From 722876d6ce1da6b5dae23b1be52e5f544c1754d4 Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 16 Oct 2026 17:24:34 +0000
Subject: [PATCH 1/4] Paper: author's full name and BRAC University affiliation

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HTqzkhjyuhZZun8Az1tW6C
---
 docs/working_paper/README.md                              | 2 +-
 docs/working_paper/detection_timing_backtest_2026-07.html | 2 +-
 docs/working_paper/detection_timing_backtest_2026-07.md   | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/working_paper/README.md b/docs/working_paper/README.md
index 8f3faf4..76c0ba3 100644
--- a/docs/working_paper/README.md
+++ b/docs/working_paper/README.md
@@ -1,7 +1,7 @@
 # Working Paper
 
 **Detection-Timing Backtest of a Deterministic Downside-Risk Screen Across Three Modern Financial Crises**
-Zarif Latif. Revision 2, October 2026 (first version July 2026).
+Md. Zarif Latif (BRAC University). Revision 2.1, October 2026 (first version July 2026).
 
 Revision 2's headline finding: the pipeline flagged all 9 affected names before their formal resolution dates, but **no first flag came before the first headline reporting the stock already falling** (Section 4.5). The paper presents the system as fast, auditable triage, not anticipation.
 
diff --git a/docs/working_paper/detection_timing_backtest_2026-07.html b/docs/working_paper/detection_timing_backtest_2026-07.html
index 1163199..77ba59d 100644
--- a/docs/working_paper/detection_timing_backtest_2026-07.html
+++ b/docs/working_paper/detection_timing_backtest_2026-07.html
@@ -39,7 +39,7 @@
 <body>
 <h1 id="detection-timing-backtest-of-a-deterministic-downside-risk-screen-across-three-modern-financial-crises">Detection-Timing Backtest of a Deterministic Downside-Risk Screen Across Three Modern Financial Crises</h1>
 <p><strong>A working paper. Revision 2.1, October 2026 (first version July 2026).</strong></p>
-<p><strong>Author:</strong> Zarif Latif, independent researcher · zarif@aetheriusresearch.tech</p>
+<p><strong>Author:</strong> Md. Zarif Latif, Undergraduate Student, BRAC University, Dhaka, Bangladesh · zarif@aetheriusresearch.tech</p>
 <p><strong>Keywords:</strong> risk screening, event study, entity resolution, textual analysis, GDELT, SEC EDGAR, bank failures, backtesting</p>
 <p><strong>JEL codes:</strong> G14, G17, G21</p>
 <blockquote>
diff --git a/docs/working_paper/detection_timing_backtest_2026-07.md b/docs/working_paper/detection_timing_backtest_2026-07.md
index 7b428ad..efeb2e2 100644
--- a/docs/working_paper/detection_timing_backtest_2026-07.md
+++ b/docs/working_paper/detection_timing_backtest_2026-07.md
@@ -2,7 +2,7 @@
 
 **A working paper. Revision 2.1, October 2026 (first version July 2026).**
 
-**Author:** Zarif Latif, independent researcher · zarif@aetheriusresearch.tech
+**Author:** Md. Zarif Latif, Undergraduate Student, BRAC University, Dhaka, Bangladesh · zarif@aetheriusresearch.tech
 
 **Keywords:** risk screening, event study, entity resolution, textual analysis, GDELT, SEC EDGAR, bank failures, backtesting
 

From 57add0bf49ba1a6cace4e465e1364ec41b1ac3cc Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 16 Oct 2026 17:30:13 +0000
Subject: [PATCH 2/4] Paper: SSRN-ready typeset PDF, BRAC email, no revision
 history

- Author email md.zarif.latif@g.bracu.ac.bd; title block, abstract,
  keywords and JEL codes laid out as a first-page academic header.
- Revision notes removed: this is the paper's first formal release. One
  sentence in 4.6 still states that earlier project materials claimed
  '0 false positives on 3 controls' and that the claim is withdrawn.
- render_working_paper.py --pdf typesets with WeasyPrint: Letter,
  1-inch margins, Times-style serif, running head, page numbers,
  booktabs-style tables kept whole, no hyphenation in tables or code,
  dates unbroken, references with hanging indents. 11 pages.
- The PDF is committed next to the Markdown and HTML.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HTqzkhjyuhZZun8Az1tW6C
---
 docs/working_paper/README.md                  |   8 +-
 .../detection_timing_backtest_2026-07.html    |  25 ++--
 .../detection_timing_backtest_2026-07.md      |  28 ++--
 scripts/render_working_paper.py               | 132 +++++++++++++++++-
 4 files changed, 158 insertions(+), 35 deletions(-)

diff --git a/docs/working_paper/README.md b/docs/working_paper/README.md
index 76c0ba3..192a619 100644
--- a/docs/working_paper/README.md
+++ b/docs/working_paper/README.md
@@ -1,19 +1,21 @@
 # Working Paper
 
 **Detection-Timing Backtest of a Deterministic Downside-Risk Screen Across Three Modern Financial Crises**
-Md. Zarif Latif (BRAC University). Revision 2.1, October 2026 (first version July 2026).
+Md. Zarif Latif (BRAC University). Working paper, October 2026.
 
