Class: FinModeling::CAPM::Beta

Inherits:
Object
  • Object
show all
Defined in:
lib/finmodeling/capm.rb

Class Method Summary collapse

Class Method Details

.from_ticker(company_ticker, num_days = 6*365, index_ticker = "SPY") ⇒ Object

Possible index tickers: “Spy” -> S&P 500 “^IXIC” -> Nasdaq



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# File 'lib/finmodeling/capm.rb', line 30

def self.from_ticker(company_ticker, num_days=6*365, index_ticker="SPY")
  index_quotes   = FamaFrench::EquityHistoricalData.new(index_ticker,   num_days)
  company_quotes = FamaFrench::EquityHistoricalData.new(company_ticker, num_days)
 
  common_dates = index_quotes  .year_and_month_strings &
                 company_quotes.year_and_month_strings

  index_quotes  .filter_by_date!(common_dates)
  company_quotes.filter_by_date!(common_dates)
  
  index_div_hist   = NasdaqQuery::DividendHistory.for_symbol(index_ticker)
  company_div_hist = NasdaqQuery::DividendHistory.for_symbol(company_ticker)
   
  index_monthly_returns   = index_quotes  .monthly_returns(index_div_hist)
  company_monthly_returns = company_quotes.monthly_returns(company_div_hist)
  
  x = GSL::Vector.alloc(index_monthly_returns)
  y = GSL::Vector.alloc(company_monthly_returns)
  intercept, slope, cov00, cov01, cov11, chisq, status = GSL::Fit::linear(x, y)
  
  # FIXME: evaluate [intercept - Rf*(1-beta)]. It tells how much better/worse than expected (given its risk) the stock did. [per time period]

  # FIXME: subtracting/adding one standard error of the beta gives a 95% confidence interval. That could be used to give a confidence interval
  #        for the resulting valuation.

  beta = slope
end