Papers

• A Cap-Axis Integral Diagnostic of Factor Models (2026)
  Useong Shin
  4.33
• Macro-aware time series forecasting via hierarchical mixed-frequency attention models (2026)
  Daniel Cunha Oliveira and Kieran Wood and Stefan Zohren and Mihai Cucuringu and Andr\'e Fujita
  1.89
• Nansde-net: A neural sde framework for generating time series with memory (2026)
  Hiromu Ozai and Kei Nakagawa
  1.67
• Stock Volatility Prediction using Time Series and Deep Learning Approach (2022)
  Ananda Chatterjee et al.
  1.60
• A Set-Sequence Model for Time Series (2025)
  Elliot L. Epstein et al.
  1.17
• Spurious seasonality detection: a non-parametric test proposal (2018)
  Aurelio F. Bariviera et al.
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• Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data (2019)
  Nikolaos Passalis et al.
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• Dealing with Stochastic Volatility in Time Series Using the R Package stochvol (2019)
  Gregor Kastner
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• Quant GANs: Deep Generation of Financial Time Series (2019)
  Magnus Wiese et al.
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• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019)
  Omer Berat Sezer et al.
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• Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19 (2019)
  Nick James et al.
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• A Stochastic Time Series Model for Predicting Financial Trends using NLP (2021)
  Pratyush Muthukumar et al.
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• Sparsification and Filtering for Spatial-temporal GNN in Multivariate Time-series (2022)
  Yuanrong Wang et al.
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• Modeling Multivariate Positive-Valued Time Series Using R-INLA (2022)
  Chiranjit Dutta et al.
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• Simulating financial time series using attention (2022)
  Weilong Fu et al.
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• Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network (2022)
  Aryan Bhambu et al.
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• Financial Time Series Forecasting using CNN and Transformer (2023)
  Zhen Zeng et al.
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• Generative modeling for time series via Schr{\"o}dinger bridge (2023)
  Mohamed Hamdouche (LPSM) et al.
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• Sig-Splines: universal approximation and convex calibration of time series generative models (2023)
  Magnus Wiese et al.
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• Automated regime classification in multidimensional time series data using sliced Wasserstein k-means clustering (2023)
  Qinmeng Luan and James Hamp
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• Enhancing Price Prediction in Cryptocurrency Using Transformer Neural Network and Technical Indicators (2024)
  Mohammad Ali Labbaf Khaniki et al.
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• Some variation of COBRA in sequential learning setup (2024)
  Aryan Bhambu et al.
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• Optimal Text-Based Time-Series Indices (2024)
  David Ardia and Keven Bluteau
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• A Financial Time Series Denoiser Based on Diffusion Model (2024)
  Zhuohan Wang et al.
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