<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>avishekb9.r-universe.dev</title><link>https://avishekb9.r-universe.dev</link><description>Recent package updates in avishekb9</description><generator>R-universe</generator><image><url>https://github.com/avishekb9.png</url><title>R packages by avishekb9</title><link>https://avishekb9.r-universe.dev</link></image><lastBuildDate>Wed, 03 Jun 2026 02:27:43 GMT</lastBuildDate><item><title>[avishekb9] sochcontagion 0.1.0</title><author>avishekb@iitbbs.ac.in (Avishek Bhandari)</author><description>A spectral theory of financial contagion under
heterogeneous information adaptation, with the estimators and
falsifiable tests it implies. Modelling both the source and the
receiving market as exponential information filters yields a
bi-exponential transmission response whose power spectrum is
the product of two Lorentzians; the slower market supplies the
binding spectral corner. Projected onto a maximal-overlap
discrete wavelet basis (Percival and Walden, 2000,
ISBN:9780521685085) this gives a closed-form
transfer-entropy-by-scale profile and three predictions
(Scale-Ordered Contagion): scale ordering by adaptation speed,
shape symmetry across direction, and magnitude asymmetry. The
package provides the closed-form spectrum and scale power, a
profile-matching estimator that recovers adaptation rates and
endogenises the fast/slow classification, the wavelet-quantile
directional-gain measure built from the transfer-entropy
estimator of Schreiber (2000) &lt;doi:10.1103/PhysRevLett.85.461&gt;
with quantile conditioning (Koenker and Bassett, 1978)
&lt;doi:10.2307/1913643&gt; and the quantile goodness-of-fit of
Koenker and Machado (1999)
&lt;doi:10.1080/01621459.1999.10473882&gt;, and the three tests with
phase-randomised surrogate (Theiler, Eubank, Longtin,
Galdrikian and Farmer, 1992) &lt;doi:10.1016/0167-2789(92)90102-S&gt;
and stationary block-bootstrap (Politis and Romano, 1994)
&lt;doi:10.1080/01621459.1994.10476870&gt; nulls. Bundled G20 equity
returns and replication scripts reproduce the headline results;
the package is general-purpose and accommodates user-supplied
returns.</description><link>https://github.com/r-universe/avishekb9/actions/runs/26874322885</link><pubDate>Wed, 03 Jun 2026 02:27:43 GMT</pubDate><r:package>sochcontagion</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://avishekb9.r-universe.dev</r:repository><r:upstream>https://github.com/avishekb9/sochcontagion</r:upstream><r:article><r:source>replication.Rmd</r:source><r:filename>replication.html</r:filename><r:title>Reproducing the G20 results</r:title><r:created>2026-06-02 18:48:14</r:created><r:modified>2026-06-02 18:48:14</r:modified></r:article><r:article><r:source>methodology.Rmd</r:source><r:filename>methodology.html</r:filename><r:title>The Scale-Ordered Contagion methodology</r:title><r:created>2026-06-02 18:48:14</r:created><r:modified>2026-06-02 18:48:14</r:modified></r:article></item><item><title>[avishekb9] contagionchannels 0.1.3</title><author>avishekb@iitbbs.ac.in (Avishek Bhandari)</author><description>Implementation of a two-stage framework for the joint
detection-and-attribution of cross-border financial contagion.
Stage one detects directional information flows between equity
markets via Wavelet-Quantile Transfer Entropy, combining
maximal-overlap discrete wavelet decomposition (Percival and
Walden, 2000, ISBN:9780521685085) with the transfer-entropy
estimator of Schreiber (2000) &lt;doi:10.1103/PhysRevLett.85.461&gt;
and quantile conditioning following Han, Linton, Oka and Whang
(2016) &lt;doi:10.1016/j.jeconom.2016.03.001&gt;. Stage two
attributes each significant directional link to one of five
mutually exclusive transmission channels (Trade, Financial,
Geopolitical, Behavioural, Monetary Policy) through a
multi-method structural identification architecture combining
instrumental-variables two-stage least squares with
channel-specific external instruments (Stock and Watson, 2018)
&lt;doi:10.1111/ecoj.12593&gt;, LASSO-based instrument selection
(Belloni, Chernozhukov and Hansen, 2014)
&lt;doi:10.1093/restud/rdt044&gt;, local projections (Jorda, 2005)
&lt;doi:10.1257/0002828053828518&gt;, heteroskedasticity-based
identification (Rigobon, 2003)
&lt;doi:10.1162/003465303772815727&gt;, and the Cinelli-Hazlett
(2020) &lt;doi:10.1111/rssb.12348&gt; robustness-value sensitivity
bound. Bundled datasets and replication scripts reproduce the
headline findings of Bhandari, Parida and Sahu (2026)
&lt;doi:10.48550/arXiv.2604.26546&gt;; the package is general-purpose
and accommodates user-supplied returns and channel proxies.</description><link>https://github.com/r-universe/avishekb9/actions/runs/25635584370</link><pubDate>Sun, 10 May 2026 17:05:40 GMT</pubDate><r:package>contagionchannels</r:package><r:version>0.1.3</r:version><r:status>success</r:status><r:repository>https://avishekb9.r-universe.dev</r:repository><r:upstream>https://github.com/avishekb9/contagionchannels</r:upstream><r:article><r:source>methodology.Rmd</r:source><r:filename>methodology.html</r:filename><r:title>Methodology Guide</r:title><r:created>2026-04-29 12:23:36</r:created><r:modified>2026-04-29 12:44:03</r:modified></r:article><r:article><r:source>replication.Rmd</r:source><r:filename>replication.html</r:filename><r:title>Replicating the Paper Results</r:title><r:created>2026-04-29 12:23:36</r:created><r:modified>2026-04-29 12:23:36</r:modified></r:article><r:article><r:source>custom_data.Rmd</r:source><r:filename>custom_data.html</r:filename><r:title>Using Custom Datasets</r:title><r:created>2026-04-29 12:23:36</r:created><r:modified>2026-04-29 12:23:36</r:modified></r:article></item><item><title>[cran] contagionchannels 0.1.3</title><author>avishekb@iitbbs.ac.in (Avishek Bhandari)</author><description>Implementation of a two-stage framework for the joint
detection-and-attribution of cross-border financial contagion.
