Spectral Finance Signal Processing, Fourier Analysis & Quantum Tools for Market Prediction

Unlock the Invisible Patterns That Drive Markets
In Spectral Finance, Hayden Van Der Post delivers a groundbreaking fusion of signal theory, Fourier transforms, and quantum mathematics-redefining how we decode, model, and forecast financial markets.
This isn't just another quant book. It's a technical playbook for those ready to transcend traditional time-series analysis and dive into the hidden dimensions of market structure. Whether you're a quantitative analyst, algo trader, or financial engineer, this guide reveals how to harness spectral decomposition, frequency-domain analysis, and quantum analogs to identify patterns that most traders never see.Inside, you'll explore:Fourier Transforms and their role in detecting hidden cycles and volatility clustersWavelet and Spectral Analysis for filtering financial noise and isolating predictive signalsQuantum Finance Tools, including Hilbert spaces, eigenstates, and probabilistic path modelingSignal Processing Techniques to optimize high-frequency trading systemsPractical Python implementations and visual examples for real-world applicationWith a balance of mathematical rigor and hands-on clarity, this book equips you to build next-generation models that capture market signals buried beneath the surface.