diff --git a/.translate/state/ge_arrow.md.yml b/.translate/state/ge_arrow.md.yml new file mode 100644 index 00000000..9c4e4995 --- /dev/null +++ b/.translate/state/ge_arrow.md.yml @@ -0,0 +1,6 @@ +source-sha: eb30e4fa25c462a5875670e623b2ec01b6f9c727 +synced-at: "2026-07-18" +model: claude-sonnet-5 +mode: RESYNC +section-count: 9 +tool-version: 0.17.0 diff --git a/lectures/ge_arrow.md b/lectures/ge_arrow.md index 68ae5e1d..3592a61a 100644 --- a/lectures/ge_arrow.md +++ b/lectures/ge_arrow.md @@ -10,6 +10,35 @@ kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 +translation: + title: 带有阿罗证券的竞争均衡 + headings: + Introduction: 引言 + The setting: 设定 + The setting::Preferences and endowments: 偏好和禀赋 + Recursive Formulation: 递归表述 + State Variable Degeneracy: 状态变量退化 + Markov Asset Prices: 马尔可夫资产价格 + Markov Asset Prices::Exogenous Pricing Kernel: 外生定价核 + Markov Asset Prices::Multi-Step-Forward Transition Probabilities and Pricing Kernels: 多步前向转移概率和定价核 + Markov Asset Prices::Laws of Iterated Expectations and Iterated Values: 迭代期望法则和迭代值法则 + General Equilibrium: 一般均衡 + General Equilibrium::Inputs: 输入 + General Equilibrium::Outputs: 输出 + General Equilibrium::$Q$ is the Pricing Kernel: $Q$ 是定价核 + General Equilibrium::Values: 数值 + General Equilibrium::Continuation Wealth: 延续财富 + General Equilibrium::Optimal Portfolios: 最优投资组合 + General Equilibrium::Equilibrium Wealth Distribution $\alpha$: 均衡财富分布 $\alpha$ + Finite Horizon: 有限期限 + Finite Horizon::Continuation Wealths: 延续财富 + Python Code: Python代码 + Examples: 示例 + Examples::Example 1: 示例 1 + Examples::Example 2: 示例 2 + Examples::Example 3: 示例 3 + Examples::Example 4: 示例 4 + Examples::Finite Horizon Example: 有限期限示例 --- # 带有阿罗证券的竞争均衡 @@ -854,7 +883,7 @@ class RecurCompetitive: def price_risk_free_bond(self): "给定Q,计算一期无风险债券价格" - PRF = np.sum(self.Q, 0) + PRF = np.sum(self.Q, axis=1) self.PRF = PRF return PRF @@ -862,7 +891,7 @@ class RecurCompetitive: def risk_free_rate(self): "给定Q,计算一期无风险利率R" - R = np.sum(self.Q, 0) + R = np.sum(self.Q, axis=1) R = np.reciprocal(R) self.R = R @@ -1272,4 +1301,3 @@ ex1.ψ, ex1_large.ψ[-1] ex1_large.value_functionss() ex1.J, ex1_large.J[-1] ``` -