Stage one detects directional information flows between equity
markets via Wavelet-Quantile Transfer Entropy, combining
maximal-overlap discrete wavelet decomposition (Percival and
Walden, 2000, ISBN:9780521685085) with the transfer-entropy
estimator of Schreiber (2000) &lt;doi:10.1103/PhysRevLett.85.461&gt;
and quantile conditioning following Han, Linton, Oka and Whang
(2016) &lt;doi:10.1016/j.jeconom.2016.03.001&gt;. Stage two
attributes each significant directional link to one of five
mutually exclusive transmission channels (Trade, Financial,
Geopolitical, Behavioural, Monetary Policy) through a
multi-method structural identification architecture combining
instrumental-variables two-stage least squares with
channel-specific external instruments (Stock and Watson, 2018)
&lt;doi:10.1111/ecoj.12593&gt;, LASSO-based instrument selection
(Belloni, Chernozhukov and Hansen, 2014)
&lt;doi:10.1093/restud/rdt044&gt;, local projections (Jorda, 2005)
&lt;doi:10.1257/0002828053828518&gt;, heteroskedasticity-based
identification (Rigobon, 2003)
&lt;doi:10.1162/003465303772815727&gt;, and the Cinelli-Hazlett
(2020) &lt;doi:10.1111/rssb.12348&gt; robustness-value sensitivity
bound. Bundled datasets and replication scripts reproduce the
headline findings of Bhandari, Parida and Sahu (2026)
&lt;doi:10.48550/arXiv.2604.26546&gt;; the package is general-purpose
and accommodates user-supplied returns and channel proxies.</description><link>https://github.com/r-universe/cran/actions/runs/25569002309</link><pubDate>Fri, 08 May 2026 15:55:36 GMT</pubDate><r:package>contagionchannels</r:package><r:version>0.1.3</r:version><r:status>success</r:status><r:repository>https://cran.r-universe.dev</r:repository><r:upstream>https://github.com/cran/contagionchannels</r:upstream><r:article><r:source>methodology.Rmd</r:source><r:filename>methodology.html</r:filename><r:title>Methodology Guide</r:title><r:created>2026-05-08 15:55:36</r:created><r:modified>2026-05-08 15:55:36</r:modified></r:article><r:article><r:source>replication.Rmd</r:source><r:filename>replication.html</r:filename><r:title>Replicating the Paper Results</r:title><r:created>2026-05-08 15:55:36</r:created><r:modified>2026-05-08 15:55:36</r:modified></r:article><r:article><r:source>custom_data.Rmd</r:source><r:filename>custom_data.html</r:filename><r:title>Using Custom Datasets</r:title><r:created>2026-05-08 15:55:36</r:created><r:modified>2026-05-08 15:55:36</r:modified></r:article></item><item><title>[avishekb9] ManyIVsNets 0.1.1</title><author>bavisek@gmail.com (Avishek Bhandari)</author><description>Comprehensive toolkit for Environmental Phillips Curve
analysis featuring multidimensional instrumental variable
creation, transfer entropy causal discovery, network analysis,
and state-of-the-art econometric methods. Implements
geographic, technological, migration, geopolitical, financial,
and natural risk instruments with robust diagnostics and
visualization. Provides 24 different instrumental variable
approaches with empirical validation. Methods based on Phillips
(1958) &lt;doi:10.1111/j.1468-0335.1958.tb00003.x&gt;, transfer
entropy by Schreiber (2000) &lt;doi:10.1103/PhysRevLett.85.461&gt;,
and weak instrument tests by Stock and Yogo (2005)
&lt;doi:10.1017/CBO9780511614491.006&gt;.</description><link>https://github.com/r-universe/avishekb9/actions/runs/26150613385</link><pubDate>Wed, 18 Jun 2025 11:00:34 GMT</pubDate><r:package>ManyIVsNets</r:package><r:version>0.1.1</r:version><r:status>success</r:status><r:repository>https://avishekb9.r-universe.dev</r:repository><r:upstream>https://github.com/avishekb9/manyivsnets</r:upstream><r:article><r:source>instrument_creation.Rmd</r:source><r:filename>instrument_creation.html</r:filename><r:title>Creating Multidimensional Instruments from Scratch</r:title><r:created>2025-06-12 09:00:35</r:created><r:modified>2025-06-12 09:00:35</r:modified></r:article><r:article><r:source>introduction.Rmd</r:source><r:filename>introduction.html</r:filename><r:title>Introduction to ManyIVsNets</r:title><r:created>2025-06-12 09:00:35</r:created><r:modified>2025-06-12 09:00:35</r:modified></r:article><r:article><r:source>network_visualization.Rmd</r:source><r:filename>network_visualization.html</r:filename><r:title>Network Analysis and Visualization Guide</r:title><r:created>2025-06-12 09:00:35</r:created><r:modified>2025-06-12 09:00:35</r:modified></r:article><r:article><r:source>transfer_entropy_analysis.Rmd</r:source><r:filename>transfer_entropy_analysis.html</r:filename><r:title>Transfer Entropy Analysis and Causal Discovery</r:title><r:created>2025-06-12 09:00:35</r:created><r:modified>2025-06-12 09:00:35</r:modified></r:article></item></channel></rss>