-Revision 2's headline finding: the pipeline flagged all 9 affected names before their formal resolution dates, but **no first flag came before the first headline reporting the stock already falling** (Section 4.5). The paper presents the system as fast, auditable triage, not anticipation.
+Headline finding: the pipeline flagged all 9 affected names before their formal resolution dates, but **no first flag came before the first headline reporting the stock already falling** (Section 4.5). The paper presents the system as fast, auditable triage, not anticipation.
 
 ## Files
 
 - `detection_timing_backtest_2026-07.md` — the paper. Renders on GitHub, Substack, arXiv-style preprint sites. **This is the primary artifact.**
+- `detection_timing_backtest_2026-07.pdf` — the typeset PDF (the version posted on SSRN).
 - `detection_timing_backtest_2026-07.html` — self-contained HTML. Open in any browser. Save-as-PDF via browser print dialog for a shareable attachment.
 
 ## Rebuild the HTML
 
 ```bash
-python scripts/render_working_paper.py
+python scripts/render_working_paper.py          # HTML only
+python scripts/render_working_paper.py --pdf    # HTML + typeset PDF (WeasyPrint)
 ```
 
 The HTML has all CSS inlined and no external assets, so a single file emailed / posted anywhere renders correctly on any modern browser.
diff --git a/docs/working_paper/detection_timing_backtest_2026-07.html b/docs/working_paper/detection_timing_backtest_2026-07.html
index 77ba59d..0cdfd3d 100644
--- a/docs/working_paper/detection_timing_backtest_2026-07.html
+++ b/docs/working_paper/detection_timing_backtest_2026-07.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
 <meta charset="utf-8">
-<title>Detection-Timing Backtest of a Systematic Downside-Risk Screen Across Three Modern Financial Crises</title>
+<title>Detection-Timing Backtest of a Deterministic Downside-Risk Screen Across Three Modern Financial Crises</title>
 <style>
 :root { color-scheme: light dark; }
 body {
@@ -38,20 +38,17 @@
 </head>
 <body>
 <h1 id="detection-timing-backtest-of-a-deterministic-downside-risk-screen-across-three-modern-financial-crises">Detection-Timing Backtest of a Deterministic Downside-Risk Screen Across Three Modern Financial Crises</h1>
-<p><strong>A working paper. Revision 2.1, October 2026 (first version July 2026).</strong></p>
-<p><strong>Author:</strong> Md. Zarif Latif, Undergraduate Student, BRAC University, Dhaka, Bangladesh · zarif@aetheriusresearch.tech</p>
-<p><strong>Keywords:</strong> risk screening, event study, entity resolution, textual analysis, GDELT, SEC EDGAR, bank failures, backtesting</p>
-<p><strong>JEL codes:</strong> G14, G17, G21</p>
-<blockquote>
-<p><strong>What changed in Revision 2.</strong> Revision 1 reported that the pipeline flagged all nine affected names "before the realized event date," with a median lead of about 2.5 days. That is true, but the realized event date was the <em>formal resolution</em> (receivership, insolvency filing, Chapter 11), not the market's reaction. Revision 2 adds a test of timing against the first headline reporting each stock already falling (Section 4.5). Measured that way, <strong>no first flag came before the market reaction.</strong> Revision 2 also adds confidence intervals, states the hindsight selection of events and watchlists, documents two known false-positive classes, removes commercial framing, and describes a pre-registered live forward test (Section 8). Every number in this revision is reproduced by pinned tests.</p>
-<p><strong>What changed in Revision 2.1.</strong> A pre-publication check found that <strong>no control name appears in any of the three corpora</strong>, so the "0 false positives on controls" result was never actually tested. Text in Revisions 1 and 2 describing control headlines was wrong and has been removed. Section 4.6 explains what happened. Revision 2.1 also adds related work and references, and discloses that the Section 4.5 price-reaction pattern was written after the headlines had been read.</p>
-</blockquote>
-<hr />
+<p><strong>Md. Zarif Latif</strong><br />
+Undergraduate Student, BRAC University, Dhaka, Bangladesh<br />
+md.zarif.latif@g.bracu.ac.bd</p>
+<p>Working paper · October 2026</p>
 <h2 id="abstract">Abstract</h2>
