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covariance-estimation

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PortfolioOptimisers.jl

Portfolio optimisation library for Julia. Over 50 risk measures (CVaR, EVaR, RLVaR, drawdown, OWA), hierarchical risk parity, HERC, nested clustered optimisation, risk budgeting, near-optimal centering, four Black-Litterman variants, entropy pooling, factor and high-order priors, denoising, and JuMP-backed convex and non-convex optimization.

  • Updated Oct 25, 2026
  • Julia

Chronos-2 是一个用于时间序列预测的基础模型,基于 Chronos 和 Chronos-Bolt 构建。它提供了显著的能力改进,可以处理早期模型不支持的多种预测场景。支持的场景包括(1)单变量时间序列预测:经典的时间序列预测任务;(2)跨项目学习:利用多个相关时间序列的信息进行预;(3)多变量预测:同时预测多个相关目标变量(3)带协变量的预测:仅过去协变量:在预测时已知的历史协变量(如过去的天气数据) + 已知未来协变量:预测期间已知的协变量(如节假日、计划事件)

  • Updated Jul 13, 2026
  • Jupyter Notebook

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