Matches in SemOpenAlex for { <https://semopenalex.org/work/W4372324467> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W4372324467 endingPage "726" @default.
- W4372324467 startingPage "717" @default.
- W4372324467 abstract "The stock plays a key role in the economy market. As an individual investor, predicting stock return is always a hot research topic. In recent years, Amazon and Alibaba have become the head of e-commerce and the competition between them is becoming intense. In this paper, linear regression model and LSTM model based on machine learning are introduced and applied to predict the stock return of these two companies. RMSE and R2 are used to choose the number of variables and evaluate those models. This study finds that the simplest linear regression is even better than LSTM model with limited sources. The negative R2 scores of these two methods implies the nonlinearity and instability of stock return. However, predicting stock return is still possible. To investigate more about predicting stock return, more information such as the turnover rate and other non-numerical variables can be included in other models. Different types of LSTM model with different parameter setting can be applied to investigate deeply." @default.
- W4372324467 created "2023-05-07" @default.
- W4372324467 creator A5076315783 @default.
- W4372324467 date "2023-04-27" @default.
- W4372324467 modified "2023-10-18" @default.
- W4372324467 title "Stock Daily Return Prediction of Amazon and Alibaba using Linear Regression and LSTM" @default.
- W4372324467 cites W3170468188 @default.
- W4372324467 cites W4220989417 @default.
- W4372324467 cites W4224441998 @default.
- W4372324467 cites W4308093324 @default.
- W4372324467 cites W4309187428 @default.
- W4372324467 cites W4312778989 @default.
- W4372324467 cites W4312914256 @default.
- W4372324467 doi "https://doi.org/10.54691/bcpbm.v44i.4923" @default.
- W4372324467 hasPublicationYear "2023" @default.
- W4372324467 type Work @default.
- W4372324467 citedByCount "0" @default.
- W4372324467 crossrefType "journal-article" @default.
- W4372324467 hasAuthorship W4372324467A5076315783 @default.
- W4372324467 hasBestOaLocation W43723244671 @default.
- W4372324467 hasConcept C10138342 @default.
- W4372324467 hasConcept C105795698 @default.
- W4372324467 hasConcept C119857082 @default.
- W4372324467 hasConcept C127413603 @default.
- W4372324467 hasConcept C149782125 @default.
- W4372324467 hasConcept C151730666 @default.
- W4372324467 hasConcept C152877465 @default.
- W4372324467 hasConcept C154945302 @default.
- W4372324467 hasConcept C162324750 @default.
- W4372324467 hasConcept C204036174 @default.
- W4372324467 hasConcept C2780299701 @default.
- W4372324467 hasConcept C2780762169 @default.
- W4372324467 hasConcept C33923547 @default.
- W4372324467 hasConcept C41008148 @default.
- W4372324467 hasConcept C48921125 @default.
- W4372324467 hasConcept C78519656 @default.
- W4372324467 hasConcept C83546350 @default.
- W4372324467 hasConcept C86637286 @default.
- W4372324467 hasConcept C86803240 @default.
- W4372324467 hasConceptScore W4372324467C10138342 @default.
- W4372324467 hasConceptScore W4372324467C105795698 @default.
- W4372324467 hasConceptScore W4372324467C119857082 @default.
- W4372324467 hasConceptScore W4372324467C127413603 @default.
- W4372324467 hasConceptScore W4372324467C149782125 @default.
- W4372324467 hasConceptScore W4372324467C151730666 @default.
- W4372324467 hasConceptScore W4372324467C152877465 @default.
- W4372324467 hasConceptScore W4372324467C154945302 @default.
- W4372324467 hasConceptScore W4372324467C162324750 @default.
- W4372324467 hasConceptScore W4372324467C204036174 @default.
- W4372324467 hasConceptScore W4372324467C2780299701 @default.
- W4372324467 hasConceptScore W4372324467C2780762169 @default.
- W4372324467 hasConceptScore W4372324467C33923547 @default.
- W4372324467 hasConceptScore W4372324467C41008148 @default.
- W4372324467 hasConceptScore W4372324467C48921125 @default.
- W4372324467 hasConceptScore W4372324467C78519656 @default.
- W4372324467 hasConceptScore W4372324467C83546350 @default.
- W4372324467 hasConceptScore W4372324467C86637286 @default.
- W4372324467 hasConceptScore W4372324467C86803240 @default.
- W4372324467 hasLocation W43723244671 @default.
- W4372324467 hasOpenAccess W4372324467 @default.
- W4372324467 hasPrimaryLocation W43723244671 @default.
- W4372324467 hasRelatedWork W1963569934 @default.
- W4372324467 hasRelatedWork W2349648642 @default.
- W4372324467 hasRelatedWork W2535222137 @default.
- W4372324467 hasRelatedWork W2991616676 @default.
- W4372324467 hasRelatedWork W2992298911 @default.
- W4372324467 hasRelatedWork W2999452362 @default.
- W4372324467 hasRelatedWork W31220157 @default.
- W4372324467 hasRelatedWork W3215700490 @default.
- W4372324467 hasRelatedWork W4210350336 @default.
- W4372324467 hasRelatedWork W4328094172 @default.
- W4372324467 hasVolume "44" @default.
- W4372324467 isParatext "false" @default.
- W4372324467 isRetracted "false" @default.
- W4372324467 workType "article" @default.