backtest_quality: Compute the quality of a price forecast using backtest...

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

Description

This function calculates the likelihood that a price forecast will be met or exceeded at the next rebalance date.

Usage

backtest_quality(prices, forecasts, fperiod = 21, window = 63)

Arguments

prices	The daily prices matrix of a set of assets (one or more).
forecasts	The daily forecasted prices of the assets. Dimensions must match prices matrix.
fperiod	The forecasted perioc in days. For example, 21 days for a monthly forecast. This is used to compute the lag on prices for the comparison.
window	The backtest window in days. Default is 63 days (3 months).

Details

Over a given time window, it looks at the price forecast every day and determines whether that forecast was met. The BackTest Quality factor (BTQ) is therefore a number between 0 and 1 indicating the fraction of the daily forecasts that resulting in an accurate prediction.

For example, assume we have monthly (21 days) forecasts made daily for the price of an asset. This means that every day, a forecaster function is predicting that the price of the asset will meet or exceed its forecasted value 22 days forward.

This function will test this over a time window (for example, 3 months or 63 days). Therefore, 63 tests will be performed. If the forecast was accurate 40 out of the 63 days, then the BTQ factor is 40/63 = 63.5

The BTW factor is returned as a rolling window xts matrix.

Value

A list containing the following elements:

$BTQ:

An xts matrix containing the results of the rolling backtest quality window. Each value is between 0 and 1 and represents the fraction of the time the forecast was accurate over the time window ending on the current date.

$backtest

A logical xts matrix containing the logical of each forecast, as they were made on the index date, peeking into the future. If the future price does not yet exist, then NA is used. A value of 1 / TRUE indicates that the actual asset price was equal or exceeded the forecasted price. If below, then 0 / FALSE is used.

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