International Conference on Computer and Information Sciences, ICCOINS 2021 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:170762
A1  - Hilmi, M.Z.B.
A1  - Mahmood, A.K.
A1  - Moin, A.
A1  - Anwar, T.
A1  - Sutrisno, S.
ID  - scholars14704
Y1  - 2021///
TI  - Share Buyback Prediction using LSTM on Malaysian Stock Market
KW  - Commerce; Financial markets; Forecasting; Long short-term memory; Predictive analytics
KW  -  Earning per shares; Malaysians; Open market; Outstanding shares; Prediction algorithms; Prediction model; Stock indicators; Stock market prices
KW  -  Electronic trading
SN  - 9781728171517
N2  - Share buyback is a strategy for companies to repurchase their outstanding shares to reduce the number of shares from the open markets. With buyback, it indirectly increases the shares proportion and earning per shares (EPS) of a company. The aim of this study is to investigate the trend of share buyback strategy, and to design a simple prediction model for stock market price movement before initiating any buyback action. This study finds the use of Long Short-Term Memory (LSTM) as prediction algorithm has demonstrated that stock market price movement can be predicted using associated stock indicators, namely MACD and RSI which have an impact to the stock market price movement. The study also finds that the Open parameter based on the MAE, MSE and RMSE have been found to be the lowest value as compared to High , Low and Close parameters. © 2021 IEEE.
ER  -