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)
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
Logical, if TRUE the disposition difference on the "value" method is computed. Default to disposition effect (FALSE).
Function to use to aggregate results.
Further arguments to be passed to the aggregate function.
Data frame, the time series of disposition effects.
Numeric vector (or scalar) with the value(s) of disposition effect(s) or disposition difference(s).
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 \(DD = Paper Gain - |Paper Loss|\)
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
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.