returnStats {ttrTests}R Documentation

Conditional statistics for given data and TTR

Description

The first of four main backtests for a technical analysis strategy. Gives returns conditioned on the TTR above and beyond some benchmark.

Usage

returnStats(x, ttr = "macd4", params = 0, burn = 0, short = FALSE, 
condition = NULL, silent = FALSE, TC = 0.001, benchmark = "hold", latex="")

Arguments

x A univariate series
ttr The TTR to be used. Can be a character string for built-in TTRs, or a user defined function whose output is a position series s(t). See 'defaults' for a list of built-in TTRs.
params A list of parameters to use for the TTR
burn When computing the position function s(t), values for t < burn will be forced to 0, i.e. no position held during the 'burn' period
short Logical. If false the position function s(t) will be forced to 0 when it would otherwise be -1, i.e. no short selling
condition An extra opportunity to restrict the TTR so that position is forced to 0 under some condition. Must be a binary string of the same length as the data 'x'. See 'position' for more details.
silent Logical. If TRUE, supresses output from subroutines
TC Percentage used to compute returns adjusted for trading costs.
benchmark When computing 'excess' returns, all functions in this package subtract the conditional returns based on a given "ttr" from the "benchmark" returns. Two different TTRs can be compared this way if desired.
latex Full path name for a writable file. The laTeX code that generates a figure with a summary of the output will be appended to file.

Details

"excess return" means the conditional return minus the benchmark return

Value

uResults and cResults are each of lenght 10 and include: mean, variance, sharp ratio, skew, kurtosis, and first 5 autocorrelation coefficients
The third item of output is the excess return adjusted for trading costs.

Note

EXTREMELY IMPORTANT NOTE: The functions in this package evaluate past performance only. No warranty is made that the results of these tests should, or even can, be used to inform business decisions or make predictions of future events.

The author does not make any claim that any results will predict future performance. No such prediction is made, directly or implied, by the outputs of these function, and any attempt to use these function for such prediction is done solely at the risk of the end user.

Author(s)

David St John

References

William Brock, Josef Lakonishok, and Blake LeBaron. Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5):1731-1764, 1992.

Examples


spData <- as.vector(getYahooData("SPY",start="20060101",end="20081231")[,"Close"])
stat <- returnStats(spData)


[Package ttrTests version 1.4 Index]