"""Article13: dated annual financial facts and explicit instructional models."""
import argparse,datetime as dt,gzip,hashlib,html,json,math
from decimal import Decimal,ROUND_HALF_UP
from pathlib import Path
ROOT=Path(__file__).resolve().parents[1];DATA=ROOT/'articles/data/stock-metrics';ARTICLE=ROOT/'articles/market-cap-per-pbr-guide.html'
def sha(b):return hashlib.sha256(b).hexdigest()
def ratio(a,b):return a/b if b>0 else None
def price(code):
raw=json.loads(gzip.decompress((DATA/'raw'/f'price_{code}.json.gz').read_bytes()))['chart']['result'][0]
if raw['meta']['currency']!='JPY' or raw['meta']['symbol']!=code+'.T':raise ValueError('Wrong price currency/symbol')
dates=[dt.datetime.fromtimestamp(x,dt.timezone.utc).date().isoformat() for x in raw['timestamp']]
if dates.count('2026-03-31')!=1:raise ValueError('Price date missing/duplicated')
for e in raw.get('events',{}).get('splits',{}).values():
if dt.datetime.fromtimestamp(e['date'],dt.timezone.utc).date().isoformat()>'2026-03-31':raise ValueError('Post-reference split needs price rebasing review')
index=dates.index('2026-03-31')
if not raw['indicators']['quote'][0]['volume'][index]:raise ValueError('No observed trading volume')
value=raw['indicators']['quote'][0]['close'][index]
if value is None or not math.isfinite(value) or value<=0:raise ValueError('Invalid price')
return float(Decimal(str(value)).quantize(Decimal('.01'),rounding=ROUND_HALF_UP)),value
def load():
m=json.loads((DATA/'sources.json').read_text())
for name,digest in m['input_sha256'].items():
if sha((DATA/name).read_bytes())!=digest:raise ValueError('Input checksum mismatch: '+name)
rows=json.loads((DATA/'companies.json').read_text())['companies']
if len(rows)!=6 or len({c['code'] for c in rows})!=6:raise ValueError('Company count/duplicates')
for c in rows:
if (c['fiscal_start'],c['fiscal_end'],c['price_date'],c['equity_begin_date'])!=('2025-04-01','2026-03-31','2026-03-31','2025-03-31'):raise ValueError('Unmatched fiscal/price dates')
if c['treasury_shares']<0 or c['issued_shares']<=c['treasury_shares'] or c['weighted_average_shares']<=0:raise ValueError('Invalid share counts')
if c['disclosed_date']<=c['price_date']:raise ValueError('Retrospective disclosure flag inconsistent')
return rows
def metrics(p,issued,treasury,weighted,n,e0,e1):
if p<=0 or issued<=treasury or treasury<0 or weighted<=0:raise ValueError('Invalid price/shares')
shares=issued-treasury;eps=n/weighted;bps=e1/shares;eps_end=n/shares;roe_avg=ratio(n,(e0+e1)/2);roe_end=ratio(n,e1)
return dict(price=p,issued=issued,treasury=treasury,shares=shares,weighted=weighted,profit=n,equity_begin=e0,equity_end=e1,market_cap=p*shares,eps=eps,bps=bps,per=ratio(p,eps),pbr=ratio(p,bps),roe_average=roe_avg,roe_end=roe_end,eps_end=eps_end,per_end=ratio(p,eps_end))
def calculate():
out=[]
for c in load():
p,raw=price(c['code']);r=metrics(p,c['issued_shares'],c['treasury_shares'],c['weighted_average_shares'],c['profit_million_yen']*1e6,c['equity_begin_million_yen']*1e6,c['equity_end_million_yen']*1e6)
r.update(code=c['code'],name=c['name'],industry=c['industry'],price_raw_api=raw,source=c['source'],reported_eps=float(c['reported_eps_yen']),reported_bps=float(c['reported_bps_yen']),forecast_per=None,price_date=c['price_date'],fiscal_end=c['fiscal_end'],disclosed_date=c['disclosed_date'])
r['eps_vs_reported']=r['eps']-r['reported_eps'];r['bps_vs_reported']=r['bps']-r['reported_bps']
# One displayed sen plus max one-million-yen input reporting unit / denominator.
if abs(r['eps_vs_reported'])>=.01+1e6/r['weighted'] or abs(r['bps_vs_reported'])>=.01+1e6/r['shares']:raise ValueError('Published per-share facts not reconciled within stated precision')
out.append(r)
base=metrics(1000,100000000,0,100000000,10000000000,100000000000,100000000000)
issued=metrics(1000,120000000,0,120000000,10000000000,120000000000,120000000000)
split=metrics(500,200000000,0,200000000,10000000000,100000000000,100000000000)
buyback=metrics(1000,100000000,20000000,80000000,10000000000,80000000000,80000000000)
return dict(review_date='2026-11-07',price_date='2026-03-31',fiscal_start='2025-04-01',fiscal_end='2026-03-31',currency='JPY',retrospective_not_point_in_time=True,companies=out,examples=dict(price_cap=[dict(company='A',price=100,shares=1000000000,market_cap=100000000000),dict(company='B',price=1000,shares=10000000,market_cap=10000000000)],per=[dict(price=1000,eps=eps,per=ratio(1000,eps)) for eps in (100,50,20,0,-50)],pbr=[dict(price=1000,bps=bps,pbr=ratio(1000,bps)) for bps in (500,1000,2000,0,-500)],profit_halved=dict(price=1000,eps_before=100,eps_after=50,per_before=10,per_after=20),base=base,split=split,issue=issued,buyback=buyback,issue_existing_owner_before=.01,issue_existing_owner_after=1000000/120000000),growth=[dict(growth=g,points=[dict(year=y,eps=100*(1+g)**y,per=1000/(100*(1+g)**y)) for y in range(6)]) for g in (0,.1,.2)],identity=[dict(per=per,points=[dict(roe=r/100,pbr=per*r/100) for r in range(1,21)]) for per in (10,15,20)])
def number(v,unit='',scale=1,digits=2):return '算定対象外' if v is None else f'{v/scale:,.{digits}f}'+unit
def table(caption,heads,rows):
return '表は左右にスクロールできます。
'+caption+''+''.join('| '+html.escape(h)+' | ' for h in heads)+'
'+''.join(''+''.join(('| '+html.escape(str(v))+' | ') if i==0 else ''+html.escape(str(v))+' | ' for i,v in enumerate(row))+'
' for row in rows)+'