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arXiv · 2508.13327

Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention

Sarthak Khanna·Armin Berger·David Berghaus·Tobias Deusser·Lorenz Sparrenberg·Rafet Sifa
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Abstract

We propose STONK (Stock Optimization using News Knowledge), a multimodal framework integrating numerical market indicators with sentiment-enriched news embeddings to improve daily stock-movement prediction. By combining numerical & textual embeddings via feature concatenation and cross-modal attention, our unified pipeline addresses limitations of isolated analyses. Backtesting shows STONK outperforms numeric-only baselines. A comprehensive evaluation of fusion strategies and model configurations offers evidence-based guidance for scalable multimodal financial forecasting. Source code is available on GitHub

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Sarthak Khanna, Armin Berger, David Berghaus, Tobias Deusser, Lorenz Sparrenberg, Rafet Sifa. 2025-08-18. Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention. https://arxiv.org/abs/2508.13327

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