Building blocks for trend-following CTA strategies: scale-free oscillators, volatility-adjusted returns, matrix shrinkage and a position engine
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Updated
Oct 6, 2026 - Python
Building blocks for trend-following CTA strategies: scale-free oscillators, volatility-adjusted returns, matrix shrinkage and a position engine
Code for the paper E. Raninen and E. Ollila, “Coupled regularized sample covariance matrix estimator for multiple classes,” in IEEE Transactions on Signal Processing, vol. 69, pp. 5681–5692, 2021, doi: 10.1109/TSP.2021.3118546.
Nested Cross-Validation for Bayesian Optimized Linear Regularization
Sliding Filter for AWGN Denoising
Where does a subject's own record beat their reference class? Pilot measurement of the IREP premise on 69 seasons of the Lahman Baseball Database; hypotheses frozen for a confirmatory second domain.
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