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Multi-Transformer: A New Neural Network-Based Architecture for
  Forecasting S&P Volatility

Multi-Transformer: A New Neural Network-Based Architecture for Forecasting S&P Volatility

26 September 2021
Eduardo Ramos-Pérez
P. Alonso-González
J. J. Núñez-Velázquez
ArXiv (abs)PDFHTML

Papers citing "Multi-Transformer: A New Neural Network-Based Architecture for Forecasting S&P Volatility"

8 / 8 papers shown
Adaptive Temporal Fusion Transformers for Cryptocurrency Price Prediction
Adaptive Temporal Fusion Transformers for Cryptocurrency Price Prediction
Arash Peik
Mohammad Ali Zare Chahooki
Amin Milani Fard
Mehdi Agha Sarram
AI4TS
56
0
0
06 Sep 2025
Trading through Earnings Seasons using Self-Supervised Contrastive
  Representation Learning
Trading through Earnings Seasons using Self-Supervised Contrastive Representation Learning
Zhengxin Joseph Ye
Bjoern Schuller
173
1
0
25 Sep 2024
Uniform $\mathcal{C}^k$ Approximation of $G$-Invariant and Antisymmetric
  Functions, Embedding Dimensions, and Polynomial Representations
Uniform Ck\mathcal{C}^kCk Approximation of GGG-Invariant and Antisymmetric Functions, Embedding Dimensions, and Polynomial Representations
Soumya Ganguly
Khoa Tran
Rahul Sarkar
266
0
0
02 Mar 2024
From GARCH to Neural Network for Volatility Forecast
From GARCH to Neural Network for Volatility ForecastAAAI Conference on Artificial Intelligence (AAAI), 2024
Pengfei Zhao
Haoren Zhu
Wilfred Siu Hung Ng
Dik Lun Lee
AIFin
215
13
0
29 Jan 2024
Forecasting Bitcoin volatility spikes from whale transactions and
  CryptoQuant data using Synthesizer Transformer models
Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer modelsIEEE Access (IEEE Access), 2022
Dorien Herremans
Kah Wee Low
203
7
0
06 Oct 2022
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated
  Causal Convolutions
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions
Fernando Moreno-Pino
S. Zohren
272
18
0
23 Sep 2022
Transformer-Based Deep Learning Model for Stock Price Prediction: A Case
  Study on Bangladesh Stock Market
Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock MarketInternational Journal of Computational Intelligence and Applications (IJCIA), 2022
Tashreef Muhammad
Anika Bintee Aftab
Mainul Ahsan
Maishameem Meherin Muhu
Muhammad Ibrahim
S. I. Khan
Mohammad Shafiul Alam
160
74
0
17 Aug 2022
Graph-Based Learning for Stock Movement Prediction with Textual and
  Relational Data
Graph-Based Learning for Stock Movement Prediction with Textual and Relational DataInternational Conference on AI in Finance (ICAF), 2021
Qinkai Chen
C. Robert
AIFin
206
26
0
22 Jul 2021
1
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