 <p>We replay a deterministic entity-mapping and severity-scoring pipeline against real news headlines from three well-studied financial crises: the March 2023 U.S. regional-bank contagion, the June 2020 Wirecard AG accounting fraud and the November 2022 FTX collapse. For each affected name we report detection timing and how it compares with the market's own reaction.</p>
 <p>On 161 archived observations from GDELT DOC 2.0, the pipeline flagged <strong>all 9 affected names</strong> at "elevated" or "high" severity before each name's formal resolution date, with a median lead of 2.48 days. With only nine names, the 95% confidence interval for recall is 66–100%. The study's three control names never appear in the corpus, so it provides <strong>no evidence about false positives</strong>.</p>
 <p>The more important finding is about timing. In all 9 detections, the first flag arrived <strong>at the same time as, not before,</strong> the first headline reporting that the stock was already falling. In 8 of 9 it <em>was</em> that headline. The pipeline is therefore evidence of fast, auditable <strong>triage</strong> of a market reaction already underway. It is not evidence of anticipating the market. We describe the pipeline, the corpus and the ground truth, discuss the limitations, and describe a pre-registered live forward test started on 2026-10-16. All code and data are Apache-2.0 licensed and reproducible.</p>
 <p><strong>This is detection-timing evidence on frozen historical windows. It is not a return forecast, a trading signal, or a causal claim.</strong></p>
+<p><strong>Keywords:</strong> risk screening, event study, entity resolution, textual analysis, GDELT, SEC EDGAR, bank failures, backtesting</p>
+<p><strong>JEL codes:</strong> G14, G17, G21</p>
 <hr />
 <h2 id="1-motivation">1. Motivation</h2>
 <p>Concentrated public-equity books, such as those of search funds, small family offices, litigation-finance analysts and small credit shops, carry large single-name risk. Professional surveillance products are priced and configured for large institutional teams.</p>
@@ -89,7 +86,7 @@ <h3 id="23-severity-scoring">2.3 Severity scoring</h3>
 </ul>
 <p><code>severity_label()</code> bins risk into <code>low</code>, <code>moderate</code>, <code>elevated</code> or <code>high</code>. Every weight is a constant, and there are no learned parameters.</p>
 <h3 id="24-adverse-language-gate">2.4 Adverse-language gate</h3>
-<p><code>adverse_severity(raw_text)</code> (same module) counts matches against a fixed list of about 40 downside terms (<code>loss</code>, <code>plunge</code>, <code>withdrawals</code>, <code>deposit run</code>, <code>receivership</code>, <code>collapse</code>, <code>funding pressure</code>, <code>distress</code>, <code>insolven…</code>, …) and maps the count to an event-severity score. An observation is a <strong>shippable flag</strong> only when its severity label is <code>elevated</code> or <code>high</code> <strong>and</strong> at least one adverse term is present. Unit tests show the gate holding a benign direct mention below shippable severity (for example, "Microsoft expands Copilot across product suite"). The backtest corpora contain no such case for the controls (Section 4.6). Since Revision 2, the live API, the backtest and the forward test all import this single implementation.</p>
+<p><code>adverse_severity(raw_text)</code> (same module) counts matches against a fixed list of about 40 downside terms (<code>loss</code>, <code>plunge</code>, <code>withdrawals</code>, <code>deposit run</code>, <code>receivership</code>, <code>collapse</code>, <code>funding pressure</code>, <code>distress</code>, <code>insolven…</code>, …) and maps the count to an event-severity score. An observation is a <strong>shippable flag</strong> only when its severity label is <code>elevated</code> or <code>high</code> <strong>and</strong> at least one adverse term is present. Unit tests show the gate holding a benign direct mention below shippable severity (for example, "Microsoft expands Copilot across product suite"). The backtest corpora contain no such case for the controls (Section 4.6). The live API, the backtest and the forward test all import this single implementation.</p>
 <h3 id="25-backtest-harness">2.5 Backtest harness</h3>
