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Method Comparison & Use Cases

This guide provides a comprehensive comparison of all yfinance-go methods, their capabilities, limitations, and recommended use cases to help you choose the right method for your needs.

Overview

yfinance-go provides two main categories of methods:

  1. API Methods: Direct access to Yahoo Finance API endpoints
  2. Scraping Methods: Web scraping fallback for data not available through APIs

Method Comparison Table

Method Category Use Case Data Returned Limitations Performance
FetchQuote() API Real-time prices Current price, volume, market data No historical data Fast
FetchDailyBars() API Historical analysis OHLCV data for date range Limited to available history Fast
FetchWeeklyBars() API Long-term trends Weekly OHLCV data Limited historical depth Fast
FetchMonthlyBars() API Long-term analysis Monthly OHLCV data Limited historical depth Fast
FetchIntradayBars() API Short-term analysis Intraday OHLCV data May return 422 errors Fast
ScrapeFinancials() Scraping Fundamental analysis Revenue, EPS, financial metrics Quarterly/annual data only Slower
ScrapeBalanceSheet() Scraping Balance sheet analysis Assets, liabilities, equity Quarterly/annual data only Slower
ScrapeCashFlow() Scraping Cash flow analysis Operating, investing, financing cash flows Quarterly/annual data only Slower
ScrapeKeyStatistics() Scraping Key metrics P/E ratios, market cap, financial metrics May be limited for some stocks Slower
ScrapeAnalysis() Scraping Analyst insights Estimates, projections May be limited for smaller companies Slower
ScrapeAnalystInsights() Scraping Detailed analysis Comprehensive analyst data May be limited for smaller companies Slower
ScrapeNews() Scraping Market sentiment Recent news articles May be empty for some stocks Slower
FetchCompanyInfo() API Basic company data Name, exchange, currency No address/executives Fast
FetchMarketData() API Comprehensive market data Price, volume, 52-week ranges No historical data Fast
FetchFundamentalsQuarterly() API Quarterly fundamentals Financial statement data Requires paid subscription Fast

Detailed Method Analysis

Real-time Data Methods

FetchQuote()

Best for: Getting current market prices and basic market data

Returns:

  • Current market price
  • Bid/ask prices and sizes
  • Daily high/low
  • Volume
  • Market venue information

Limitations:

  • No historical data
  • May be delayed (not real-time)
  • Some fields may be nil

Use Cases:

  • Real-time price monitoring
  • Portfolio valuation
  • Market data dashboards
  • Trading applications

Example:

quote, err := client.FetchQuote(ctx, "AAPL", runID)
if quote.RegularMarketPrice != nil {
    price := float64(quote.RegularMarketPrice.Scaled) / 
            float64(quote.RegularMarketPrice.Scale)
    fmt.Printf("Current price: $%.2f\n", price)
}

FetchMarketData()

Best for: Comprehensive market data including 52-week ranges

Returns:

  • Current market price
  • Daily high/low
  • 52-week high/low
  • Previous close
  • Market time information

Limitations:

  • No historical data
  • No fundamental metrics

Use Cases:

  • Market analysis dashboards
  • Price range analysis
  • Market timing applications

Historical Data Methods

FetchDailyBars()

Best for: Daily price analysis and backtesting

Returns:

  • Daily OHLCV data
  • Split/dividend adjustments
  • Volume information
  • Currency information

Limitations:

  • Limited by Yahoo Finance's historical data availability
  • Some symbols may have incomplete data

Use Cases:

  • Technical analysis
  • Backtesting strategies
  • Portfolio performance analysis
  • Risk management

Example:

start := time.Date(2024, 1, 1, 0, 0, 0, 0, time.UTC)
end := time.Date(2024, 12, 31, 0, 0, 0, 0, time.UTC)
bars, err := client.FetchDailyBars(ctx, "AAPL", start, end, true, runID)

FetchIntradayBars()

Best for: Short-term trading and intraday analysis

Returns:

  • Intraday OHLCV data (1m, 5m, 15m, 30m, 60m)
  • High-frequency price data

Limitations:

  • May return HTTP 422 errors for some symbols
  • Limited historical depth (typically 60 days for 1m data)
  • Data availability varies by symbol

Use Cases:

  • Day trading
  • Intraday analysis
  • High-frequency trading
  • Market microstructure analysis

FetchWeeklyBars() / FetchMonthlyBars()

Best for: Long-term trend analysis

Returns:

  • Weekly/monthly OHLCV data
  • Long-term price trends

Limitations:

  • Limited historical depth
  • Less granular than daily data

Use Cases:

  • Long-term investment analysis
  • Trend identification
  • Macro analysis
  • Portfolio rebalancing

Company Information Methods

FetchCompanyInfo()

Best for: Basic company identification and exchange information

Returns:

  • Company name (long and short)
  • Exchange information
  • Currency
  • Instrument type
  • Timezone information
  • First trade date

⚠️ Important Limitations:

  • Only returns basic security information
  • Does NOT include: Address, executives, website, employees, business summary
  • Use case: Basic identification only

Use Cases:

  • Symbol validation
  • Exchange identification
  • Basic company lookup
  • Data source identification

Example:

companyInfo, err := client.FetchCompanyInfo(ctx, "AAPL", runID)
fmt.Printf("Company: %s\n", companyInfo.LongName)
fmt.Printf("Exchange: %s\n", companyInfo.Exchange)
// Note: No address, executives, or business summary available

Fundamentals Methods

FetchFundamentalsQuarterly()

Best for: Quarterly financial data (requires paid subscription)

Returns:

  • Quarterly financial statements
  • EPS, revenue, net income
  • Financial ratios

⚠️ Important Limitations:

