pyexuber

pyexuber detects explosive behaviour (bubbles) in time series. It runs the recursive right-tailed unit root tests of Phillips, Shi and Yu (2015): ADF, SADF, GSADF and the backward SADF (BSADF) sequence. A series is explosive when it grows faster than a random walk, and each of these tests asks whether the data contain a stretch of such growth.

This is the Python counterpart of the R package exuber. Both packages compute the statistic with the same C++ core, exubercore, so they give identical numbers for the same input.

The package is distributed as pyexuber and imported as exuber.

pip install pyexuber

Usage

import exuber
from exuber.sim import sim_psy1

y = sim_psy1(200, seed=1)                 # single-bubble DGP
res = exuber.radf(y)                      # ADF / SADF / GSADF + BSADF sequence
cv = exuber.radf_crit(n=200)              # precomputed Monte Carlo critical values
exuber.datestamp(res, cv)                 # {'series1': [Episode(start=..., peak=..., end=...)]}

radf() accepts a numpy array, a 1-D sequence, or any object with a .to_numpy() method, such as a pandas or polars DataFrame (neither is a dependency). Column names become series names. A multi-column input also runs the panel version of the tests (bsadf_panel, gsadf_panel).

What the package contains


`radf(data, minw=None, lag=0)`	recursive ADF/SADF/GSADF/BSADF statistics (C++)
`radf_crit(n, lag=0)`	precomputed Monte Carlo critical values from the shared store that the R package also reads; fetched once and cached on disk
`radf_mc_cv` / `radf_mc_distr`	Monte Carlo critical values and distributions, simulated locally
`radf_wb_cv` / `radf_wb_distr`	wild-bootstrap critical values (Harvey, Leybourne, Sollis & Taylor 2016)
`datestamp(result, cv, ...)`	start, peak, end and duration of each explosive episode
`sim_psy1`, `sim_psy2`, `sim_ps1`, `sim_ps2`, `sim_blan`, `sim_evans`, `sim_div`	bubble DGP simulators
`psy_minw`, `psy_ds`	the PSY default minimum window and minimum duration rules

Beyond this core, the package ports many methods from exuber and the wider literature: other bootstrap variants (radf_wb_ps_cv, radf_sb_cv), several dating and monitoring procedures, and diagnostics(), summary() and tidy(). The docstring of exuber/__init__.py lists them all and says what is deferred.

Notes

Critical values. radf_crit() covers lags 0 to 4 and sample sizes up to 4000. For a combination that has not been simulated it returns None, and you can use radf_mc_cv instead. The store is described at exuber.kvasilopoulos.com.
Reproducibility. The simulators and bootstraps use numpy's Generator and not R's random number generator. A given seed reproduces the same draws across Python runs, but not the draws of the R function with the same name.
Numerics. The statistic is built by sequential recursive updates, so for lag > 0 the result may differ between compilers at about 1e-12. The tests use a tolerance of 1e-9 there. With lag == 0 the result matches R to 1e-12.

Building from source

Wheels are published for Linux x86_64, macOS (arm64 and x86_64) and Windows x86_64. Building from the source distribution needs a C++17 compiler, CMake 3.16 or later, and a system Armadillo installation with BLAS and LAPACK. Install it with apt install libarmadillo-dev, brew install armadillo, or vcpkg install armadillo on Windows with MSVC. CMake fetches exubercore at a pinned tag during the build.

uv sync --dev
uv run pytest

License

GPL-3.0-or-later, the same as exuber.

Metadata

Release files for pyexuber 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyexuber 0.1.0
File	Size	Uploaded
pyexuber-0.1.0.tar.gz	155.9 kB	Oct 5, 2026	Details

Built distributions (wheels)

Table of built distributions (wheels) for pyexuber 0.1.0
File	Interpreter	ABI	Platform	Reset
pyexuber-0.1.0-cp313-cp313-win_amd64.whl 6.1 MB Oct 5, 2026	CPython 3.13	CPython 3.13	Windows x86-64	Details
pyexuber-0.1.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 43.2 MB Oct 5, 2026	CPython 3.13	CPython 3.13	Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64	Details
pyexuber-0.1.0-cp313-cp313-macosx_15_0_x86_64.whl 15.0 MB Oct 5, 2026	CPython 3.13	CPython 3.13	macOS 15.0+ x86-64	Details
pyexuber-0.1.0-cp313-cp313-macosx_15_0_arm64.whl 10.9 MB Oct 5, 2026	CPython 3.13	CPython 3.13	macOS 15.0+ ARM64	Details
pyexuber-0.1.0-cp312-cp312-win_amd64.whl 6.1 MB Oct 5, 2026	CPython 3.12	CPython 3.12	Windows x86-64	Details
pyexuber-0.1.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 43.2 MB Oct 5, 2026	CPython 3.12	CPython 3.12	Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64	Details
pyexuber-0.1.0-cp312-cp312-macosx_15_0_x86_64.whl 15.0 MB Oct 5, 2026	CPython 3.12	CPython 3.12	macOS 15.0+ x86-64	Details
pyexuber-0.1.0-cp312-cp312-macosx_15_0_arm64.whl 10.9 MB Oct 5, 2026	CPython 3.12	CPython 3.12	macOS 15.0+ ARM64	Details
pyexuber-0.1.0-cp311-cp311-win_amd64.whl 6.1 MB Oct 5, 2026	CPython 3.11	CPython 3.11	Windows x86-64	Details
pyexuber-0.1.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 43.2 MB Oct 5, 2026	CPython 3.11	CPython 3.11	Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64	Details
pyexuber-0.1.0-cp311-cp311-macosx_15_0_x86_64.whl 15.0 MB Oct 5, 2026	CPython 3.11	CPython 3.11	macOS 15.0+ x86-64	Details
pyexuber-0.1.0-cp311-cp311-macosx_15_0_arm64.whl 10.9 MB Oct 5, 2026	CPython 3.11	CPython 3.11	macOS 15.0+ ARM64	Details
pyexuber-0.1.0-cp310-cp310-win_amd64.whl 6.1 MB Oct 5, 2026	CPython 3.10	CPython 3.10	Windows x86-64	Details
pyexuber-0.1.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl 43.2 MB Oct 5, 2026	CPython 3.10	CPython 3.10	Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64	Details
pyexuber-0.1.0-cp310-cp310-macosx_15_0_x86_64.whl 15.0 MB Oct 5, 2026	CPython 3.10	CPython 3.10	macOS 15.0+ x86-64	Details
pyexuber-0.1.0-cp310-cp310-macosx_15_0_arm64.whl 10.9 MB Oct 5, 2026	CPython 3.10	CPython 3.10	macOS 15.0+ ARM64	Details

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Release files / pyexuber-0.1.0-cp311-cp311-macosx_15_0_arm64.whl

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Publishing commit: github.com/kvasilopoulos/pyexuber/tree/89fab15701446701536eea84675448b1a190383d

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Release files / pyexuber-0.1.0-cp310-cp310-macosx_15_0_arm64.whl

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Uploaded via	`twine/7.0.0 CPython/3.13.14`

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Publishing repository: github.com/kvasilopoulos/pyexuber
Publishing commit: github.com/kvasilopoulos/pyexuber/tree/89fab15701446701536eea84675448b1a190383d

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This release

0.1.0 This release

Oct 5, 2026 17 release files

pyexuber 0.1.0

pyexuber

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