 <p><code>simulations/backtest/run_backtest.py</code> replays each event's <code>observations.jsonl</code> in chronological order against its <code>watchlist.json</code> and <code>ground_truth.json</code>, records the first shippable flag per name, and computes:</p>
 <ul>
@@ -371,10 +368,10 @@ <h3 id="45-timing-relative-to-the-market-reaction">4.5 Timing relative to the ma
 </tbody>
 </table>
 <p><strong>No first flag came before the market reaction.</strong> The pipeline flagged each name at the moment the press reported its shares falling. This is expected given how it works: adverse-language scoring of headlines fires most strongly on headlines <em>about</em> a sell-off.</p>
-<p>That is still useful for a small team. Out of hundreds of headlines, the names that need attention today were surfaced within the same news cycle, with an auditable reason. But it is <strong>triage, not anticipation</strong>, and Revision 1's framing of "lead time" overstated what the evidence supports.</p>
+<p>That is still useful for a small team. Out of hundreds of headlines, the names that need attention today were surfaced within the same news cycle, with an auditable reason. But it is <strong>triage, not anticipation</strong>, and lead time measured to formal resolution overstates what the evidence supports.</p>
 <h3 id="46-the-control-test-was-not-exercised">4.6 The control test was not exercised</h3>
 <p>Each fixture includes one control name (MSFT twice, DTE once) that the pipeline should not flag. None did, but none could have: <strong>no observation in any corpus maps to a control name.</strong> The fixture builder did query GDELT for each control ("Microsoft Corporation", "Deutsche Telekom"), and GDELT returned articles. GDELT matches article bodies, but the pipeline stores and scores headlines only, and none of those headlines names the control. <code>market_reaction_check.py</code> prints this coverage, and a test (<code>test_controls_never_appear_in_the_frozen_corpora</code>) pins it so the paper must be updated if a fixture is ever rebuilt.</p>
-<p>Revisions 1 and 2 reported "0 false positives on 3 controls" as evidence of specificity, and described control headlines that do not exist in the data. Both were errors. This study therefore says nothing about how often the screen fires on companies that turned out fine. The same fact makes the 100% mapping precision uninformative. Measuring false positives is the purpose of the forward test (Section 8).</p>
+<p>Earlier project materials (the repository README and website) presented "0 false positives on 3 controls" as evidence of specificity; that claim is withdrawn. This study therefore says nothing about how often the screen fires on companies that turned out fine. The same fact makes the 100% mapping precision uninformative. Measuring false positives is the purpose of the forward test (Section 8).</p>
 <hr />
 <h2 id="5-limitations">5. Limitations</h2>
 <h3 id="51-what-this-measures-and-what-it-does-not">5.1 What this measures and what it does not</h3>
@@ -533,7 +530,7 @@ <h2 id="appendix-c-primary-sources">Appendix C — Primary sources</h2>
 <h2 id="appendix-d-reproducibility">Appendix D — Reproducibility</h2>
 <ul>
 <li><strong>License:</strong> Apache-2.0.</li>
-<li><strong>Tests:</strong> the full suite (122 tests at Revision 2.1) pins the backtest metrics, the Section 4.5 timing result, the Section 4.6 control coverage, and the parity between live and backtest scoring.</li>
+<li><strong>Tests:</strong> the full suite (122 tests at the time of writing) pins the backtest metrics, the Section 4.5 timing result, the Section 4.6 control coverage, and the parity between live and backtest scoring.</li>
 <li><strong>Determinism:</strong> scoring weights are constants with no learned parameters, and reruns are bit-identical.</li>
 <li><strong>Rebuild:</strong> corpora can be regenerated from GDELT DOC 2.0 with <code>simulations/backtest/build_fixture.py</code>.</li>
 </ul>
diff --git a/docs/working_paper/detection_timing_backtest_2026-07.md b/docs/working_paper/detection_timing_backtest_2026-07.md
index efeb2e2..1a9a375 100644
--- a/docs/working_paper/detection_timing_backtest_2026-07.md
+++ b/docs/working_paper/detection_timing_backtest_2026-07.md
@@ -1,18 +1,10 @@
 # Detection-Timing Backtest of a Deterministic Downside-Risk Screen Across Three Modern Financial Crises
 
