Presents SE-WaveNet with weight-tied dilated convolutions plus wavelet and spectral components that reproduces empirical scaling collapse on financial returns while using L times fewer convolutional parameters.
Empirical properties of asset returns: stylized facts and statistical issues,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
AEGIS is a hierarchical optimization framework that uses volatility-adjusted momentum and minimax correlation to generate asymmetric alpha with reduced drawdowns in backtests.
citing papers explorer
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Scale-Equivariant Generative Forecasting: Weight-Tied Dilated Convolutions, Wavelet Scattering Inputs, and Spectral-Consistency Training for Self-Similar Time Series
Presents SE-WaveNet with weight-tied dilated convolutions plus wavelet and spectral components that reproduces empirical scaling collapse on financial returns while using L times fewer convolutional parameters.
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Taming the Black Swan: A Momentum-Gated Hierarchical Optimisation Framework for Asymmetric Alpha Generation
AEGIS is a hierarchical optimization framework that uses volatility-adjusted momentum and minimax correlation to generate asymmetric alpha with reduced drawdowns in backtests.