"""R627：共同股票篮子，滞后波动率，真实现金/碎股/比例费用与权重漂移。"""
from copy import deepcopy
from math import isclose,isfinite
from statistics import stdev

RETURNS={'A':[.01,-.01,.02,.01,-.02,.03,.01,.01],
         'B':[.02,-.02,.04,-.01,.03,-.01,.02,-.02],
         'C':[0,0,0,0,0,0,0,0]}


def targets(history,method):
    if method not in {'equal','inverse'}:raise ValueError('unknown weighting method')
    eligible={s:stdev(r) for s,r in history.items() if len(r)==3 and all(x is not None and isfinite(x) for x in r) and stdev(r)>1e-12}
    if not eligible:return {}
    raw={s:1 if method=='equal' else 1/vol for s,vol in eligible.items()}
    total=sum(raw.values())
    return {s:w/total for s,w in raw.items()}


def run(data,method):
    prices={s:[100.] for s in data}
    for s,series in data.items():
        for r in series:prices[s].append(prices[s][-1]*(1+r))
    cash=1000.;shares={s:0. for s in data};nav=[cash];ledger=[];total_cost=0.;traded=0.
    for t in range(3,8):
        open_prices={s:prices[s][t] for s in data}
        before=cash+sum(shares[s]*open_prices[s] for s in data)
        if t in [3,5,7]:
            history={s:data[s][t-3:t] for s in data}
            weights=targets(history,method)
            old={s:shares[s]*open_prices[s] for s in data}
            lo,hi=0.,before
            for _ in range(100):
                mid=(lo+hi)/2
                amount=sum(abs(mid*weights.get(s,0)-old[s]) for s in data)
                if mid+.001*amount>before:hi=mid
                else:lo=mid
            invest=(lo+hi)/2 if weights else 0.
            target={s:invest*weights.get(s,0)/open_prices[s] for s in data}
            fills={s:target[s]-shares[s] for s in data}
            notional=sum(abs(fills[s])*open_prices[s] for s in data);cost=.001*notional
            cash=before-sum(target[s]*open_prices[s] for s in data)-cost
            assert cash>=-1e-8
            shares=target;total_cost+=cost;traded+=notional
            assert isclose(cash+sum(shares[s]*open_prices[s] for s in data),before-cost,rel_tol=0,abs_tol=1e-8)
            assert not weights or isclose(sum(weights.values()),1,rel_tol=0,abs_tol=1e-12)
            ledger.append({'session':t,'weights':weights,'fills':fills,'cost':cost,
                           'cash':cash,'shares':dict(shares),'pretrade_equity':before})
        ending=cash+sum(shares[s]*prices[s][t+1] for s in data)
        drift={s:shares[s]*prices[s][t+1]/ending for s in data}
        ledger[-1]['end_weights']=drift
        nav.append(ending)
    peak=nav[0];drawdown=0
    for value in nav:
        peak=max(peak,value);drawdown=min(drawdown,value/peak-1)
    return {'ending':nav[-1],'net_return':nav[-1]/nav[0]-1,'cost':total_cost,
            'turnover':traded/nav[0],'max_drawdown':drawdown,'ledger':ledger,'nav':nav}


ew=run(RETURNS,'equal');iv=run(RETURNS,'inverse')
assert ew['ledger'][0]['weights']=={'A':.5,'B':.5}
assert isclose(iv['ledger'][0]['weights']['A'],2/3,rel_tol=0,abs_tol=1e-12)
assert 'C' not in ew['ledger'][0]['weights'] and 'C' not in iv['ledger'][0]['weights']
assert targets({'Z':[0,0,0],'M':[.01,.02]},'equal')=={}
assert targets({'Z':[0,0,0],'M':[.01,.02]},'inverse')=={}
assert targets({'M':[None,.01,.02]},'equal')==targets({'M':[None,.01,.02]},'inverse')=={}
cash_only=run({s:[0]*8 for s in RETURNS},'inverse')
assert cash_only['ending']==1000 and cash_only['cost']==0
future=deepcopy(RETURNS);future['A'][7]=.5
assert run(future,'inverse')['ledger'][0]['weights']==iv['ledger'][0]['weights']
assert ew['cost']>0 and iv['cost']>0
assert isclose(ew['ending'],1023.715184,rel_tol=0,abs_tol=1e-6)
assert isclose(iv['ending'],1018.583882,rel_tol=0,abs_tol=1e-6)
assert not isclose(ew['ledger'][0]['end_weights']['A'],.5,rel_tol=0,abs_tol=1e-6)
for label,result in [('equal',ew),('inverse',iv)]:
    print(label+' ending='+format(result['ending'],'.6f')+' net='+format(result['net_return'],'.6%')
          +' cost='+format(result['cost'],'.6f')+' turnover='+format(result['turnover'],'.6f')
          +' max_drawdown='+format(result['max_drawdown'],'.6%'))
    print(label+' first_weights='+str(result['ledger'][0]['weights'])+' rebalance_sessions=[3, 5, 7]')
    for row in result['ledger']:
        print(label+' session='+str(row['session'])+' target='+str({k:round(v,6) for k,v in row['weights'].items()})
              +' fills='+str({k:round(v,6) for k,v in row['fills'].items()})
              +' end_weights='+str({k:round(v,6) for k,v in row['end_weights'].items()})
              +' cost='+format(row['cost'],'.6f')+' cash='+format(row['cash'],'.12f'))
print('zero_vol_and_short_history=common_exclusion future_change_first_weights=unchanged self_financing=True')