trdhp: Hodrick-Prescott Filter

In FRAPO: Financial Risk Modelling and Portfolio Optimisation with R

Description

Calculation of the Hodrick-Prescott filter as a technical trading indicator.

Usage

trdhp(y, lambda)

Arguments

y	Objects of classes: numeric, matrix, data.frame, ts, mts, and timeSeries are supported.
lambda	Numeric, the value for λ in the equation below.

Details

The Hodrick-Prescott filter is calculated according to the formula:

\min (τ_t) = ∑_{t = 1}^T (y_t - τ_t)^2 + λ ∑_{t = 2}^{T-1} (Δ^2 τ_{t+1})^2

Value

An object of the same class as y, containing the computed Hodrick-Prescott values.

Methods

y = "data.frame"

The calculation is applied per column of the data.frame and only if all columns are numeric.

y = "matrix"

The calculation is applied per column of the matrix.

y = "mts"

The calculation is applied per column of the mts object. The attributes are preserved and an object of the same class is returned.

y = "numeric"

Calculation of the bilson trend.

y = "timeSeries"

The calculation is applied per column of the timeSeries object and an object of the same class is returned.

y = "ts"

Calculation of the bilson trend. The attributes are preserved and an object of the same class is returned.

y = "xts"

Calculation of the bilson trend. The attributes are preserved and an object of the same class is returned.

y = "zoo"

Calculation of the bilson trend. The attributes are preserved and an object of the same class is returned.

Author(s)

Bernhard Pfaff

References

Hodrick, R. and E.C. Prescott (1997), Postwar U.S. Business Cycles: An Empirical Investigation, Journal of Money, Credit and Banking 29(1).

See Also

trdbinary, trdes, trdbilson, trdsma, trdwma, capser

Examples

data(StockIndex)
y <- StockIndex[, "SP500"]
hp <- trdhp(y, lambda = 1600)
head(hp)

FRAPO documentation built on May 2, 2019, 6:33 a.m.