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Date-stamping periods of mildly explosive behavior

Source: R/radf-methods.R
datestamp.Rd

Computes the origination, termination and duration of episodes during which the time series display explosive dynamics.

Usage

datestamp(object, cv = NULL, min_duration = 0L, ...)

# S3 method for class 'radf_obj'
datestamp(
  object,
  cv = NULL,
  min_duration = 0L,
  sig_lvl = 95,
  option = c("gsadf", "sadf", "svadf"),
  nonrejected = FALSE,
  ...
)

Arguments

object

An object of class obj.

cv

An object of class cv.

min_duration

The minimum duration of an explosive period for it to be reported (default = 0).

...

further arguments passed to methods.

sig_lvl

logical. Significance level, one of 90, 95 or 99. Ignored when option = "svadf".

option

one of "gsadf"/"sadf" (PWY/PSY dating against cv's critical values) or "svadf" (Sarkar & Wells 2026's SV-ADF asymmetric-threshold dating – radf()'s own badf compared against two closed-form, sample-size-only thresholds, log(t)/10 for origination and log(t)/2 for collapse; no cv needed). See Caveats.

nonrejected

logical. Whether to apply datestamping technique to the series that were not able to reject the Null hypothesis. Ignored when option = "svadf".

Value

Return a table with the following columns:

  • Start:

  • Peak:

  • End:

  • Duration:

  • Signal:

  • Ongoing:

Returns a list containing the estimated origination and termination dates of episodes of explosive behaviour and the corresponding duration.

Details

Datestamp also stores a vector whose elements take the value of 1 when there is a period of explosive behaviour and 0 otherwise. This output can serve as a dummy variable for the occurrence of exuberance.

Caveats

option = "svadf": [Experimental] Sarkar & Wells (2026) is a non-peer-reviewed preprint, a different bar than every other source this package implements. The same note is emitted as a message when called with this option. Detects at most one origination/collapse pair per series (the paper's own procedure), not every recurring episode the way "gsadf"/"sadf" do.

References

Phillips, P. C. B., Shi, S., & Yu, J. (2015). Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500. International Economic Review, 56(4), 1043-1078.

Sarkar, A., & Wells, M. T. (2026). Is there an AI bubble? Robust date-stamping for periods of exuberance. arXiv:2604.12062.

Examples


rsim_data <- radf(sim_data)

ds_data <- datestamp(rsim_data)
#> Using `radf_crit` for `cv`.
ds_data
#> 
#> ── Datestamp (min_duration = 0) ───────────────────────────────── Monte Carlo ──
#> 
#> psy1 :
#>   Start Peak End Duration   Signal Ongoing
#> 1    44   48  56       12 positive   FALSE
#> 
#> psy2 :
#>   Start Peak End Duration   Signal Ongoing
#> 1    22   40  41       19 positive   FALSE
#> 2    62   70  71        9 positive   FALSE
#> 
#> evans :
#>   Start Peak End Duration   Signal Ongoing
#> 1    20   20  21        1 positive   FALSE
#> 2    44   44  45        1 positive   FALSE
#> 3    66   67  68        2 positive   FALSE
#> 
#> blan :
#>   Start Peak End Duration   Signal Ongoing
#> 1    34   36  37        3 positive   FALSE
#> 2    84   86  87        3 positive   FALSE
#> 

# Choose minimum window
datestamp(rsim_data, min_duration = psy_ds(nrow(sim_data)))
#> Using `radf_crit` for `cv`.
#> 
#> ── Datestamp (min_duration = 5) ───────────────────────────────── Monte Carlo ──
#> 
#> psy1 :
#>   Start Peak End Duration   Signal Ongoing
#> 1    44   48  56       12 positive   FALSE
#> 
#> psy2 :
#>   Start Peak End Duration   Signal Ongoing
#> 1    22   40  41       19 positive   FALSE
#> 2    62   70  71        9 positive   FALSE
#> 

autoplot(ds_data)


# SV-ADF asymmetric-threshold dating (no critical values needed)
datestamp(rsim_data, option = "svadf")
#> Experimental. Sarkar & Wells (2026) is a non-peer-reviewed preprint; see ?datestamp, Caveats section.
#> 
#> ── Datestamp (min_duration = 0) ──────────────── SV-ADF (Sarkar & Wells 2026) ──
#> 
#> ℹ Experimental. Sarkar & Wells (2026) is a non-peer-reviewed preprint; see ?datestamp, Caveats section.
#> 
#> psy1 :
#>   Start Peak End Duration   Signal Ongoing
#> 1    48   48  49        1 positive   FALSE
#> 
#> psy2 :
#>   Start Peak End Duration   Signal Ongoing
#> 1    23   23  24        1 positive   FALSE
#> 
#> evans :
#>   Start Peak End Duration   Signal Ongoing
#> 1    20   20  21        1 positive   FALSE
#> 
#> div :
#>   Start Peak End Duration   Signal Ongoing
#> 1    22   22  23        1 positive   FALSE
#> 
#> blan :
#>   Start Peak End Duration   Signal Ongoing
#> 1    35   36  37        2 positive   FALSE
#>