lbapplyr: Apply Rolling Functions From LBStart to LBEnd Wrapper around...

In jmuhlenkamp/conditionalAR: Conditionally Evaluate Rolling Performance of AR Models

Description

Apply Rolling Functions From LBStart to LBEnd Wrapper around rollapplyr so that we can easily apply rolling functions over lagged windows

Usage

lbapplyr(data, FUN, lbstart = 63, lbend = 0, ...)

Arguments

data	An 'xts' object that is passed to 'rollapplyr'.
FUN	The function to be applied.
lbstart	The start of the lookback window.
lbend	The end of the lookback window.
...	Other arguments passed to rollapplyr.

Examples

growth <- diff(log(stocks))
signal <- rollAR(growth, rep(1/9,9))
# Rolling 10-day long-short hitrate
hits <- lbapplyr(compute_hits(growth, signal, "longshort"), sum, 9, 0)
bets <- lbapplyr(abs(compute_bets(signal, "longshort")), sum, 9, 0)
hr_ls <- hits/bets

# Rolling 10-day long hitrate
hits <- lbapplyr(compute_hits(growth, signal, "long"), sum, 9, 0)
bets <- lbapplyr(abs(compute_bets(signal, "long")), sum, 9, 0)
hr_long <- hits/bets

# Rolling 10-day uprate
hits <- lbapplyr(compute_hits(growth, signal, "alwayslong"), sum, 9, 0)
bets <- lbapplyr(abs(compute_bets(signal, "alwayslong")), sum, 9, 0)
hr_up <- hits/bets

# Rolling 10-day short hitrate
hits <- lbapplyr(compute_hits(growth, signal, "short"), sum, 9, 0)
bets <- lbapplyr(abs(compute_bets(signal, "short")), sum, 9, 0)
hr_short <- hits/bets

# Rolling 10-day downrate
hits <- lbapplyr(compute_hits(growth, signal, "alwaysshort"), sum, 9, 0)
bets <- lbapplyr(abs(compute_bets(signal, "alwaysshort")), sum, 9, 0)
hr_down <- hits/bets

jmuhlenkamp/conditionalAR documentation built on May 30, 2019, 1:59 p.m.