def reconcile_share(share_obj):
transactions = Transactions.objects.filter(
share=share_obj).order_by('trans_date')
try:
stock = Stock.objects.get(exchange=share_obj.exchange,
symbol=share_obj.symbol)
bonuses = Bonusv2.objects.filter(stock=stock)
splits = Splitv2.objects.filter(stock=stock)
round_qty_to_int = True if share_obj.exchange in [
'NSE', 'BSE', 'NSE/BSE'
] else False
qty, buy_value, buy_price, realised_gain, unrealised_gain = reconcile_event_based(
transactions,
bonuses,
splits,
round_qty_to_int=round_qty_to_int,
latest_price=share_obj.latest_price,
latest_conversion_rate=share_obj.conversion_rate)
share_obj.quantity = qty
share_obj.buy_value = buy_value
share_obj.buy_price = buy_price
share_obj.realised_gain = realised_gain
share_obj.gain = unrealised_gain
roi = 0
if qty > 0:
roi = get_roi(transactions, share_obj.latest_value)
share_obj.roi = roi
share_obj.save()
except Stock.DoesNotExist:
description = 'Stock not found in db. No splits/bonuses data available. This affects other calculations.'
create_alert(
summary=
f'{share_obj.exchange} {share_obj.symbol} not found in db.',
content=description,
severity=Severity.warning,
alert_type="Application")
except Exception as ex:
print(
f'exception {ex} when reconciling {share_obj.exchange} {share_obj.symbol}'
)
def get_goal_yearly_contrib(self, goal_id, yr):
st_date = datetime.date(year=yr, day=1, month=1)
end_date = datetime.date(year=yr, day=31, month=12)
if end_date > datetime.date.today():
end_date = datetime.date.today()
cash_flows = list()
contrib = 0
deduct = 0
total = 0
for share_obj in Share.objects.filter(goal=goal_id):
transactions = Transactions.objects.filter(share=share_obj, trans_date__lte=end_date)
stock = Stock.objects.get(exchange=share_obj.exchange, symbol=share_obj.symbol)
bonuses = Bonusv2.objects.filter(stock=stock, record_date__lte=end_date)
splits = Splitv2.objects.filter(stock=stock, ex_date__lte=end_date)
round_qty_to_int = True if share_obj.exchange in ['NSE', 'BSE', 'NSE/BSE'] else False
qty, buy_value, buy_price, realised_gain, unrealised_gain = reconcile_event_based(transactions, bonuses, splits, round_qty_to_int=round_qty_to_int, latest_price=share_obj.latest_price, latest_conversion_rate=share_obj.conversion_rate)
for t in transactions:
if t.trans_date >= st_date:
if t.trans_type == 'Buy':
cash_flows.append((t.trans_date, -1*float(t.trans_price)))
contrib += float(t.trans_price)
else:
cash_flows.append((t.trans_date, float(t.trans_price)))
deduct += -1*float(t.trans_price)
if qty > 0:
year_end_value_vals = get_historical_stock_price_based_on_symbol(share_obj.symbol, share_obj.exchange, end_date+relativedelta(days=-5), end_date)
if year_end_value_vals:
conv_rate = 1
if share_obj.exchange == 'NASDAQ' or share_obj.exchange == 'NYSE':
conv_val = get_conversion_rate('USD', 'INR', end_date)
if conv_val:
conv_rate = conv_val
for k,v in year_end_value_vals.items():
total += float(v)*float(conv_rate)*float(qty)
break
else:
print(f'failed to get year end values for {share_obj.exchange} {share_obj.symbol} {end_date}')
return cash_flows, contrib, deduct, total
def rsu_insights(request):
template = 'rsus/rsu_insights.html'
ret = list()
today = datetime.date.today()
total = dict()
for i, award in enumerate(RSUAward.objects.all()):
rsus = RestrictedStockUnits.objects.filter(award=award)
if len(rsus) > 0:
std = award.award_date
r = lambda: random.randint(0,255)
color = '#{:02x}{:02x}{:02x}'.format(r(), r(), r())
ret.append({
'label':str(award.award_id),
'data': list(),
'fill': 'false',
'borderColor':color
})
std = std.replace(day=1)
reset_to_zero = False
while True:
val = 0
for rsu in RestrictedStockUnits.objects.filter(award=award, vest_date__lte=std):
trans = list()
trans.append(Trans(rsu.shares_for_sale, rsu.vest_date, 'buy', rsu.shares_for_sale*rsu.aquisition_price))
for st in RSUSellTransactions.objects.filter(rsu_vest=rsu, trans_date__lte=std):
trans.append(Trans(st.units, st.trans_date, 'sell', st.trans_price))
q, _,_,_,_ = reconcile_event_based(trans, list(), list())
lv = get_historical_stock_price_based_on_symbol(award.symbol, award.exchange, std+relativedelta(days=-5), std)
if lv:
print(lv)
conv_rate = 1
if award.exchange == 'NASDAQ' or award.exchange == 'NYSE':
