Security Bond Analysis — 保證債分析

债券分析专家——覆盖债券估值、收益率分析、久期/凸性计算、信用利差分析、债券组合管理。适用：固收分析师、债券交易员、组合管理人。

行业痛点 / 行业痛点 痛点 / 痛点 | 影响 | 本Skill解决方案 ---------|------|--------------- 收益率计算复杂 | 多种收益率指标容易混淆 | 标准化收益率计算框架 信用分析耗时 | 发行主体众多，分析量大 | 模板化信用分析框架 利率风险难测 | 久期/凸性概念抽象 | 可视化风险分析 城投债信仰 | 城投刚兑预期与违约现实冲突 | 区域财政分析模型 久期管理难 | 利率变动对组合影响大 | 久期匹配优化工具

触发关键词 / 触发关键词 English Triggers: bond analysis, yield curve, duration, convexity, credit spread, China bonds, fixed income, bond valuation, interest rate risk, credit risk 中文触发词（优先）： 债券分析 / 收益率曲线 / 久期 / 凸性 / 信用利差 / 中国债券 / 固收 / 债券估值 / 利率风险 / 信用风险 / 国债 / 企业债 / 城投债 / 金融债 / 可转债 / 债券回购 / 债券评级 / YTM / 即期收益率 / 到期收益率

核心能力 / 核心能力

• Bond Valuation Engine / 债券估值引擎

import numpy as np
import pandas as pd
class BondAnalyzer:
    """债券分析引擎"""
    @staticmethod
    def calculate_price(face_value: float, coupon_rate: float, ytm: float, years: int, frequency: int = 2) -> float:
        """ 债券定价
        Args:
            face_value: 面值（元）
            coupon_rate: 年票面利率
            ytm: 到期收益率
            years: 剩余期限（年）
            frequency: 付息频率（1=年付，2=半年付）
        """
        n = years  frequency
        r_per_period = ytm / frequency
        c_per_period = (face_value  coupon_rate) / frequency
        pv_coupons = sum([c_per_period / (1 + r_per_period)  t for t in range(1, n + 1)])
        pv_face = face_value / (1 + r_per_period)  n
        return pv_coupons + pv_face
    @staticmethod
    def calculate_ytm(price: float, face_value: float, coupon_rate: float, years: float, frequency: int = 2) -> float:
        """ 计算到期收益率（YTM）- 牛顿迭代法 """
        n = years  frequency
        c = (face_value  coupon_rate) / frequency
        ytm = coupon_rate
        for _ in range(100):
            pv = sum([c / (1 + ytm/frequency)  t for t in range(1, n + 1)]) + face_value / (1 + ytm/frequency)  n
            diff = price - pv
            duration = BondAnalyzer.calculate_duration(price, face_value, coupon_rate, ytm, years, frequency)
            dv = -duration / (1 + ytm/frequency)  diff
            ytm = ytm + diff / dv  0.5
            if abs(diff) < 1e-6:
                break
        return ytm
    @staticmethod
    def calculate_duration(price: float, face_value: float, coupon_rate: float, ytm: float, years: float, frequency: int = 2) -> float:
        """ 计算久期（Macauley Duration） """
        n = int(years  frequency)
        c = (face_value  coupon_rate) / frequency
        r = ytm / frequency
        weighted_time = sum([t  c / (1 + r)  t for t in range(1, n + 1)])
        weighted_time += n  face_value / (1 + r) * n
        return weighted_time / price / frequency
    @staticmethod
    def calculate_convexity(price: float, face_value: float, coupon_rate: float, ytm: float, years: float, frequency: int = 2) -> float:
        """ 计算凸性 """
        n = int(years  frequency)
        c = (face_value  coupon_rate) / frequency
        r = ytm / frequency
        weighted_sq = sum([t  (t + 1)  c / (1 + r)  (t + 2) for t in range(1, n + 1)])
        weighted_sq += n  (n + 1)  face_value / (1 + r)  (n + 2)
        return weighted_sq / price / (frequency  2)
    @staticmethod
    def price_change_estimate(duration: float, convexity: float, rate_change: float) -> dict:
        """ 利率变动对价格的影响估算 """
        duration_effect = -duration  rate_change
        convexity_effect = 0.5  convexity  (rate_change * 2)
        total_effect = duration_effect + convexity_effect
        return {
            "duration_effect": round(duration_effect  100, 4),
            "convexity_effect": round(convexity_effect  100, 4),
            "total_effect": round(total_effect  100, 4),
            "approximate_new_price_pct": round((1 + total_effect) * 100, 4)
        }
Credit Analysis Framework / 信用分析框架
信用债分析模板
一、发债主体概况
项目
内容
公司名称
实际控制人
主体评级
行业分类
主营业务
二、财务分析

python CREDIT_ANALYSIS_RATIOS = { "盈利能力": { "毛利率": ">30%为优质", "净利率": ">15%为优质", "ROE": ">10%为优质" }, "偿债能力": { "资产负债率": "<70%为稳健", ```