Per Bailey and Lopex de Prado (2014), construct a Deflated Sharpe Ratio and associated p-value based on an observed Sharpe ratio and information drawn from a series of trials (e.g. parameter optimization or other strategies tried before the candidate strategy)
deflatedSharpe(portfolios, ..., strategy = NULL, trials = NULL,
audit = NULL, env = .GlobalEnv).deflatedSharpe(sharpe, nTrials, varTrials, skew, kurt, numPeriods,
periodsInYear = 252)
string name of portfolio, or optionally a vector of portfolios, see DETAILS
any other passtrhrough parameters
optional strategy specification that would contain more information on the process, default NULL
optional number of trials,default NULL
optional audit environment containing the results of parameter optimization or walk forward, default NULL
optional environment to find market data in, if required.
candidate (annualized) Sharpe Ratio
numeric number or trials
variance of Sharpe ratios of the trials
skewness of the candidate
non-excess kurtosis
total periods in the backtest
number of periods in a year, default 252 (daily)
a data.frame containing:
original observed Sharpe ratio
deflated Sharpe ratio
p-value of the deflated Sharpe ratio
number of trials used for adjustment
this object may change in the future, and may be classed so that we can include more information
Bailey, David H, and Marcos Lopez de Prado. 2014. "The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting and Non-Normality." Journal of Portfolio Management 40 (5): 94-107. http://www.davidhbailey.com/dhbpapers/deflated-sharpe.pdf
https://quantstrattrader.wordpress.com/2015/09/24/