-**A working paper. Revision 2.1, October 2026 (first version July 2026).**
+**Md. Zarif Latif**  
+Undergraduate Student, BRAC University, Dhaka, Bangladesh  
+md.zarif.latif@g.bracu.ac.bd
 
-**Author:** Md. Zarif Latif, Undergraduate Student, BRAC University, Dhaka, Bangladesh · zarif@aetheriusresearch.tech
-
-**Keywords:** risk screening, event study, entity resolution, textual analysis, GDELT, SEC EDGAR, bank failures, backtesting
-
-**JEL codes:** G14, G17, G21
-
-> **What changed in Revision 2.** Revision 1 reported that the pipeline flagged all nine affected names "before the realized event date," with a median lead of about 2.5 days. That is true, but the realized event date was the *formal resolution* (receivership, insolvency filing, Chapter 11), not the market's reaction. Revision 2 adds a test of timing against the first headline reporting each stock already falling (Section 4.5). Measured that way, **no first flag came before the market reaction.** Revision 2 also adds confidence intervals, states the hindsight selection of events and watchlists, documents two known false-positive classes, removes commercial framing, and describes a pre-registered live forward test (Section 8). Every number in this revision is reproduced by pinned tests.
->
-> **What changed in Revision 2.1.** A pre-publication check found that **no control name appears in any of the three corpora**, so the "0 false positives on controls" result was never actually tested. Text in Revisions 1 and 2 describing control headlines was wrong and has been removed. Section 4.6 explains what happened. Revision 2.1 also adds related work and references, and discloses that the Section 4.5 price-reaction pattern was written after the headlines had been read.
-
----
+Working paper · October 2026
 
 ## Abstract
 
@@ -24,6 +16,10 @@ The more important finding is about timing. In all 9 detections, the first flag
 
 **This is detection-timing evidence on frozen historical windows. It is not a return forecast, a trading signal, or a causal claim.**
 
+**Keywords:** risk screening, event study, entity resolution, textual analysis, GDELT, SEC EDGAR, bank failures, backtesting
+
+**JEL codes:** G14, G17, G21
+
 ---
 
 ## 1. Motivation
@@ -76,7 +72,7 @@ Because matching is case-insensitive, a ticker that is also an English word matc
 
 ### 2.4 Adverse-language gate
 
-`adverse_severity(raw_text)` (same module) counts matches against a fixed list of about 40 downside terms (`loss`, `plunge`, `withdrawals`, `deposit run`, `receivership`, `collapse`, `funding pressure`, `distress`, `insolven…`, …) and maps the count to an event-severity score. An observation is a **shippable flag** only when its severity label is `elevated` or `high` **and** at least one adverse term is present. Unit tests show the gate holding a benign direct mention below shippable severity (for example, "Microsoft expands Copilot across product suite"). The backtest corpora contain no such case for the controls (Section 4.6). Since Revision 2, the live API, the backtest and the forward test all import this single implementation.
+`adverse_severity(raw_text)` (same module) counts matches against a fixed list of about 40 downside terms (`loss`, `plunge`, `withdrawals`, `deposit run`, `receivership`, `collapse`, `funding pressure`, `distress`, `insolven…`, …) and maps the count to an event-severity score. An observation is a **shippable flag** only when its severity label is `elevated` or `high` **and** at least one adverse term is present. Unit tests show the gate holding a benign direct mention below shippable severity (for example, "Microsoft expands Copilot across product suite"). The backtest corpora contain no such case for the controls (Section 4.6). The live API, the backtest and the forward test all import this single implementation.
 
 ### 2.5 Backtest harness
 
@@ -181,13 +177,13 @@ The lead times above are measured to the formal resolution date. An investor car
 
 **No first flag came before the market reaction.** The pipeline flagged each name at the moment the press reported its shares falling. This is expected given how it works: adverse-language scoring of headlines fires most strongly on headlines *about* a sell-off.
 
-That is still useful for a small team. Out of hundreds of headlines, the names that need attention today were surfaced within the same news cycle, with an auditable reason. But it is **triage, not anticipation**, and Revision 1's framing of "lead time" overstated what the evidence supports.
+That is still useful for a small team. Out of hundreds of headlines, the names that need attention today were surfaced within the same news cycle, with an auditable reason. But it is **triage, not anticipation**, and lead time measured to formal resolution overstates what the evidence supports.
 
 ### 4.6 The control test was not exercised
 
 Each fixture includes one control name (MSFT twice, DTE once) that the pipeline should not flag. None did, but none could have: **no observation in any corpus maps to a control name.** The fixture builder did query GDELT for each control ("Microsoft Corporation", "Deutsche Telekom"), and GDELT returned articles. GDELT matches article bodies, but the pipeline stores and scores headlines only, and none of those headlines names the control. `market_reaction_check.py` prints this coverage, and a test (`test_controls_never_appear_in_the_frozen_corpora`) pins it so the paper must be updated if a fixture is ever rebuilt.
 
