A motif-based decomposition of quantile risk networks shows that local triadic topology and orbit-position diversity carry portfolio-relevant information missed by aggregate connectedness, with motif-based portfolios outperforming benchmarks and positional diversity marking tail transmitters.
Portfolio selection
6 Pith papers cite this work. Polarity classification is still indexing.
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A penalty-free pipeline samples an objective-only QUBO on D-Wave hardware and enforces cardinality classically, cutting chain-break fractions from 71-92% to at most 0.04% across tested equity and betting instances.
Develops a CVaR continuous-time model combining put options and trend following for tail risk, deriving an HJB equation and illustrating hybrid CVaR reductions via stylized Monte Carlo.
D-Wave hybrid portfolio optimization is dominated by classical decomposition, with QPU access at 0.68% of wall-clock time and classical TabuSampler matching objective values.
Characterizes Nash equilibria for MMV portfolio problems via FBSDEs and extended HJBs, with MMV equilibria investing more than MV ones and gap narrowing over time.
Asymmetry PRISM-CPU achieves 4.5x-24.1x speedups over reference solvers on N=100-2000 problems and GPU completes all 500 accounts in 109.5s where OSQP completes 4.
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Tail Risk Management with Puts and Trend Following: A CVaR Framework for Crashes and Drawdowns
Develops a CVaR continuous-time model combining put options and trend following for tail risk, deriving an HJB equation and illustrating hybrid CVaR reductions via stylized Monte Carlo.