Compute the disposition effect and the disposition difference.

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. Numeric vector (or scalar) containing paper gains values. Numeric vector (or scalar) containing realized losses values. Numeric vector (or scalar) containing paper losses values. Numeric vector (or scalar) containing gains. Numeric vector (or scalar) containing losses. Data frame, the portfolio of the investor containing the realized and paper gains and losses results (as those obtained via portfolio_compute). Logical, if TRUE the disposition difference on the "value" method is computed. Default to disposition effect (FALSE). 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. Data frame, the time series of disposition effects.

## Value

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

## 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 $$DD = Paper Gain - |Paper Loss|$$

## 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.