RecessionAlert Standard Charts — exploratory proxy campaign¶

from hashlib import sha256
import json
import sqlite3
from pathlib import Path

ROOT = Path.cwd()
DB = ROOT / "data" / "recessionalert.sqlite"
MANIFEST = ROOT / "research" / "artifacts" / "recessionalert" / "manifest.json"
INVENTORY = ROOT / "research" / "findings" / "recessionalert_inventory.md"
PAGE = "https://recessionalert.com/charts/"
EXPECTED = "sha256:c610205a996e580266e255a7b7999bc33e889b12bed140898f0056c3bacdae75"
with sqlite3.connect(f"file:{DB}?mode=ro", uri=True) as connection:
    connection.execute("PRAGMA query_only=ON")
    row = connection.execute("SELECT status, sha256, content_length, body FROM pages WHERE url = ?", (PAGE,)).fetchone()
    assets = connection.execute("SELECT COUNT(*) FROM assets WHERE page_url = ?", (PAGE,)).fetchone()[0]
manifest = json.loads(MANIFEST.read_text())
manifest_page = next(item for item in manifest if item.get("redacted_url") == PAGE)
inventory_text = INVENTORY.read_text()
assert row and row[1] == EXPECTED == manifest_page["sha256"]
assert sha256(row[3]).hexdigest() == EXPECTED.removeprefix("sha256:")
assert "CHARTS > Standard" in inventory_text and EXPECTED[:18] in inventory_text
print(f"source_sha256={row[1]}")
print(f"manifest_digest_verified={manifest_page['sha256'] == row[1]}")
print(f"inventory_digest_verified={EXPECTED[:18] in inventory_text}")
print(f"page_status={row[0]} body_bytes={row[2]} target_assets={assets}")
print("native_span=trough/top multi-decade claim; NEWHI August 2016; other spans unknown")
print("publication_schedule=daily 08:00 GMT/04:00 EST; weekly weekend/no later Monday; monthly third working day; intraday 15 minutes; ALIX end-of-day")
print("causal_policy=one available-period lag then next available bar; lag zero control only")

import sys
sys.path.insert(0, str(ROOT))
from research.research_campaign.recessionalert_1365 import default_variants, evaluate_variant, load_proxy_panel
panel = load_proxy_panel()
print(f"panel_span={panel.index.min().date()}..{panel.index.max().date()} observations={len(panel)}")
for variant in default_variants():
    result = evaluate_variant(panel, family=variant["family"], lookback_months=variant["lookback_months"], threshold=variant["threshold"], lag_bars=variant["lag_bars"])
    returns = result["portfolio_returns"].dropna()
    equity = (1.0 + returns).cumprod()
    drawdown = (equity / equity.cummax() - 1.0).min()
    cagr = equity.iloc[-1] ** (12.0 / len(returns)) - 1.0
    print(f"{variant['id']} status=tested cagr={cagr:.6f} max_dd={drawdown:.6f} label={variant['claim_kind']}")
print("tested_variants=6 causal_variants=5 lag_zero_control_excluded=True")