FinMod: Financial Models for Variance and Volatility

Barndorff<e2><80><90>Nielsen and Shephard Realized Variance

1	BNS(ticker, start_date, end_date, prediction_period, days_to_drop, lambda1, delta1, gamma1, phi1, testing)

`ticker`	Stock ticker
`start_date`	Starting date of data to use
`end_date`	Ending date of data to use
`prediction_period`	How many days to predict using the model
`days_to_drop`	Number of days of realized variances to drop when fitting the model
`lambda`	The mean reverting variable
`delta`	Influences the tail thickness of the disribution
`gamma`	Influences the scale of the distribution
`phi`	Volatility of the volatility.
`testing`	Whether to use prediction_period days prior to end_date as the prediction period. If false, the prediction period takes place after end_date