-Revisions 1 and 2 reported "0 false positives on 3 controls" as evidence of specificity, and described control headlines that do not exist in the data. Both were errors. This study therefore says nothing about how often the screen fires on companies that turned out fine. The same fact makes the 100% mapping precision uninformative. Measuring false positives is the purpose of the forward test (Section 8).
+Earlier project materials (the repository README and website) presented "0 false positives on 3 controls" as evidence of specificity; that claim is withdrawn. This study therefore says nothing about how often the screen fires on companies that turned out fine. The same fact makes the 100% mapping precision uninformative. Measuring false positives is the purpose of the forward test (Section 8).
 
 ---
 
@@ -331,7 +327,7 @@ Every news observation also carries its own `source_url`.
 ## Appendix D — Reproducibility
 
 - **License:** Apache-2.0.
-- **Tests:** the full suite (122 tests at Revision 2.1) pins the backtest metrics, the Section 4.5 timing result, the Section 4.6 control coverage, and the parity between live and backtest scoring.
+- **Tests:** the full suite (122 tests at the time of writing) pins the backtest metrics, the Section 4.5 timing result, the Section 4.6 control coverage, and the parity between live and backtest scoring.
 - **Determinism:** scoring weights are constants with no learned parameters, and reruns are bit-identical.
 - **Rebuild:** corpora can be regenerated from GDELT DOC 2.0 with `simulations/backtest/build_fixture.py`.
 
diff --git a/scripts/render_working_paper.py b/scripts/render_working_paper.py
index 7060330..c457e9d 100644
--- a/scripts/render_working_paper.py
+++ b/scripts/render_working_paper.py
@@ -1,7 +1,13 @@
-"""Render the detection-timing backtest working paper to a self-contained HTML.
+"""Render the detection-timing backtest working paper to HTML and a print PDF.
 
 Reads:  docs/working_paper/detection_timing_backtest_2026-07.md
 Writes: docs/working_paper/detection_timing_backtest_2026-07.html
+        docs/working_paper/detection_timing_backtest_2026-07.pdf   (with --pdf)
+
+The PDF is typeset for submission (SSRN): Letter, 1-inch margins, Times-style
+serif, centred title block, abstract on page 1, running header, page numbers,
+tables and headings kept together across page breaks. It needs WeasyPrint
+(already in requirements.txt).
 
 The HTML uses inline CSS and no external dependencies so it can be:
   * opened directly in a browser
@@ -14,13 +20,59 @@
 """
 from __future__ import annotations
 
+import re
 from pathlib import Path
 
 import markdown
+from bs4 import BeautifulSoup
 
 REPO_ROOT = Path(__file__).resolve().parents[1]
 IN_PATH = REPO_ROOT / "docs" / "working_paper" / "detection_timing_backtest_2026-07.md"
 OUT_PATH = REPO_ROOT / "docs" / "working_paper" / "detection_timing_backtest_2026-07.html"
+PDF_PATH = OUT_PATH.with_suffix(".pdf")
+TITLE = "Detection-Timing Backtest of a Deterministic Downside-Risk Screen Across Three Modern Financial Crises"
+RUNNING_HEAD = "Latif \u00b7 Detection-Timing Backtest of a Deterministic Downside-Risk Screen"
+
+PRINT_CSS = """
+@page {
+    size: Letter;
+    margin: 1in 1in 0.9in 1in;
+    @top-center { content: "__RUNNING_HEAD__"; font: italic 8.5pt 'Liberation Serif', serif; color: #555; }
+    @bottom-center { content: counter(page); font: 9pt 'Liberation Serif', serif; color: #333; }
+}
+@page :first { @top-center { content: none; } }
+html { font-family: 'Liberation Serif', 'Times New Roman', serif; font-size: 11pt; color: #111; }
+body { margin: 0; line-height: 1.38; text-align: justify; hyphens: auto; }
+h1 { font-size: 17pt; line-height: 1.22; text-align: center; margin: 0 0 14pt; font-weight: bold; }
+.titleblock p { text-align: center; margin: 0 0 3pt; }
+.titleblock .date { margin-top: 8pt; color: #333; }
+section.abstract { margin: 18pt 0.45in 0; }
+section.abstract h2 { text-align: center; font-size: 11pt; text-transform: uppercase; letter-spacing: 0.08em;
+    border: 0; margin: 0 0 6pt; padding: 0; }
+section.abstract p { font-size: 10pt; line-height: 1.32; margin: 0 0 6pt; }
+h2 { font-size: 12.5pt; margin: 18pt 0 6pt; font-weight: bold; break-after: avoid; }
+h2.first-section { break-before: page; }
+h3 { font-size: 11pt; font-style: italic; font-weight: bold; margin: 12pt 0 4pt; break-after: avoid; }
+p { margin: 0 0 7pt; orphans: 3; widows: 3; }
+ul, ol { margin: 0 0 7pt; padding-left: 18pt; }
+li { margin-bottom: 3pt; }
+hr { display: none; }
+a { color: #1a3d7c; text-decoration: none; }
+code { font-family: 'DejaVu Sans Mono', monospace; font-size: 8.6pt; hyphens: none; }
+pre { font-family: 'DejaVu Sans Mono', monospace; font-size: 8pt; line-height: 1.35; background: #f4f4f2;
+    border: 0.5pt solid #ccc; padding: 6pt 8pt; text-align: left; white-space: pre-wrap; break-inside: avoid; }
+pre code { font-size: 8pt; }
+table { border-collapse: collapse; width: 100%; margin: 6pt 0 10pt; font-size: 8.6pt; line-height: 1.25;
+    text-align: left; hyphens: none; break-inside: avoid; }
+thead { display: table-header-group; }
+th { border-top: 1pt solid #111; border-bottom: 0.6pt solid #111; padding: 3pt 4pt; font-weight: bold; vertical-align: bottom; }
+td { border-bottom: 0.3pt solid #bbb; padding: 3pt 4pt; vertical-align: top; }
+tr:last-child td { border-bottom: 1pt solid #111; }
+.nowrap { white-space: nowrap; }
+section.references { break-inside: avoid; }
+section.references p { padding-left: 18pt; text-indent: -18pt; text-align: left; font-size: 10pt; }
+blockquote { margin: 6pt 18pt; font-size: 10pt; }
+"""
 
