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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREMWP702

Visualization and Forecasting Stocks using Dash using LSTM and SVR

Stream/Area:

-

Subject:

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Paper ID:

IJSREMWP702

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

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License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GP

G. Prabhas

AK

Ashutosh Kumar

CG

Chetanya Gera

S

Siddhartha

AKS

Ajay Kumar Singh

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Abstract

Investors and analysts require user-friendly tools to instantly analyze stock data in today’s data-driven financial environment. This paper presents a web-driven, Python-based stock analysis tool that combines visual dashboards powered by Dash with machine learning models. In addition to producing informative charts, candlestick plots, and overlays that illustrate market movements, it offers real-time forecasts via Support Vector Regression (SVR). Through data-driven insights and streamlined dashboards, the system’s modular, interactive, and user-friendly architecture supports better investment decisions.

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Cite This Article

G. Prabhas, Ashutosh Kumar, Chetanya Gera, Siddhartha, Ajay Kumar Singh, "Visualization and Forecasting Stocks using Dash using LSTM and SVR," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025.

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Publication Date

10/4/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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