OI_aggregate_factor-methods: Construct futures open interest growth (OI) aggregate factor
In bautheac/factorem: factor'em!

Description Usage Arguments Value References

Provided with futures contract front price and aggregate open interest data from Bloomberg retrieved with pullit, construct aggregate open interest growth (OI) factor. The open interest factor relates to futures market liquidity and is popular in the literature, in particular in the context of commodity markets research \insertCitehong_what_2012factorem. The aggregate open interest factor \insertCitebasu_financiallization_2018factorem is concerned with liquidity over the whole futures term strucutre and sorts on open interest aggregated (summed up) over the futures term structure.

OI_aggregate_factor(
  price_data,
  aggregate_data,
  update_frequency = "month",
  return_frequency = "day",
  ranking_period = 1L,
  long_threshold = 0.5,
  short_threshold = 0.5,
  weighted = F
)

## S4 method for signature 'FuturesTS,FuturesAggregate'
OI_aggregate_factor(
  price_data,
  aggregate_data,
  update_frequency = "month",
  return_frequency = "day",
  ranking_period = 1L,
  long_threshold = 0.5,
  short_threshold = 0.5,
  weighted = F
)

`price_data`	an S4 object of class `FuturesTS`. `FuturesTS` objects are returned by the `BBG_futures_TS` function from the pullit package.
`aggregate_data`	an S4 object of class `FuturesAggregate`. `FuturesAggregate` objects are returned by the `BBG_futures_aggregate` function from the `pullit` package.
`update_frequency`	a scalar `character` vector. Specifies the rebalancing frequency. Must be one of 'year', 'semester', 'quarter', 'month' or 'week'. Defaults to 'month'.
`return_frequency`	a scalar `character` vector. Specifies the frequency of the returns output. Must be one of 'year', 'semester', 'quarter', 'month', 'week' or 'day'. Defaults to 'day'.
`ranking_period`	a scalar `integer` vector. Specifies number of periods in term of `update_frequency` looking backward for aggregate open interest average growth calculation. Defaults to 1 where sort is done on last observation only.
`long_threshold`	a scalar `numeric` vector. Specifies the threshold for short positions. Default: 0.5.
`short_threshold`	a scalar `numeric` vector. Specifies the threshold for long positions. Default: 0.5.
`weighted`	a scalar `logical` vector. If 'TRUE' adjusts portoflio weights with respect to sorting variable values, else equal weights are used. Defaults to 'FALSE'.