CrossAlpha is a new open benchmark covering 3600 firms across US, Japan, Taiwan, South Korea and Hong Kong that distills reports into 10-category descriptions, constructs residual cross-market similarity graphs, and tests them on 11 years of aligned return data.
Financial statement analysis with large language models
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
verdicts
UNVERDICTED 6representative citing papers
CSTrader is a multi-agent LLM trading system for CS2 skins that outperforms a -15.62% market index and single-prompt baselines with up to 7.58% returns by using specialized agents for liquidity, sentiment reversal, and risk control.
Frozen LLM checkpoints serve as time capsules of public text and generate outlook scores that forecast equity returns and analyst actions beyond contemporaneous valuations.
QRAFTI is a multi-agent framework using tool-calling and reflection-based planning to emulate quant research tasks like factor replication and signal testing on financial data.
CausalGAN + SAC RL pipeline generates synthetic bond yield data; fine-tuned Qwen2.5-7B LLM produces trading signals, with reported MAE 0.103, 60% profit rate, and LLM score 3.37/5.
A survey synthesizing recent LLM research and assessing its applicability to financial data analysis.
citing papers explorer
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CrossAlpha: An Annual-Report Benchmark for Cross-Market Factor Researc (with LLM Agents)
CrossAlpha is a new open benchmark covering 3600 firms across US, Japan, Taiwan, South Korea and Hong Kong that distills reports into 10-category descriptions, constructs residual cross-market similarity graphs, and tests them on 11 years of aligned return data.
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CSTrader: A Testbed for Language-Grounded Trading in a Community-Driven Virtual Asset Market
CSTrader is a multi-agent LLM trading system for CS2 skins that outperforms a -15.62% market index and single-prompt baselines with up to 7.58% returns by using specialized agents for liquidity, sentiment reversal, and risk control.
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ChatGPT as a Time Capsule: The Limits of Price Discovery
Frozen LLM checkpoints serve as time capsules of public text and generate outlook scores that forecast equity returns and analyst actions beyond contemporaneous valuations.
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QRAFTI: An Agentic Framework for Empirical Research in Quantitative Finance
QRAFTI is a multi-agent framework using tool-calling and reflection-based planning to emulate quant research tasks like factor replication and signal testing on financial data.
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Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation
CausalGAN + SAC RL pipeline generates synthetic bond yield data; fine-tuned Qwen2.5-7B LLM produces trading signals, with reported MAE 0.103, 60% profit rate, and LLM score 3.37/5.
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Bridging Language Models and Financial Analysis
A survey synthesizing recent LLM research and assessing its applicability to financial data analysis.