GARCH 波动率模型
GARCH 波动率模型：用 GARCH 族模型进行波动率建模与预测，支持夏普比率统计推断和 SPA 模型比较测试，应用于全球市场风险管理。 含 15 条反模式约束。
晶体简介
Constraints
Evidence Quality
Medium confidence — review before critical use
77 条不可违反的约束
WHENWhen implementing data input for ARCH model initialization
ACTIONvalidate that input data contains only finite values using np.all(np.isfinite) before any numeric computation
CONSEQUENCEOptimizers and recursive variance computations will produce NaN/inf results, causing the entire model estimation to fail silently with meaningless outputs
WHENWhen implementing data input for ARCH model initialization
ACTIONconvert each input data to contiguous float64 arrays using np.ascontiguousarray before storing in self._y
CONSEQUENCENon-contiguous arrays or non-float64 types will cause buffer errors in Cython/Numba optimized recursive computations, leading to segmentation faults or incorrect variance calculations
WHENWhen initializing ARCH models with data
ACTIONpass None as input data without raising RuntimeError when attempting to fit the model
CONSEQUENCEFitting attempt with no data will cause cryptic errors in scipy optimize or segfault in Cython recursions
常见问题
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v0.1.0: 首次发布到 Doramagic.ai。基于 tangweigang-jpg/doramagic-skills 的自动化 batch-v1 元数据 + 自动生成 FAQ。