  • Requires Yahoo Finance paid subscription
  • Returns error with exit code 2 if subscription required
  • Limited to quarterly data only

Use Cases:

  • Financial analysis (if you have paid subscription)
  • Earnings analysis
  • Financial modeling

ScrapeFinancials()

Best for: Income statement data without paid subscription

Returns:

  • Revenue, expenses, net income
  • EPS (basic and diluted)
  • Financial statement line items

Limitations:

  • Quarterly/annual data only
  • Slower than API methods
  • May be limited for some stocks

Use Cases:

  • Financial analysis
  • Earnings analysis
  • Financial modeling
  • Investment research

ScrapeBalanceSheet()

Best for: Balance sheet analysis

Returns:

  • Assets, liabilities, equity
  • Balance sheet line items
  • Financial position data

Use Cases:

  • Financial health analysis
  • Debt analysis
  • Asset analysis
  • Financial ratio calculations

ScrapeCashFlow()

Best for: Cash flow analysis

Returns:

  • Operating, investing, financing cash flows
  • Cash flow statement data
  • Liquidity analysis

Use Cases:

  • Cash flow analysis
  • Liquidity assessment
  • Financial health evaluation
  • Investment analysis

ScrapeKeyStatistics()

Best for: Key financial metrics and ratios

Returns:

  • P/E ratio, market cap
  • Enterprise value
  • Financial ratios
  • Key performance indicators

Use Cases:

  • Valuation analysis
  • Financial ratio analysis
  • Investment screening
  • Performance metrics

Analysis Methods

ScrapeAnalysis()

Best for: Analyst recommendations and price targets

Returns:

  • Analyst recommendations
  • Price targets
  • Earnings estimates
  • Analyst ratings

Limitations:

  • May be limited for smaller companies
  • Slower than API methods

Use Cases:

  • Investment research
  • Analyst sentiment analysis
  • Price target analysis
  • Market sentiment

ScrapeAnalystInsights()

Best for: Detailed analyst insights

Returns:

  • Comprehensive analyst data
  • Detailed insights
  • Analyst reports

Use Cases:

  • Investment research
  • Analyst sentiment analysis
  • Market research
  • Investment decision support

News Methods

ScrapeNews()

Best for: Market sentiment and news analysis

Returns:

  • Recent news articles
  • Press releases
  • Market news

Limitations:

  • May be empty for some stocks
  • News availability varies by company

Use Cases:

  • Market sentiment analysis
  • News monitoring
  • Event-driven analysis
  • Risk assessment

Recommended Data Fetching Strategy

1. Start with Quote

Get current market data for real-time applications:

quote, err := client.FetchQuote(ctx, "AAPL", runID)

2. Add Historical Data

Get price history for analysis:

bars, err := client.FetchDailyBars(ctx, "AAPL", start, end, true, runID)

3. Include Fundamentals

Get financial metrics for analysis:

financials, err := client.ScrapeFinancials(ctx, "AAPL", runID)
keyStats, err := client.ScrapeKeyStatistics(ctx, "AAPL", runID)

4. Add Analysis

Get analyst estimates and recommendations:

analysis, err := client.ScrapeAnalysis(ctx, "AAPL", runID)

5. Include News

Get market sentiment:

news, err := client.ScrapeNews(ctx, "AAPL", runID)

6. Handle Company Info

Use for basic identification only:

companyInfo, err := client.FetchCompanyInfo(ctx, "AAPL", runID)
// Note: Limited data, use alternative sources for detailed profiles

Performance Considerations

Fast Methods (API-based)

  • FetchQuote()
  • FetchDailyBars()
  • FetchWeeklyBars()
  • FetchMonthlyBars()
  • FetchIntradayBars()
  • FetchCompanyInfo()
  • FetchMarketData()

Slower Methods (Scraping-based)

  • ScrapeFinancials()
  • ScrapeBalanceSheet()
  • ScrapeCashFlow()
  • ScrapeKeyStatistics()
  • ScrapeAnalysis()
  • ScrapeAnalystInsights()
  • ScrapeNews()

Performance Optimization Tips

  1. Use API methods when possible for better performance
  2. Use session rotation for high-volume requests
  3. Implement rate limiting to avoid being blocked
  4. Cache results when appropriate
  5. Use concurrent processing for multiple symbols

Error Handling by Method Type

API Methods

  • Network errors
  • Rate limiting (429)
  • Invalid symbols
  • Data not available

Scraping Methods

  • Parse errors
  • Website structure changes
  • Rate limiting
  • Empty results

Paid Subscription Methods

  • Authentication errors (401)
  • Subscription required (exit code 2)

Data Quality Expectations

High Quality (API Methods)

  • Quotes: Generally available for all active stocks
  • Historical Data: Available for most stocks
  • Company Info: Basic info only

Variable Quality (Scraping Methods)

  • Financials: Available for most public companies
  • Analysis: May be limited for smaller companies
  • News: Highly variable, may be empty

Use Case Recommendations

Trading Applications

  • Use FetchQuote() for real-time prices
  • Use FetchIntradayBars() for short-term analysis
  • Use FetchDailyBars() for daily analysis

Investment Research

  • Use ScrapeFinancials() for financial analysis
  • Use ScrapeKeyStatistics() for valuation metrics
  • Use ScrapeAnalysis() for analyst insights
  • Use ScrapeNews() for market sentiment

Portfolio Management

  • Use FetchDailyBars() for performance analysis
  • Use FetchQuote() for current valuations
  • Use ScrapeKeyStatistics() for risk metrics

Market Analysis

  • Use FetchMarketData() for comprehensive market data
  • Use ScrapeNews() for market sentiment
  • Use ScrapeAnalysis() for analyst sentiment

Next Steps