"""
커버드콜 ETF 단점 · 백테스트 7호 재현 코드 (ajussiguide.com)
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이 파일은 파이썬 3 스크립트다. 확장자를 .py로 바꿔 저장한 뒤 같은 폴더의 coveredcall-bt7-data.csv와 함께 실행한다.
  python coveredcall-bt7-calc.py coveredcall-bt7-data.csv
아래 첫 번째 '#' 줄부터가 코드다. 이 설명 블록은 파이썬이 실행하지 않도록 문자열로 감싸 두었다.
"""
# 커버드콜 ETF 단점 · 백테스트 7호 — 공개 재현 코드
# 사용: python coveredcall-bt7-calc.py coveredcall-bt7-data.csv
# 입력 CSV 열: symbol,date,close,dividend_exdate (분배락일 주당 분배금, 없으면 빈칸)
import csv,sys,datetime as dt
path=sys.argv[1] if len(sys.argv)>1 else 'coveredcall-bt7-data.csv'
raw={}
for r in csv.DictReader(open(path)):
    c=float(r['close']); assert c>0
    raw.setdefault(r['symbol'],[]).append((dt.date.fromisoformat(r['date']),c,float(r['dividend_exdate'] or 0)))
syms={}
for s,rows in raw.items():
    rows.sort(); assert all(rows[i][0]<rows[i+1][0] for i in range(len(rows)-1)),'dup/unsorted'
    x=[];tr=1.0
    for i,(d,c,dv) in enumerate(rows):
        if i>0: tr*=(c+dv)/rows[i-1][1]          # 분배락일 종가 재투자
        x.append({'d':d,'c':c,'tr':tr,'dv':dv})
    syms[s]=x
pct=lambda v:round(v*100,1)
def align(a,b):
    mb={r['d']:r for r in b}; return [(r,mb[r['d']]) for r in a if r['d'] in mb]
def stats(A,B):
    x=align(A,B); n=len(x); f,l=x[0],x[-1]; yrs=(l[0]['d']-f[0]['d']).days/365.25
    trA=l[0]['tr']/f[0]['tr']-1; trB=l[1]['tr']/f[1]['tr']-1
    cagr=lambda r:(1+r)**(1/yrs)-1
    def mdd(k):
        p=-1;pd=None;m=0;md=(None,None)
        for pair in x:
            r=pair[k]
            if r['tr']>p: p=r['tr'];pd=r['d']
            dd=r['tr']/p-1
            if dd<m: m=dd;md=(pd,r['d'])
        return pct(m),[str(d) for d in md]
    def roll(w):
        if n<=w: return None
        c=sum(1 for i in range(w,n) if x[i][0]['tr']/x[i-w][0]['tr']>x[i][1]['tr']/x[i-w][1]['tr'])
        return {'win':round(c/(n-w)*100,1),'t':n-w}
    def dca(k):
        u=inv=0
        for i in range(0,n,21): u+=100/x[i][k]['tr']; inv+=100
        return pct(u*x[-1][k]['tr']/inv-1)
    return {'from':str(f[0]['d']),'to':str(l[0]['d']),'yrs':round(yrs,2),'n':n,
        'TR_cc':pct(trA),'TR_idx':pct(trB),'CAGR_cc':pct(cagr(trA)),'CAGR_idx':pct(cagr(trB)),
        'PR_cc':pct(l[0]['c']/f[0]['c']-1),'PR_idx':pct(l[1]['c']/f[1]['c']-1),
        'MDD_cc':mdd(0),'MDD_idx':mdd(1),'r1':roll(252),'r3':roll(756),'r5':roll(1260),
        'DCA_cc':dca(0),'DCA_idx':dca(1),'end_value_100':[round(100*(1+trA),1),round(100*(1+trB),1)]}
def yearly(s):
    x=syms[s];by={}
    for r in x: by.setdefault(r['d'].year,[r['tr'],r['tr']]); by[r['d'].year][1]=r['tr']
    ys=sorted(by); return {str(ys[i]):pct(by[ys[i]][1]/by[ys[i-1]][1]-1) for i in range(1,len(ys))}
def cash(s):
    x=syms[s];f,l=x[0],x[-1];sd=sum(r['dv'] for r in x);ds=[r for r in x if r['dv']>0]
    yrs=(l['d']-f['d']).days/365.25;last12=sum(r['dv'] for r in ds[-12:])
    return {'p0':f['c'],'p1':l['c'],'n_div':len(ds),'sumDiv':round(sd,4),'priceRet':pct(l['c']/f['c']-1),
        'cashTR_incl_unpaid':pct((l['c']+sd)/f['c']-1),'cash_annualized':pct(((l['c']+sd)/f['c'])**(1/yrs)-1),
        'last12_yield':pct(last12/l['c'])}
def pt(s,a,b):
    x={r['d']:r for r in syms[s]}; return {'TR':pct(x[b]['tr']/x[a]['tr']-1),'PR':pct(x[b]['c']/x[a]['c']-1)}
def mdd_year(s,y):
    p=-1;m=0
    for r in syms[s]:
        if r['d'].year==y: p=max(p,r['tr']); m=min(m,r['tr']/p-1)
    return pct(m)
def worst(s,w):
    x=syms[s];b=(9,None,None)
    for i in range(w,len(x)):
        r=x[i]['tr']/x[i-w]['tr']-1
        if r<b[0]: b=(r,str(x[i-w]['d']),str(x[i]['d']))
    return {'ret':pct(b[0]),'from':b[1],'to':b[2]}
pairs={'QYLD_QQQ':('QYLD','QQQ'),'XYLD_SPY':('XYLD','SPY'),'JEPI_SPY':('JEPI','SPY'),'JEPQ_QQQ':('JEPQ','QQQ')}
R={'pairs':{k:stats(syms[a],syms[b]) for k,(a,b) in pairs.items()},
   'yearly_TR':{s:yearly(s) for s in syms},'cash':{s:cash(s) for s in ['QYLD','XYLD','JEPI','JEPQ']},
   'case_20211231_20241231':{s:pt(s,dt.date(2021,12,31),dt.date(2024,12,31)) for s in ['QYLD','QQQ','JEPI','SPY']},
   'recent_1y_20250922_20260921':{s:pt(s,dt.date(2025,9,22),dt.date(2026,9,21)) for s in ['JEPI','SPY','QYLD','QQQ']},
   'mdd_2022':{s:mdd_year(s,2022) for s in ['QYLD','QQQ','JEPI','SPY','XYLD']},
   'worst_1y':{s:worst(s,252) for s in syms}}
import json; print(json.dumps(R,ensure_ascii=False,indent=1))