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Portfolio Selection is More of a Belle Art Than Economics or Finance
| name | portfolio-selection-belle-art-economics |
| description | Portfolio Selection is More of a Belle Art Than Economics or Finance |
| metadata | {"arxiv_id":"10.2139/ssrn.6293058","published":"2026-06-06","category":"economics-quantum","topic":"Economics, Investment + Quantum"} |
This methodology was extracted from DOI: 10.2139/ssrn.6293058. It addresses portfolio selection is more of a belle art than economics or finance.
We reveal three points why econometrics and economic theory cannot help to select an optimal portfolio. Markowitz variance describes only a limited market case when all trade volumes are assumed constant. The use of this approximation while predicting portfolio variance is like using constant steps while forecasting random Brownian motion.
Apply this framework when analyzing financial portfolios with quantum computational methods.
Breakeven demonstration of quantum low-density parity-check (qLDPC) codes — first experimental evidence that qLDPC codes can achieve fault-tolerance breakeven on trapped-ion quantum hardware. Critical milestone for scalable quantum error correction. Activation: qLDPC, quantum error correction, breakeven, trapped-ion, fault tolerance, quantum coding, logical qubit, error suppression.
Arrovian impossibility theorem for Automated Market Maker (AMM) design. Proves no aggregation rule for weighted-product AMMs can be simultaneously fair and strategy-proof when n>2 liquidity providers. Key result: fairness forces mean-type aggregation (weighted Aitchison centroid) while strategy-proofness forces median-type; only single-provider dictatorship satisfies both. Obstruction vanishes at n=2. Applies to DeFi protocol design, mechanism design, and prediction markets. (arXiv: 2606.04959)
Architecture-aware quantum state preparation using Bucket Brigade QRAM (BBQRAM) with segment tree for polylogarithmic query time. Covers complex-valued matrix encoding, classical precomputation of rotation angles, and magnitude-then-phase procedures. Enables efficient data loading for quantum finance applications. Based on arXiv:2604.25644. Use when: designing QRAM-based quantum data loaders, optimizing state preparation for quantum finance, loading complex-valued financial data into quantum circuits, implementing efficient amplitude encoding with BBQRAM.
Distributional Portfolio Optimization (DPO) unified framework — organizing Bayesian, robust, chance-constrained, stochastic-allocation, and distributional RL portfolio methods through joint coupling Gamma_theta(dw,dr). Includes Wasserstein-CVaR duality, credible-radius calibration, and distributional Bellman contraction. Activation: distributional portfolio optimization, DPO, Wasserstein DRO, Bayesian portfolio, CVaR, credible radius, distributional reinforcement learning.
Critical analysis methodology for quantum data encoding — identifies how naive amplitude encoding (psi=sqrt(P)) abelianizes the Hilbert space and fails to achieve genuine quantum advantage in QML/finance. Advocates for Dynamical Hamiltonian Encoding (DHE) where data generates non-commutative evolution.
Portfolio Optimization with Mean-Variance-Spectrum Preferences
