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风险管理插件 - 市场风险、信用风险、流动性风险管理
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Baseado na classificação ocupacional SOC
FICC 经营分析报告生成系统 - 基于 Anthropic financial-services-plugins 架构，支持 18 个业务团队的多维度经营分析
FICC经营分析报告主协调器，负责工作流程编排、阶段路由与状态管理，协调各子技能完成报告生成全流程
客户解决方案插件 - 套保方案设计、结构性产品定价、客户风险分析
大宗商品业务插件 - 贵金属、能源、基本金属分析与估值
FICC 核心插件 - 数据连接、基础建模、统一接口
固收业务插件 - 利率债、信用债、衍生品分析与估值
| name | risk-management |
| description | 风险管理插件 - 市场风险、信用风险、流动性风险管理 |
| dependency | {"python":["pandas>=2.0.0","numpy>=1.24.0"]} |
风险管理插件是FICC核心插件层的重要组成部分，提供全面的风险管理能力，包括市场风险、信用风险、流动性风险的计量、监控和报告。
class MarketRiskManager:
"""市场风险管理器"""
def calculate_var(self, portfolio, method="historical", confidence=0.99):
"""
计算VaR
Methods: historical, parametric, monte_carlo
"""
pass
def calculate_cvar(self, portfolio, confidence=0.99):
"""计算CVaR/Expected Shortfall"""
pass
def calculate_sensitivities(self, portfolio):
"""
计算敏感度指标
包括：PV01, CS01, Delta, Gamma, Vega等
"""
pass
def perform_stress_test(self, portfolio, scenarios):
"""执行压力测试"""
pass
def monitor_risk_limits(self, portfolio, limits):
"""监控风险限额"""
pass
class CreditRiskManager:
"""信用风险管理器"""
def calculate_exposure(self, counterparty, trades):
"""
计算敞口
包括：当前敞口、潜在未来敞口(PFE)
"""
pass
def calculate_cva(self, portfolio, counterparty_data):
"""
计算信用估值调整(CVA)
"""
pass
def calculate_pfe(self, portfolio, confidence=0.99, horizon=252):
"""
计算潜在未来敞口(PFE)
"""
pass
def assess_counterparty_risk(self, counterparty_id):
"""评估交易对手风险"""
pass
def monitor_credit_limits(self, exposures, limits):
"""监控信用限额"""
pass
class LiquidityRiskManager:
"""流动性风险管理器"""
def calculate_lcr(self, assets, liabilities):
"""
计算流动性覆盖率(LCR)
LCR = High Quality Liquid Assets / Net Cash Outflows over 30 days
"""
pass
def calculate_nsf(self, assets, liabilities):
"""
计算净稳定资金比率(NSFR)
NSFR = Available Stable Funding / Required Stable Funding
"""
pass
def assess_funding_liquidity(self, portfolio):
"""评估融资流动性"""
pass
def assess_market_liquidity(self, positions):
"""评估市场流动性"""
pass
def stress_liquidity(self, portfolio, stress_scenarios):
"""流动性压力测试"""
pass
class RiskReporting:
"""风险报告"""
def generate_daily_risk_report(self, portfolios):
"""生成日度风险报告"""
pass
def generate_risk_appetite_report(self, risk_metrics, limits):
"""生成风险偏好报告"""
pass
def generate_stress_test_report(self, stress_results):
"""生成压力测试报告"""
pass
def create_risk_dashboard(self, real_time_data):
"""创建风险仪表盘"""
pass
# 业务插件使用风险管理服务示例
from core_plugins.risk_management import MarketRiskManager, CreditRiskManager
from core_plugins.ficc_core import CurveBuilder
class FixedIncomePlugin:
def __init__(self):
self.market_risk_mgr = MarketRiskManager()
self.credit_risk_mgr = CreditRiskManager()
self.curve_builder = CurveBuilder()
def analyze_portfolio_risk(self, bond_portfolio):
# 计算VaR
var_result = self.market_risk_mgr.calculate_var(
portfolio=bond_portfolio,
method="historical",
confidence=0.99
)
# 计算敏感度
sensitivities = self.market_risk_mgr.calculate_sensitivities(
portfolio=bond_portfolio
)
# 计算信用敞口
credit_exposure = self.credit_risk_mgr.calculate_exposure(
counterparty=bond_portfolio.counterparty,
trades=bond_portfolio.trades
)
return {
"var": var_result,
"sensitivities": sensitivities,
"credit_exposure": credit_exposure
}