fx-desk

name	fx-desk
description	外汇业务插件 - 汇率分析、外汇交易、衍生品分析与估值
dependency	{"python":["pandas>=2.0.0","numpy>=1.24.0"]}

外汇业务插件 (FX Desk)

概述

外汇业务插件是FICC业务插件层的重要组成部分，专注于外汇市场的分析、交易和风险管理，包括即期外汇、远期外汇、外汇期权、货币互换等产品。

功能模块

1. 汇率分析与预测

class FXAnalyzer:
    """外汇分析器"""
    
    def analyze_exchange_rate(self, currency_pair, historical_data):
        """
        分析汇率走势
        
        包括：趋势分析、波动性分析、技术指标
        """
        pass
    
    def calculate_carry_trade_return(self, funding_ccy, investment_ccy, rates_data):
        """
        计算套利交易收益
        
        Carry Return = (Investment Rate - Funding Rate) + FX Return
        """
        pass
    
    def analyze_purchasing_power_parity(self, currency_pair, inflation_data):
        """
        分析购买力平价
        """
        pass
    
    def calculate_real_effective_exchange_rate(self, currency, trade_weights):
        """
        计算实际有效汇率(REER)
        """
        pass

2. 外汇敞口管理

class FXExposureManager:
    """外汇敞口管理器"""
    
    def calculate_position_exposure(self, positions, base_currency):
        """
        计算头寸敞口
        
        按币种、期限、类型分解敞口
        """
        pass
    
    def calculate_cash_flow_exposure(self, cash_flows, currencies):
        """
        计算现金流敞口
        
        分析未来各币种现金流入流出
        """
        pass
    
    def calculate_translation_exposure(self, foreign_assets, exchange_rates):
        """
        计算折算敞口
        
        境外资产负债因汇率变动产生的账面损益
        """
        pass
    
    def generate_hedge_recommendations(self, exposure_analysis, hedge_instruments):
        """
        生成对冲建议
        
        推荐最优对冲工具和比例
        """
        pass

3. 外汇衍生品定价与分析

class FXDerivativePricer:
    """外汇衍生品定价器"""
    
    def price_fx_forward(self, spot_rate, domestic_rate, foreign_rate, maturity):
        """
        定价外汇远期
        
        F = S × exp((r_d - r_f) × T)
        """
        pass
    
    def price_fx_swap(self, near_date, far_date, spot_rate, points):
        """
        定价外汇掉期
        """
        pass
    
    def price_fx_option(self, option_params, market_data, model="garman_kohlhagen"):
        """
        定价外汇期权
        
        Models: Garman-Kohlhagen, Vanna-Volga, Local Volatility
        """
        pass
    
    def price_ccs(self, ccs_params, discount_curves):
        """
        定价货币互换(CCS)
        """
        pass
    
    def calculate_option_greeks(self, fx_option, market_data):
        """
        计算外汇期权希腊字母
        
        包括：Delta, Gamma, Vega, Theta, Rho, Vanna, Volga
        """
        pass

4. 套保有效性分析

class FXHedgeEffectivenessAnalyzer:
    """外汇套保有效性分析器"""
    
    def dollar_offset_test(self, hedged_item, hedging_instrument, period):
        """
        美元抵消法测试
        
        比率在80%-125%之间为高度有效
        """
        pass
    
    def regression_analysis(self, hedged_item_series, hedging_instrument_series):
        """
        回归分析
        
        R² ≥ 0.8 且斜率在0.8-1.25之间为高度有效
        """
        pass
    
    def calculate_hedge_ineffectiveness(self, hedged_item, hedging_instrument):
        """
        计算套保无效部分
        
        用于会计处理和风险管理
        """
        pass
    
    def generate_hedge_documentation(self, hedge_relationship, effectiveness_results):
        """
        生成套保文档
        
        满足会计准则要求的套保文档
        """
        pass

与核心插件的集成

# 外汇业务插件使用核心服务示例

from core_plugins.ficc_core import CurveBuilder, DataConnectionManager
from core_plugins.risk_management import MarketRiskManager

class FXDeskPlugin:
    def __init__(self):
        self.curve_builder = CurveBuilder()
        self.data_conn = DataConnectionManager()
        self.risk_manager = MarketRiskManager()
        self.fx_analyzer = FXAnalyzer()
        self.fx_pricer = FXDerivativePricer()
    
    def analyze_fx_portfolio(self, fx_portfolio, market_data):
        # 获取市场数据
        fx_rates = self.data_conn.connect_market_data("bloomberg").get_fx_rates()
        
        # 分析汇率走势
        trend_analysis = self.fx_analyzer.analyze_exchange_rate(
            currency_pair=fx_portfolio.base_currency + fx_portfolio.quote_currency,
            historical_data=market_data.historical_rates
        )
        
        # 计算敞口
        exposure = FXExposureManager().calculate_position_exposure(
            positions=fx_portfolio.positions,
            base_currency="CNY"
        )
        
        # 衍生品定价
        for option in fx_portfolio.options:
            price = self.fx_pricer.price_fx_option(
                option_params=option.params,
                market_data=market_data,
                model="garman_kohlhagen"
            )
        
        # 风险计算
        var_result = self.risk_manager.calculate_var(
            portfolio=fx_portfolio,
            method="historical",
            confidence=0.99
        )
        
        return {
            "trend_analysis": trend_analysis,
            "exposure": exposure,
            "risk_metrics": var_result
        }

依赖项

• pandas >= 2.0.0
• numpy >= 1.24.0