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Wiese, Magnus, Bai, Lianjun, Wood, Ben, Buehler, Hans , year = · 2019 · arXiv 1911.01700

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Generating Financial Time Series by Matching Random Convolutional Features

cs.LG · 2026-06-03 · unverdicted · novelty 6.0

Introduces SOCK (SOft Competing Kernels), a differentiable random convolutional feature map, to train generative models of financial time series via feature matching and shows outperformance over signature and diffusion baselines on small-sample datasets.

Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation

q-fin.CP · 2025-02-24 · unverdicted · novelty 3.0

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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Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation q-fin.CP · 2025-02-24 · unverdicted · none · ref 32
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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