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

26 September 2021

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

7 / 7 papers shown

Title
Trading through Earnings Seasons using Self-Supervised Contrastive Representation Learning Zhengxin Joseph Ye Bjoern Schuller 29 0 0 25 Sep 2024
$Uniform $\mathcal{C}^k$ Approximation of $G$-Invariant and Antisymmetric Functions, Embedding Dimensions, and Polynomial Representations$ Uniform $\mathcal{C}^k$ Approximation of $G$ -Invariant and Antisymmetric Functions, Embedding Dimensions, and Polynomial Representations Soumya Ganguly Khoa Tran Rahul Sarkar 44 0 0 02 Mar 2024
From GARCH to Neural Network for Volatility Forecast Pengfei Zhao Haoren Zhu Wilfred Siu Hung Ng Dik Lun Lee AIFin 19 6 0 29 Jan 2024
Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer models Dorien Herremans Kah Wee Low 15 4 0 06 Oct 2022
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions Fernando Moreno-Pino S. Zohren 31 12 0 23 Sep 2022
Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market Tashreef Muhammad Anika Bintee Aftab Mainul Ahsan Maishameem Meherin Muhu Muhammad Ibrahim S. I. Khan Mohammad Shafiul Alam 24 38 0 17 Aug 2022
Graph-Based Learning for Stock Movement Prediction with Textual and Relational Data Qinkai Chen C. Robert AIFin 40 25 0 22 Jul 2021