A novel LSTM-CNN architecture to forecast stock prices

Amol Dhaliwal, Nikolaos Polatidis, Elias Pimenidis

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

Original language	English
Title of host publication	31st International Conference on Artificial Neural Networks
Subtitle of host publication	ICANN
Publisher	Springer
Publication status	Published - 9 Sept 2022
Event	International Conference on Artificial Neural Networks - University of the West of England, Bristol, United Kingdom Duration: 6 Sept 2022 → 9 Sept 2022 https://e-nns.org/icann2022/

Conference	International Conference on Artificial Neural Networks
Abbreviated title	ICANN
Country/Territory	United Kingdom
City	Bristol
Period	6/09/22 → 9/09/22
Internet address	https://e-nns.org/icann2022/

NYP

Cite this

@inproceedings{e2827111da084240bd6179f6da66abb1,

title = "A novel LSTM-CNN architecture to forecast stock prices",

author = "Amol Dhaliwal and Nikolaos Polatidis and Elias Pimenidis",

note = "NYP; International Conference on Artificial Neural Networks, ICANN ; Conference date: 06-09-2022 Through 09-09-2022",

year = "2022",

month = sep,

day = "9",

language = "English",

booktitle = "31st International Conference on Artificial Neural Networks",

publisher = "Springer",

url = "https://e-nns.org/icann2022/",

}

TY - GEN

T1 - A novel LSTM-CNN architecture to forecast stock prices

AU - Dhaliwal, Amol

AU - Polatidis, Nikolaos

AU - Pimenidis, Elias

N1 - NYP

PY - 2022/9/9

Y1 - 2022/9/9

M3 - Conference contribution with ISSN or ISBN

BT - 31st International Conference on Artificial Neural Networks

PB - Springer

T2 - International Conference on Artificial Neural Networks

Y2 - 6 September 2022 through 9 September 2022

ER -