A new benchmark called Quant-Arena evaluates large language model agents on the full iterative loop of quantitative trading research — proposing a market hypothesis, implementing it as an executable signal, testing it on historical data, and deciding what to keep. The benchmark's authors note that existing benchmarks score formulas, code, or individual trading decisions, leaving open whether LLMs can carry out the complete research cycle.
Quantitative research is an iterative loop: a researcher proposes a market hypothesis, implements it as an executable signal, tests it on historical data, and decides what to keep. Existing benchmarks score formulas, code, or individual trading decisions, leaving open whether large language models (
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