financial-analysis-agent
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ChineseFinancial Analysis Agent
财务分析Agent
Build intelligent financial analysis agents that evaluate investments, assess risks, and generate data-driven recommendations.
构建可评估投资、分析风险并生成数据驱动型建议的智能财务分析Agent。
Financial Data Integration
金融数据集成
See examples/financial_data_collector.py for the class that:
FinancialDataCollector- Integrates with yfinance for stock data
- Retrieves financial statements (income, balance sheet, cash flow)
- Fetches key metrics (market cap, PE ratio, dividend yield, etc.)
查看examples/financial_data_collector.py中的类，它具备以下功能：
FinancialDataCollector- 与yfinance集成以获取股票数据
- 检索财务报表（利润表、资产负债表、现金流量表）
- 获取关键指标（市值、市盈率、股息率等）
Financial Analysis Techniques
财务分析技术
Technical Analysis
技术分析
See examples/technical_analyzer.py for :
TechnicalAnalyzer- Moving averages calculation
- Relative Strength Index (RSI)
- Support and resistance level identification
查看examples/technical_analyzer.py中的：
TechnicalAnalyzer- 移动平均线计算
- 相对强弱指数（RSI）
- 支撑位和阻力位识别
Fundamental Analysis
基本面分析
See examples/fundamental_analyzer.py for :
FundamentalAnalyzer- Profitability ratios (gross margin, operating margin, net margin, ROA, ROE)
- Valuation ratios (PE, PB, PEG, price-to-sales)
- Liquidity ratios (current ratio, quick ratio, debt-to-equity)
查看examples/fundamental_analyzer.py中的：
FundamentalAnalyzer- 盈利能力比率（毛利率、营业利润率、净利润率、资产回报率ROA、净资产回报率ROE）
- 估值比率（市盈率PE、市净率PB、市盈增长比率PEG、市销率）
- 流动性比率（流动比率、速动比率、负债权益比）
Risk Assessment
风险评估
See examples/risk_analyzer.py for :
RiskAnalyzer- Volatility calculation
- Value at Risk (VaR) assessment
- Sharpe Ratio calculation
- Company risk assessment
查看examples/risk_analyzer.py中的：
RiskAnalyzer- 波动率计算
- 在险价值（VaR）评估
- 夏普比率计算
- 公司风险评估
Investment Recommendations
投资建议
See examples/investment_recommender.py for :
InvestmentRecommender- Generates recommendations (Strong Buy, Buy, Hold, Sell, Strong Sell)
- Calculates investment scores based on technical and fundamental signals
- Provides confidence levels and risk assessments
查看examples/investment_recommender.py中的：
InvestmentRecommender- 生成投资建议（强力买入、买入、持有、卖出、强力卖出）
- 根据技术面和基本面信号计算投资评分
- 提供置信水平和风险评估
Portfolio Management
投资组合管理
See examples/portfolio_manager.py for :
PortfolioManager- Calculate portfolio total value
- Rebalance portfolio based on target allocations
- Assess portfolio risk and volatility
查看examples/portfolio_manager.py中的：
PortfolioManager- 计算投资组合总价值
- 根据目标配置重新平衡投资组合
- 评估投资组合风险和波动率
Market Intelligence
市场情报
Build market intelligence capabilities by:
- Analyzing overall market trends and sector performance
- Calculating market volatility indices
- Fetching economic indicators
- Identifying undervalued, growth, and dividend opportunities
通过以下方式构建市场情报能力：
- 分析整体市场趋势和行业表现
- 计算市场波动率指数
- 获取经济指标
- 识别被低估、成长型和高股息投资机会
Best Practices
最佳实践
Analysis Quality
分析质量
- ✓ Use multiple data sources
- ✓ Cross-validate findings
- ✓ Document assumptions
- ✓ Consider time horizons
- ✓ Account for fees and taxes
- ✓ 使用多个数据源
- ✓ 交叉验证分析结果
- ✓ 记录假设前提
- ✓ 考虑时间周期
- ✓ 计入费用和税收
Risk Management
风险管理
- ✓ Assess downside risk
- ✓ Implement stop losses
- ✓ Diversify appropriately
- ✓ Position size accordingly
- ✓ Review regularly
- ✓ 评估下行风险
- ✓ 设置止损
- ✓ 合理分散投资
- ✓ 调整头寸规模
- ✓ 定期回顾
Ethical Considerations
伦理考量
- ✓ Disclose conflicts of interest
- ✓ Avoid market manipulation
- ✓ Base recommendations on analysis
- ✓ Update recommendations regularly
- ✓ Acknowledge limitations
- ✓ 披露利益冲突
- ✓ 避免市场操纵
- ✓ 基于分析结果给出建议
- ✓ 定期更新建议
- ✓ 承认局限性
Tools & Data Sources
工具与数据源
Data APIs
数据API
- yfinance
- Alpha Vantage
- IEX Cloud
- Polygon.io
- Yahoo Finance
- yfinance
- Alpha Vantage
- IEX Cloud
- Polygon.io
- Yahoo Finance
Analysis Libraries
分析库
- pandas
- NumPy
- scikit-learn
- TA-Lib
- statsmodels
- pandas
- NumPy
- scikit-learn
- TA-Lib
- statsmodels
Getting Started
快速开始
- Collect financial data
- Perform technical analysis
- Analyze fundamentals
- Assess risks
- Generate recommendations
- Monitor positions
- Rebalance periodically
- 收集金融数据
- 执行技术分析
- 分析基本面
- 评估风险
- 生成投资建议
- 监控持仓
- 定期重新平衡