Financial Time Series

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3 papers in the last four weeks, down 57% on the four weeks before. 0.0% of all new papers.

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Deployment-Side Adaptiveness in Multi-Horizon Volatility Forecasting
Jun 26, 2026Riku Green, Zahraa S. Abdallah, Telmo M Silva FilhoFinancial Forecasting Time Series Forecasting
The University of Bristol Bristol, UK
The Inference-Compute Frontier and a Latency-Efficient Architecture for Limit Order Book Prediction
Jun 24, 2026C. Evans HedgesEfficient Neural Network Inference Financial Time Series
Independent Researcher New York, USA
MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios
Jun 23, 2026Patara Trirat, Jin Myung Kwak, Jay Heo +2Quantitative Finance Financial Forecasting
KAIST
RAVEN: A Regime-Aware Variable-context Expert Network for Financial Time Series Forecasting
Jun 23, 2026Cheng He, Zhenyu Guan, Xijie Liang +6Financial Forecasting Time Series Forecasting
University of Science and Technology of China, China · Shanghai Black Wing Asset Management Co., Ltd., China · College of Sciences, Shanghai University, China +2
Biarchetype analysis for univariate functional data. An application to macroeconomic financial time series
Jun 14, 2026Aleix Alcacer, Rafael Benitez, Vicente J. Bolos +1Financial Time Series
Jaume I University, Castelló 12071, Spain. · University of València, València 46022, Spain.
Machine Learning and the Random Walk Puzzle: Forecasting the CAD/USD Exchange Rate with Expanding Window Evaluation and SHAP Interpretability
Jun 13, 2026Louis Agyekum, Edmund Fosu Agyemang, Obu-Amoah Ampomah +6Time Series Forecasting Forecasting Benchmarks
Department of Economics, University of Ottawa, Ottawa, ON K1N 6N5, Canada · Department of Biostatistics and Data Science, Celia Scott Weatherhead School of Public Health and Tropical Medicine at Tulane University, New Orleans, LA 70112, USA · School of Mathematical and Statistical Sciences, University of Texas Rio Grande Valley, Edinburg, Texas, USA +6
Addressing Market Regime Changes and Heavy-Tailed Returns in Portfolio Optimization via Bayesian VAR and Elliptical Black-Litterman
Jun 8, 2026Daniil Mikriukov, Ruoyu Sun, Angelos Stefanidis +2Quantitative Finance Portfolio Optimization
University of Liverpool · Xi'an Jiaotong-Liverpool University · Department of Computer Science, University of Liverpool, Liverpool, United Kingdom +1
Zero-Copy Semantic Contagion: An In-Memory Streaming Architecture for Evolving Attention Graphs
Jun 4, 2026Kabir MurjaniDynamic Graph Learning Financial Time Series
Department of Electrical Engineering Nirma University Ahmedabad, India
Generating Financial Time Series by Matching Random Convolutional Features
Jun 3, 2026Konrad J. Mueller, Nikita Zozoulenko, Ben Wood +2Time Series Generation Random Feature Methods
Imperial College London · JPMorgan Chase & Co.‡
ReSGA: A Large Tail Risk Model for Learning Value-at-Risk and Expected Shortfall
Jun 3, 2026Yichi Zhang, Ke Zhu, Zhoufan ZhuQuantitative Finance Autoencoders
Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong · Wang Yanan Institute for Studies in Economics, Xiamen University, China · Department of Finance, School of Economics, Xiamen University, China
FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance
Jun 2, 2026Jiaze Sun, Kelvin J. L. Koa, Ruiyang Ni +3Financial Forecasting Time Series Forecasting
National University of Singapore Singapore · National University of Singapore Asian Institute of Digital Finance Singapore · Nanyang Technological University Singapore
ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting
Jun 1, 2026Tingting Wang, Yunyi Zhang, Benyou WangFinancial Time Series Uncertainty Calibration
School of Data Science, The Chinese University of Hong Kong, Shenzhen
Regime-Adaptive Continual Learning for Portfolio Management
May 29, 2026Chaofan Pan, Lingfei Ren, Linbo Xiong +3Continual Learning Portfolio Optimization
Southwestern University of Finance and Economics · Shanxi University
GS-FUSE: Granger-Supervised Gated Fusion and Multi-Granularity Alignment for Event-Driven Financial Forecasting
May 27, 2026Yang Zhang, En Chun, Ziyun Mao +2Financial Forecasting Time Series Forecasting
Southwestern University of Finance and Economics Chengdu, China
High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework
May 26, 2026Giuseppe Masi, Andrea Coletta, Novella BartoliniSynthetic Data Generation Time Series Generation
Sapienza University of Rome, Italy · Banca d’Italia, Italy
Sequential Structure in Intraday Futures Data: LSTM vs Gradient Boosting on MNQ
May 18, 2026Mathias MesfinGradient-Boosted Decision Trees Quantitative Finance
Independent Researcher
Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market
May 17, 2026Mingxuan Yi, Vidal Mehra, Jing Chen +1Change-Point Detection Financial Time Series
School of Engineering Mathematics and Technology, University of Bristol, UK · Propellant Digital B.V., Amsterdam, Netherlands · School of Mathematics, Cardiff University, UK
A Hybrid Gaussian Process Regression Framework for Stable Volatility-Covariance Estimation: Evidence from Global Equity Indices
May 17, 2026Ujjwala VadrevuQuantitative Finance Financial Time Series
Financially Guided Deep Portfolio Optimization
May 16, 2026Rahul Fernandes, Travis DesellQuantitative Finance Portfolio Optimization
Department of Software Engineering Rochester Institute of Technology Rochester, New York, USA
Vector-Quantized Discrete Latent Factors Meet Financial Priors: Dynamic Cross-Sectional Stock Ranking Prediction for Portfolio Construction
May 13, 2026Namhyoung Kim, Jae Wook SongLatent Variable Models Portfolio Optimization
RiskX · Hanyang University
Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis
May 11, 2026Aman Singh, Tokunbo Ogunfunmi, Sanjiv DasQuantitative Finance Time Series Forecasting
Department of Electrical and Computer Engineering, Santa Clara University, USA · School of Business, Santa Clara University, USA
Multivariate Financial Forecasting using the Chronos Time Series Foundation Models
May 8, 2026Sanjiv R Das, Tarang Goyal, Mohini YadavMultivariate Time Series Forecasting Quantitative Finance
Santa Clara University
Learning Time-Inhomogeneous Markov Dynamics in Financial Time Series via Neural Parameterization
May 6, 2026Jan Rovirosa, Jesse SchmolzeMarkov Models Financial Time Series
University of Wisconsin – Madison, Madison, WI, USA
FinSTaR: Towards Financial Reasoning with Time Series Reasoning Models
May 5, 2026Seunghan Lee, Jun Seo, Jaehoon Lee +7Time Series Reasoning CoT Reasoning
LG AI Research · Seoul, South Korea
Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval
May 5, 2026Eshwar Sai Kandimalla, Sravan Chowdary Kankanala, Sumana Bhimineni +2Financial Forecasting Financial Time Series
Department of Computer Science & Engineering, SRM University AP, India
Hindsight Preference Optimization for Financial Time Series Advisory
Apr 27, 2026Yanwei Cui, Guanghui Wang, Xing Zhang +7LLM Alignment Financial Forecasting
1AWS Generative AI Innovation Center · 2HSBC Holdings Plc. HSBC Technology Center China
Visual Chart Representations for Cryptocurrency Regime Prediction: A Systematic Deep Learning Study
Apr 25, 2026Dustin M. HaggettVisual Representation Learning Convolutional Neural Networks
Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken, NJ, USA
Time Series Augmented Generation for Financial Applications
Apr 21, 2026Anton Kolonin, Alexey Glushchenko, Evgeny Bochkov +1LLM Agent Evaluation AI Agent Benchmarks
SingularityNET Foundation
Synthetic data in cryptocurrencies using generative models
Apr 17, 2026André Saimon S. Sousa, Otto Pires, Frank Acasiete +3Synthetic Data Generation Time Series Generation
Universidade SENAI CIMATEC Salvador, Brazil · CoFi, Universidad Jorge Tadeo Lozano Bogotá, Colombia · Universidade do Estado da Bahia - UNEB Salvador, Brazil
A Hybrid Quantum Circuit Born Machine Framework for Financial Volatility Forecasting: Quantum-Assisted Training and Classical Inference
Mar 10, 2026Yixiong ChenQuantitative Finance Quantum Machine Learning

