fn_SpreadBuilder: Calculate prices of a spread from 2 instruments.
In FinancialInstrument: Financial Instrument Model Infrastructure for R

Description Usage Arguments Details Value Note Author(s) See Also Examples

Given 2 products, calculate spread values for as many columns as practicable.

fn_SpreadBuilder(prod1, prod2, ratio = 1, currency = "USD", from = NULL,
  to = NULL, session_times = NULL, notional = TRUE,
  unique_method = c("make.index.unique", "duplicated", "least.liq",
  "price.change"), silent = FALSE, auto.assign = TRUE, env = .GlobalEnv,
  ...)

`prod1`	chr name of instrument that will be the 1st leg of a 2 leg spread (Can also be xts data for first product)
`prod2`	chr name of instrument that will be the 2nd leg of a 2 leg spread (Can also be xts data for second product)
`ratio`	Hedge ratio. Can be a single number, or a vector of same length as data.
`currency`	chr name of currency denomination of the spread
`from`	from Date to pass through to getSymbols if needed.
`to`	to Date to pass through to getSymbols if needed.
`session_times`	ISO-8601 time subset for the session time, in GMT, in the format 'T08:00/T14:59'
`notional`	TRUE/FALSE. Should the prices be multiplied by contract multipliers before calculating the spread?
`unique_method`	method for making the time series unique
`silent`	silence warnings? (FALSE by default)
`auto.assign`	If `TRUE` (the default) the constructed spread will be stored in symbol created with `make_spread_id`. instrument metadata will also be created and stored with the same primary_id.
`env`	If `prod1` and `prod1` are character, this is where to `get` the data. Also, if `auto.assign` is `TRUE` this is the environment in which to store the data (.GlobalEnv by default)
`...`	other arguments to pass to `getSymbols` and/or `make_spread_id`

prod1 and prod2 can be the names of instruments, or the xts objects themselves. Alternatively, prod2 can be omitted, and a vector of 2 instrument names can be given to prod1. See the last example for this usage.

If prod1 and prod2 are names (not xts data), it will try to get data for prod1 and prod2 from env (.GlobalEnv by default). If it cannot find the data, it will get it with a call to getSymbols. Prices are multiplied by multipliers and exchange rates to get notional values in the currency specified. The second leg's notional values are multiplied by ratio. Then the difference is taken between the notionals of leg1 and the new values for leg2.

‘make.index.unique’ uses the xts function make.index.unique ‘least.liq’ subsets the spread time series, by using the timestamps of the leg that has the fewest rows. ‘duplicated’ removes any duplicate indexes. ‘price.change’ only return rows where there was a price change in the Bid, Mid or Ask Price of the spread.

an xts object with Bid, Ask, Mid columns, or Open, Close, Adjusted columns, or Open, Close columns. or Price column.

requires quantmod

Lance Levenson, Brian Peterson, Garrett See

buildSpread synthetic.instrument formatSpreadPrice buildRatio

## Not run: 
currency("USD")
stock("SPY", "USD")
stock("DIA", "USD")
getSymbols(c("SPY","DIA"))

#can call with names of instrument/xts ojects
fSB <- fn_SpreadBuilder("SPY","DIA")
fSB2 <- fn_SpreadBuilder(SPY,DIA) # or you can pass xts objects

#assuming you first somehow calculated the ratio to be a constant 1.1
fSB3 <- fn_SpreadBuilder("SPY","DIA",1.1)
head(fSB)

# Call fn_SpreadBuilder with vector of 2 instrument names
# in 1 arg instead of using both prod1 and prod2.
fSB4 <- fn_SpreadBuilder(c("SPY","DIA"))
#download data and plot the closing values of a spread in one line
chartSeries(Cl(fn_SpreadBuilder(getSymbols(c("SPY","DIA")),auto.assign=FALSE)))

## End(Not run)