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import pandas as pd
from . import DAILY_DIR
from exchangelib import FileAttachment
from serenitas.analytics.utils import get_fx
paths = {
"Serenitas": ["NYops", "Margin calls MS"],
"Brinker": ["NYops", "Margin Calls MS-Brinker"],
"BowdSt": ["BowdoinOps", "Margin MS"],
"Selene": ["SeleneOps", "Margin MS"],
}
subjects = {
"Serenitas": "SERCX **Daily",
"Brinker": "061761QY1***BRINKER",
"BowdSt": "BOSTON PATRIOT BOWDOIN",
"Selene": "ISO SELENE",
}
def download_files(em, count=20, *, fund="Serenitas", **kwargs):
if fund not in paths:
return
emails = em.get_msgs(
path=paths[fund],
count=count,
subject__contains=subjects[fund],
)
DATA_DIR = DAILY_DIR / fund / "MS_reports"
for msg in emails:
for attach in msg.attachments:
if isinstance(attach, FileAttachment):
if "NETSwaps" in attach.name:
fname = "Trade_Detail_" + attach.name.split("_")[1]
elif "NETFX" in attach.name:
fname = "Trade_Detail_FX_" + attach.name.split("_")[1]
elif "NET_Collateral" in attach.name:
fname = "Collateral_Detail_" + attach.name.rsplit("_", 1)[1]
elif "Statement" in attach.name and attach.name.endswith("pdf"):
ending = attach.name.rsplit("_", 1)[1]
fname = "Statement_" + ending.split(".")[0] + ".pdf"
else:
continue
p = DATA_DIR / fname
if not p.exists():
p.write_bytes(attach.content)
def collateral(d, dawn_trades, *, fund="Serenitas", **kwargs):
df = pd.read_excel(
DAILY_DIR / fund / "MS_reports" / f"Collateral_Detail_{d:%Y%m%d}.xls"
)
collat = df.loc[1, "coll_val_ccy"].replace(",", "")
if "(" in collat:
collat = collat[1:-1]
collat = -float(collat)
else:
collat = float(collat)
df = pd.read_excel(DAILY_DIR / fund / "MS_reports" / f"Trade_Detail_{d:%Y%m%d}.xls")
try:
df_fx = pd.read_excel(
DAILY_DIR / fund / "MS_reports" / f"Trade_Detail_FX_{d:%Y%m%d}.xls"
)
net_fx_exposure = (
df_fx.loc[df_fx.buy_ccy == "EUR", "amt_buy_ccy"].sum()
- df_fx.loc[df_fx.sell_ccy == "EUR", "amt_sell_ccy"].sum()
)
fx_ia = net_fx_exposure * 0.05 * get_fx(d, "EUR")
df = pd.concat([df, df_fx])
except FileNotFoundError: # We don't always have FX files
pass
# df = df.dropna(subset=["trade_ccy"])
df = df.merge(dawn_trades, how="left", left_on="trade_id", right_on="cpty_id")
missing_ids = df.loc[df.cpty_id.isnull(), "trade_id"]
if not missing_ids.empty:
raise ValueError(f"{missing_ids.tolist()} not in the database for {fund}")
df = df.groupby("folder")[["collat_req_in_agr_ccy"]].sum()
df["Currency"] = "USD"
df = df.reset_index()
df.columns = ["Strategy", "Amount", "Currency"]
try:
df.loc[df.Strategy == "TCSH", "Amount"] -= fx_ia
except UnboundLocalError:
pass
if "M_CSH_CASH" not in df.Strategy.array:
df.loc[len(df.index)] = ["M_CSH_CASH", -collat - df.Amount.sum(), "USD"]
else:
df.loc[df.Strategy == "M_CSH_CASH", "Amount"] -= collat + df.Amount.sum()
df["date"] = d
return df.set_index("Strategy")
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