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We develop a large-scale deep learning model to predict price movements from limit order book (LOB) data of cash equities. The architecture utilizes convolution
We develop a large-scale deep learning model to predict price movements from limit order book (LOB) data of cash equities. The architecture utilizes convolution
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Agent Trading Arena probes numerical understanding of LLM-based trading agents in a zero-sum market simulation
InvestorBench evaluates LLM-based agents on financial decision-making tasks across multiple asset classes and markets
FinMTEB is a finance-specific massive text embedding benchmark with 64 datasets across seven financial NLP task types
