disposition_effect {dispositionEffect}

Disposition Effect

Description

Compute the disposition effect and the disposition difference.

Usage

disposition_effect(realized_gains, paper_gains, realized_losses, paper_losses)

disposition_difference(gains, losses)

disposition_compute(
  gainslosses,
  dispdiff_value = FALSE,
  aggregate_fun = NULL,
  ...
)

disposition_compute_ts(gainslosses, aggregate_fun = NULL, ...)

disposition_summary(gainslosses, dispdiff_value = FALSE)

disposition_summary_ts(de_timeseries)

Arguments

realized_gains

Numeric vector (or scalar) containing realized gains values.

paper_gains

Numeric vector (or scalar) containing paper gains values.

realized_losses

Numeric vector (or scalar) containing realized losses values.

paper_losses

Numeric vector (or scalar) containing paper losses values.

gains

Numeric vector (or scalar) containing gains.

losses

Numeric vector (or scalar) containing losses.

gainslosses

Data frame, the portfolio of the investor containing the realized and paper gains and losses results (as those obtained via portfolio_compute).

dispdiff_value

Logical, if TRUE the disposition difference on the "value" method is computed. Default to disposition effect (FALSE).

aggregate_fun

Function to use to aggregate results. Default to NULL, that is no aggregation is performed and the results of each asset are shown.

...

Further arguments to be passed to the aggregate function.

de_timeseries

Data frame, the time series of disposition effects.

Details

The disposition effect is defined as DE = (Realized Gain / (Realized Gain - Paper Gain)) - (Realized Loss / (Realized Loss + Paper Loss))

The disposition difference is defined as DD = Realized Gain - |Realized Loss| or DD = Paper Gain - |Paper Loss|

Value

Numeric vector (or scalar) with the value(s) of disposition effect(s) or disposition difference(s).

Functions

• disposition_effect: Compute the disposition effect

• disposition_difference: Compute the disposition difference

• disposition_compute: Compute the disposition effect directly on the investor's portfolio containing realized and paper gains and losses results.

• disposition_compute_ts: Compute the time series disposition effect on the gains and losses results.

• disposition_summary: Wrapper that returns the most important summary statistics related to the disposition effect.

• disposition_summary_ts: Wrapper that returns the most important summary statistics related to the time series disposition effect.