FPILOT optimizes pre-trained RL trading policies at inference time using forecasted price trajectories to improve portfolio allocations and risk-adjusted returns on the DJ30 benchmark.
Foundations and Trends in Optimization , volume =
2 Pith papers cite this work. Polarity classification is still indexing.
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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.
citing papers explorer
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Plan Before You Trade: Inference-Time Optimization for RL Trading Agents
FPILOT optimizes pre-trained RL trading policies at inference time using forecasted price trajectories to improve portfolio allocations and risk-adjusted returns on the DJ30 benchmark.
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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.