 CSS = """
 :root { color-scheme: light dark; }
@@ -66,7 +118,7 @@ def render() -> Path:
         "<!DOCTYPE html>\n"
         "<html lang=\"en\">\n<head>\n"
         "<meta charset=\"utf-8\">\n"
-        "<title>Detection-Timing Backtest of a Systematic Downside-Risk Screen Across Three Modern Financial Crises</title>\n"
+        f"<title>{TITLE}</title>\n"
         f"<style>{CSS}</style>\n"
         "</head>\n<body>\n"
         f"{body_html}\n"
@@ -76,6 +128,82 @@ def render() -> Path:
     return OUT_PATH
 
 
+_DATE_RE = re.compile(r"(\d{4}-\d{2}-\d{2}(?: \d{2}:\d{2}Z)?)")
+
+
+def _print_html(body_html: str) -> str:
+    """Restructure the rendered Markdown for print: title block, abstract box,
+    page break before Section 1, references with hanging indents, and dates in
+    table cells kept on one line."""
+    soup = BeautifulSoup(body_html, "html.parser")
+    h1 = soup.find("h1")
+    abstract = soup.find("h2", id="abstract")
+    # Title block: everything between the title and the Abstract heading.
+    block = soup.new_tag("div", attrs={"class": "titleblock"})
+    node = h1.find_next_sibling()
+    while node is not None and node is not abstract:
+        nxt = node.find_next_sibling()
+        block.append(node.extract())
+        node = nxt
+    paras = block.find_all("p")
+    if paras:
+        paras[-1]["class"] = "date"
+    h1.insert_after(block)
+    # Abstract section: from the Abstract heading to the next h2.
+    section = soup.new_tag("section", attrs={"class": "abstract"})
+    abstract.insert_before(section)
+    node = abstract
+    while node is not None and not (node.name == "h2" and node is not abstract):
+        nxt = node.find_next_sibling()
+        section.append(node.extract())
+        node = nxt
+    if node is not None:
+        node["class"] = "first-section"
+    # References: hanging indents.
+    refs = soup.find("h2", id="references")
+    if refs is not None:
+        rsec = soup.new_tag("section", attrs={"class": "references"})
+        refs.insert_before(rsec)
+        node = refs
+        while node is not None and not (node.name == "h2" and node is not refs):
+            nxt = node.find_next_sibling()
+            rsec.append(node.extract())
+            node = nxt
+    # Dates inside table cells must not break at their hyphens.
+    for cell in soup.find_all(["td", "th"]):
+        for text in list(cell.find_all(string=_DATE_RE)):
+            parts = _DATE_RE.split(str(text))
+            new = []
+            for i, part in enumerate(parts):
+                if i % 2:
+                    span = soup.new_tag("span", attrs={"class": "nowrap"})
+                    span.string = part
+                    new.append(span)
+                elif part:
+                    new.append(part)
+            text.replace_with(*new)
+    return str(soup)
+
+
+def render_pdf() -> Path:
+    from weasyprint import HTML
+
+    md_text = IN_PATH.read_text(encoding="utf-8")
+    body_html = markdown.markdown(md_text, extensions=["tables", "fenced_code", "toc"])
+    html = (
+        "<!DOCTYPE html><html lang=\"en\"><head><meta charset=\"utf-8\">"
+        f"<title>{TITLE}</title><meta name=\"author\" content=\"Md. Zarif Latif\">"
+        f"<style>{PRINT_CSS.replace('__RUNNING_HEAD__', RUNNING_HEAD)}</style></head><body>"
+        f"{_print_html(body_html)}</body></html>"
+    )
+    HTML(string=html, base_url=str(IN_PATH.parent)).write_pdf(PDF_PATH)
+    return PDF_PATH
+
+
 if __name__ == "__main__":
+    import sys
+
     out = render()
     print(f"Rendered -> {out}")
+    if "--pdf" in sys.argv:
+        print(f"Rendered -> {render_pdf()}")