conv_val = get_conversion_rate('USD', 'INR', std)
if conv_val:
conv_rate = conv_val
for k,v in lv.items():
val += float(v)*float(conv_rate)*float(q)
break
else:
print(f'failed to get value of {award.award_id} {award.exchange}:{award.symbol} on {std}')
if val > 0:
x = std.strftime('%Y-%m-%d')
ret[i]['data'].append({'x': x, 'y':round(val,2)})
total[x] = total.get(x, 0) + round(val,2)
reset_to_zero = True
elif reset_to_zero:
x = std.strftime('%Y-%m-%d')
ret[i]['data'].append({'x': x, 'y':0})
reset_to_zero = False
total[x] = total.get(x, 0)
if std == today:
break
std = std+relativedelta(months=1)
if std > today:
std = today
print(ret)
if len(ret) > 0:
d = list()
for k,v in sorted(total.items()):
d.append({'x':k, 'y':round(v, 2)})
r = lambda: random.randint(0,255)
color = '#{:02x}{:02x}{:02x}'.format(r(), r(), r())
ret.append({
'label':'total',
'data': d,
'fill': 'false',
'borderColor':color
})
context = dict()
context['progress_data'] = ret
return render(request, template, context)
def get_context_data(self, **kwargs):
data = super().get_context_data(**kwargs)
rsu = data['object']
data['sell_trans'] = RSUSellTransactions.objects.filter(rsu_vest=rsu)
data['curr_module_id'] = 'id_rsu_module'
std = rsu.vest_date
today = datetime.date.today()
r = lambda: random.randint(0,255)
color = '#{:02x}{:02x}{:02x}'.format(r(), r(), r())
ret = list()
ret.append({
'label':'',
'data': list(),
'fill': 'false',
'borderColor':color
})
ret[0]['data'].append({'x': rsu.vest_date.strftime('%Y-%m-%d'), 'y':round(float(rsu.shares_for_sale*rsu.aquisition_price*rsu.conversion_rate),2)})
std = std+relativedelta(months=1)
if std > today:
std = today
else:
std = std.replace(day=1)
while True:
val = 0
trans = list()
trans.append(Trans(rsu.shares_for_sale, rsu.vest_date, 'buy', rsu.shares_for_sale*rsu.aquisition_price*rsu.conversion_rate))
for st in RSUSellTransactions.objects.filter(rsu_vest=rsu, trans_date__lte=std):
trans.append(Trans(st.units, st.trans_date, 'sell', st.trans_price))
q, _,_,_,_ = reconcile_event_based(trans, list(), list())
lv = get_historical_stock_price_based_on_symbol(rsu.award.symbol, rsu.award.exchange, std+relativedelta(days=-5), std)
if lv:
print(lv)
conv_rate = 1
if rsu.award.exchange == 'NASDAQ' or rsu.award.exchange == 'NYSE':
conv_val = get_conversion_rate('USD', 'INR', std)
if conv_val:
conv_rate = conv_val
for k,v in lv.items():
val += float(v)*float(conv_rate)*float(q)
break
else:
print(f'failed to get value of {rsu.award.exchange}:{rsu.award.symbol} on {std}')
if val > 0:
x = std.strftime('%Y-%m-%d')
ret[0]['data'].append({'x': x, 'y':round(val,2)})
if std == today:
break
std = std+relativedelta(months=1)
if std > today:
std = today
data['progress_data'] = ret
try:
s = Stock.objects.get(symbol=rsu.award.symbol, exchange=rsu.award.exchange)
last_date = datetime.date.today()
if rsu.unsold_shares == 0:
all_sell = RSUSellTransactions.objects.filter(rsu_vest=rsu).order_by('trans_date')
last_date = all_sell[len(all_sell)-1].trans_date
res = get_comp_index_values(s, rsu.vest_date, last_date)
if 'chart_labels' in res and len(res['chart_labels']) > 0:
for k, v in res.items():
data[k] = v
except Stock.DoesNotExist:
print(f'trying to get stock that does not exist {rsu.award.symbol} {rsu.award.exchange}')
return data
def espp_insights(request):
template = 'espps/espp_insights.html'
ret = list()
today = datetime.date.today()
total = dict()
for i, espp in enumerate(Espp.objects.all()):
std = espp.purchase_date
r = lambda: random.randint(0, 255)
color = '#{:02x}{:02x}{:02x}'.format(r(), r(), r())
ret.append({
'label': espp.purchase_date.strftime('%Y-%m-%d'),
'data': list(),
'fill': 'false',
'borderColor': color
})
std = std + relativedelta(months=1)
if std > today:
std = today
else:
std = std.replace(day=1)
reset_to_zero = False
while True:
val = 0
trans = list()
trans.append(
Trans(espp.shares_purchased, espp.purchase_date, 'buy',
espp.total_purchase_price))
for st in EsppSellTransactions.objects.filter(espp=espp,
trans_date__lte=std):
trans.append(
Trans(st.units, st.trans_date, 'sell', st.trans_price))
q, _, _, _, _ = reconcile_event_based(trans, list(), list())
lv = get_historical_stock_price_based_on_symbol(
espp.symbol, espp.exchange, std + relativedelta(days=-5), std)
