VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling
Financial observations are continuous, heterogeneous, and noisy, whereas decoder-only next-token models are usually built around discrete symbolic inputs. We introduce Vector-Input Autoregressive Inference for Ordinal-Return Modeling (VAIOM), a decoder-only Transformer for probabilistic next-return modeling on one-hour foreign-exchange bars. VAIOM separates input representation from output likelihood: continuous multivariate financial-event vectors preserve numerical structure at the input, while a categorical distribution over the next volatility-normalized return bucket supports cross-entrop
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- LinkedLinked via arxiv author · 85%Yiming Ma →
“VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling”
- LinkedLinked via arxiv author · 85%Xinyu Chen →
“VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling”