Qscore: Calculate the Quality score of a prediction

In jeanmarcgp/xtsanalytics: A library of functions to do advanced analytics of time series data (xts matrices).

Description

The quality score (Qscore) is a simple measure of prediction quality of a model. The Qscore is a performance comparison of three equity curves: a buy and hold strategy, a long only strategy (go to cash when the prediction is down), or a long-short strategy.

Usage

Qscore(xy, on = "days")

Arguments

xy	An xts matrix of two columns. The first column contains the actual value (y), whereas the second column contains the predicted value (yhat) The order of the columns matter to calculate an accurate score.
on	The periodic granularity of xts matrix xy, and used to accurately calculate the performance metrics. Default is 'days'. Can be any of: 'days', 'weeks', 'months', 'quarters' or 'years'.

Details

An xts matrix of two columns must be provided. Column 1 is the actual single period return of the asset (normally y in a model) and column 2 is the single period normalized prediction for associated time period (normally yhat in a model).

Normally, xy is a daily matrix, but the predictions may be done at some lower granularity (on = 'months' for example). The equity curves are built based upon the predictions (xy column 2).

Any rows containing NAs are removed.

Value

The Qscore is a 5 row by 3 column data frame containing performance statistics of the three equity curves built using the prediction: buy-hold, long-only and long-short.

The columns are:

      Buy_Hold:   Performance results for a buy and hold strategy of that asset.

      Long_Short: Performance when buying the asset on a positive prediction and shorting
      the asset on a negative prediction.

      Long_Only:  Performance when buying the asset on a positive prediction and staying in cash
      otherwise. 

The rows contain performance figures as follows:

      Annualized Return:   Annualized return expressed in percentage.

      Maximum Drawdown:    Maximum drawdown expressed in percentage.

      Annualized Std Dev:  Standard deviation of returns in percent, annualized.

      Annualized Sharpe:   The annualized Sharpe ratio (risk free rate = 0

      Excess Return:       The excess annualized return in percent above the Buy and Hold strategy.

      

TODO: Add trade statistics, such as total number of trades, and average number of trades per year.

jeanmarcgp/xtsanalytics documentation built on May 19, 2019, 12:38 a.m.