if lv:
print(lv)
conv_rate = 1
if espp.exchange == 'NASDAQ' or espp.exchange == 'NYSE':
conv_val = get_conversion_rate('USD', 'INR', std)
if conv_val:
conv_rate = conv_val
for k, v in lv.items():
val += float(v) * float(conv_rate) * float(q)
break
else:
print(
f'failed to get value of {espp.exchange}:{espp.symbol} on {std}'
)
if val > 0:
x = std.strftime('%Y-%m-%d')
ret[i]['data'].append({'x': x, 'y': round(val, 2)})
total[x] = total.get(x, 0) + round(val, 2)
reset_to_zero = True
elif reset_to_zero:
x = std.strftime('%Y-%m-%d')
ret[i]['data'].append({'x': x, 'y': 0})
reset_to_zero = False
total[x] = total.get(x, 0)
if std == today:
break
std = std + relativedelta(months=1)
if std > today:
std = today
print(ret)
if len(ret) > 0:
d = list()
for k, v in sorted(total.items()):
d.append({'x': k, 'y': v})
r = lambda: random.randint(0, 255)
color = '#{:02x}{:02x}{:02x}'.format(r(), r(), r())
ret.append({
'label': 'total',
'data': d,
'fill': 'false',
'borderColor': color,
'spanGaps': 'false'
})
context = dict()
context['progress_data'] = ret
print(context)
return render(request, template, context)
def get_context_data(self, **kwargs):
data = super().get_context_data(**kwargs)
print(data)
data['goal_str'] = get_goal_name_from_id(data['object'].goal)
data['user_str'] = get_user_name_from_id(data['object'].user)
obj = data['object']
cash_flows = list()
cash_flows.append(
(obj.purchase_date, -1 * float(obj.total_purchase_price)))
for st in EsppSellTransactions.objects.filter(espp=data['object']):
cash_flows.append((st.trans_date, float(st.trans_price)))
if float(obj.latest_value) > 0:
cash_flows.append((obj.as_on_date, float(obj.latest_value)))
roi = xirr(cash_flows, 0.1) * 100
roi = round(roi, 2)
data['roi'] = roi
data['curr_module_id'] = 'id_espp_module'
'''
data['transactions'] = list()
for st in EsppSellTransactions.objects.filter(espp=data['object']):
data['transactions'].append({
'id':st.id,
'trans_date':st.trans_date,
'price':st.price,
'units':st.units,
'conversion_rate':st.conversion_rate,
'trans_price':st.trans_price,
'realised_gain':st.realised_gain,
'notes':st.notes
})
'''
std = obj.purchase_date
today = datetime.date.today()
r = lambda: random.randint(0, 255)
color = '#{:02x}{:02x}{:02x}'.format(r(), r(), r())
ret = list()
ret.append({
'label': '',
'data': list(),
'fill': 'false',
'borderColor': color
})
ret[0]['data'].append({
'x': obj.purchase_date.strftime('%Y-%m-%d'),
'y': round(float(obj.total_purchase_price), 2)
})
std = std + relativedelta(months=1)
if std > today:
std = today
else:
std = std.replace(day=1)
reset_to_zero = False
while True:
val = 0
trans = list()
trans.append(
Trans(obj.shares_purchased, obj.purchase_date, 'buy',
obj.total_purchase_price))
for st in EsppSellTransactions.objects.filter(espp=obj,
trans_date__lte=std):
trans.append(
Trans(st.units, st.trans_date, 'sell', st.trans_price))
q, _, _, _, _ = reconcile_event_based(trans, list(), list())
lv = get_historical_stock_price_based_on_symbol(
obj.symbol, obj.exchange, std + relativedelta(days=-5), std)
if lv:
print(lv)
conv_rate = 1
if obj.exchange == 'NASDAQ' or obj.exchange == 'NYSE':
conv_val = get_conversion_rate('USD', 'INR', std)
if conv_val:
conv_rate = conv_val
for k, v in lv.items():
val += float(v) * float(conv_rate) * float(q)
break
else:
print(
f'failed to get value of {obj.exchange}:{obj.symbol} on {std}'
)
if val > 0 or reset_to_zero:
x = std.strftime('%Y-%m-%d')
ret[0]['data'].append({'x': x, 'y': round(val, 2)})
if val > 0:
reset_to_zero = True
else:
reset_to_zero = False
if std == today:
break
std = std + relativedelta(months=1)
if std > today:
std = today
data['progress_data'] = ret
try:
s = Stock.objects.get(symbol=obj.symbol, exchange=obj.exchange)
last_date = datetime.date.today()
if obj.shares_avail_for_sale == 0:
all_sell = EsppSellTransactions.objects.filter(
espp=obj).order_by('trans_date')
last_date = all_sell[len(all_sell) - 1].trans_date
res = get_comp_index_values(s, obj.purchase_date, last_date)
if 'chart_labels' in res and len(res['chart_labels']) > 0:
for k, v in res.items():
data[k] = v
except Stock.DoesNotExist:
print(
f'trying to get stock that does not exist {obj.symbol} {obj.exchange}'
)
return data