From e4551130772de3a4501f1299c82768b9ccc3a73d Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 16 Oct 2026 17:30:25 +0000
Subject: [PATCH 3/4] Commit the typeset paper PDF; point README at it

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HTqzkhjyuhZZun8Az1tW6C
---
 .gitignore                                      |   3 +++
 docs/working_paper/README.md                    |   2 +-
 .../detection_timing_backtest_2026-07.pdf       | Bin 0 -> 74871 bytes
 3 files changed, 4 insertions(+), 1 deletion(-)
 create mode 100644 docs/working_paper/detection_timing_backtest_2026-07.pdf

diff --git a/.gitignore b/.gitignore
index 60582a6..8ec7f3f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -50,3 +50,6 @@ RELEASE_CHECKLIST.md
 invoice_template.html
 AI Business Idea Generation.pdf
 *.pdf
+
+# The typeset working paper is a deliverable, not a build artifact.
+!docs/working_paper/detection_timing_backtest_2026-07.pdf
diff --git a/docs/working_paper/README.md b/docs/working_paper/README.md
index 192a619..a033c4f 100644
--- a/docs/working_paper/README.md
+++ b/docs/working_paper/README.md
@@ -51,6 +51,6 @@ pytest aetherius/tests/test_market_reaction_check.py -v
 
 ## Posting as a preprint
 
-- **SSRN** (ssrn.com, free): good fit under Financial Economics → Risk Management. Upload a PDF made from the HTML (browser print → Save as PDF). No affiliation is required.
+- **SSRN** (ssrn.com, free): good fit under Financial Economics → Risk Management. Upload `detection_timing_backtest_2026-07.pdf` (build it with `python scripts/render_working_paper.py --pdf`).
 - **arXiv q-fin.RM / q-fin.CP**: a first-time submitter usually needs an endorsement from an existing arXiv author in that category. Ask a professor or a researcher whose work you cite.
 - In the abstract, keep the Revision 2 framing: triage at the market reaction, not anticipation.
diff --git a/docs/working_paper/detection_timing_backtest_2026-07.pdf b/docs/working_paper/detection_timing_backtest_2026-07.pdf
new file mode 100644
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From 378c038a52c7cc381c300e95d7fa0e2104dd9e31 Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Fri, 16 Oct 2026 17:50:06 +0000
Subject: [PATCH 4/4] site: contact email zarif.latif.biz@gmail.com

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HTqzkhjyuhZZun8Az1tW6C
---
 site/index.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/site/index.html b/site/index.html
index 5fc6cbb..5be7167 100644
--- a/site/index.html
+++ b/site/index.html
@@ -130,7 +130,7 @@ <h2>Run it yourself</h2>
 python simulations/backtest/run_backtest.py --event svb-2023</code></pre>
 
   <h2>About</h2>
-  <p>Built by Zarif Latif as a study in building auditable data systems and evaluating them honestly. Python, FastAPI, PostgreSQL, Celery and GitHub Actions. Feedback, especially critical feedback, is welcome: <a href="mailto:zarif@aetheriusresearch.tech">zarif@aetheriusresearch.tech</a>.</p>
+  <p>Built by Zarif Latif as a study in building auditable data systems and evaluating them honestly. Python, FastAPI, PostgreSQL, Celery and GitHub Actions. Feedback, especially critical feedback, is welcome: <a href="mailto:zarif.latif.biz@gmail.com">zarif.latif.biz@gmail.com</a>.</p>
 
   <footer>
     Apache-2.0 licensed research software. Not investment advice, and not a recommendation to buy, sell or hold any security.