Jun 26, 2026, cs.LGJ/K move · Enter open · S save

Deployment-Side Adaptiveness in Multi-Horizon Volatility Forecasting

Riku Green, Zahraa S. Abdallah, Telmo M Silva Filho

The University of Bristol Bristol, UK

Financial Forecasting Time Series Forecasting Financial Time Series Finance

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In financial forecasting, predictive performance depends not only on which model is trained, but also on how the trained model is deployed. We study this issue in multi-horizon volatility forecasting. Our starting point is that a trained multi-output (MIMO) forecaster does not define a single deployable predictor: by changing the inference-time rollout rule, the same trained model induces a family of forecasts with different accuracy and cost profiles. Across 20 stock-volatility series, three forecast horizons, and architectures ranging from linear models to PatchTST, we find that non-default rollout rules often improve over standard MIMO deployment. However, the best fixed rule varies substantially across architectures and horizons, making any single static replacement unreliable. We therefore evaluate validation-based deployment policies over the induced rule family. Under the primary MSE objective, validation-selected singletons provide a low-cost improvement over default MIMO, while small rule subsets recover much of the benefit of larger ensembles at substantially lower inference cost. We also find that policy rankings are metric-sensitive: MSE-selected policies do not transfer uniformly to QLIKE, a finance-standard volatility loss. These results show that inference-time deployment is a meaningful source of adaptiveness in financial forecasting, and that trained volatility forecasters should be evaluated not only by their architecture, but also by their deployment policy.

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