diff options
Diffstat (limited to 'python/swaption_quotes.py')
| -rw-r--r-- | python/swaption_quotes.py | 101 |
1 files changed, 61 insertions, 40 deletions
diff --git a/python/swaption_quotes.py b/python/swaption_quotes.py index 27a80b7a..83ecb427 100644 --- a/python/swaption_quotes.py +++ b/python/swaption_quotes.py @@ -5,14 +5,22 @@ from db import serenitas_pool from statistics import median -def get_refids(conn, index, series, expiry, value_date=datetime.date.today(), - sources=["GS", "MS", "CITI"]): - sql_str = ("SELECT ref_id, ref, quotedate FROM swaption_ref_quotes " - "WHERE quotedate::date=%s " - " AND quote_source=%s " - " AND index=%s AND series=%s" - " AND expiry=%s " - "ORDER BY quotedate DESC LIMIT 1") +def get_refids( + conn, + index, + series, + expiry, + value_date=datetime.date.today(), + sources=["GS", "MS", "CITI"], +): + sql_str = ( + "SELECT ref_id, ref, quotedate FROM swaption_ref_quotes " + "WHERE quotedate::date=%s " + " AND quote_source=%s " + " AND index=%s AND series=%s" + " AND expiry=%s " + "ORDER BY quotedate DESC LIMIT 1" + ) d = {} with conn.cursor() as c: for s in sources: @@ -20,57 +28,70 @@ def get_refids(conn, index, series, expiry, value_date=datetime.date.today(), d[s] = c.fetchone() return d -def adjust_stacks(index_type, series, expiry, - value_date=datetime.date.today(), - sources=["GS", "MS", "CITI"], common_ref=None): + +def adjust_stacks( + index_type, + series, + expiry, + value_date=datetime.date.today(), + sources=["GS", "MS", "CITI"], + common_ref=None, +): conn = serenitas_pool.getconn() d = get_refids(conn, index_type, series, expiry, value_date, sources) if all(v is None for v in d.values()): raise ValueError("no quotes") if common_ref is None: common_ref = median(v[1] for v in d.values()) - index = CreditIndex(index_type, series, "5yr", value_date=value_date, - notional=10000.) + index = CreditIndex( + index_type, series, "5yr", value_date=value_date, notional=10000.0 + ) index.ref = common_ref old_pv = index.pv quotes = {} for s, (ref_id, ref, _) in d.items(): index.ref = ref dindex_pv = index.pv - old_pv - df = pd.read_sql_query("SELECT strike, pay_bid, pay_offer, delta_pay, " - "rec_bid, rec_offer, delta_rec FROM swaption_quotes " - "WHERE ref_id=%s ORDER BY strike", - conn, - params=(ref_id,), - index_col=['strike']) + df = pd.read_sql_query( + "SELECT strike, pay_bid, pay_offer, delta_pay, " + "rec_bid, rec_offer, delta_rec FROM swaption_quotes " + "WHERE ref_id=%s ORDER BY strike", + conn, + params=(ref_id,), + index_col=["strike"], + ) if s == "GS": - df['delta_rec'] = 1 - df['delta_pay'] + df["delta_rec"] = 1 - df["delta_pay"] if index_type == "HY": - df[['pay_bid', 'pay_offer', 'rec_bid', 'rec_offer']] *=100 + df[["pay_bid", "pay_offer", "rec_bid", "rec_offer"]] *= 100 if s == "CITI": - df['delta_rec'] *= -1 - if dindex_pv != 0.: - df[['pay_bid', 'pay_offer']] = df[['pay_bid', 'pay_offer']].sub( - df.delta_pay * dindex_pv, axis=0) - df[['rec_bid', 'rec_offer']] = df[['rec_bid', 'rec_offer']].add( - df.delta_rec * dindex_pv, axis=0) + df["delta_rec"] *= -1 + if dindex_pv != 0.0: + df[["pay_bid", "pay_offer"]] = df[["pay_bid", "pay_offer"]].sub( + df.delta_pay * dindex_pv, axis=0 + ) + df[["rec_bid", "rec_offer"]] = df[["rec_bid", "rec_offer"]].add( + df.delta_rec * dindex_pv, axis=0 + ) quotes[s] = df - quotes = pd.concat(quotes, names=['source']) - quotes = quotes.swaplevel('source', 'strike').sort_index() - inside_quotes = pd.concat([ - quotes[['pay_bid', 'rec_bid']].groupby(level='strike').max(), - quotes[['pay_offer', 'rec_offer']].groupby(level='strike').min()], - axis=1 + quotes = pd.concat(quotes, names=["source"]) + quotes = quotes.swaplevel("source", "strike").sort_index() + inside_quotes = pd.concat( + [ + quotes[["pay_bid", "rec_bid"]].groupby(level="strike").max(), + quotes[["pay_offer", "rec_offer"]].groupby(level="strike").min(), + ], + axis=1, ).sort_index(axis=1) - quotes = quotes.unstack('source') + quotes = quotes.unstack("source") d = {} - for k in ['pay_bid', 'rec_bid']: - #quotes[k].style.apply(highlight_max, axis=1) + for k in ["pay_bid", "rec_bid"]: + # quotes[k].style.apply(highlight_max, axis=1) df = pd.concat([quotes[k], inside_quotes[k]], axis=1) - d[k] = df.rename(columns={k: 'Best'}) - for k in ['pay_offer', 'rec_offer']: - #quotes[k].style.apply(highlight_min, axis=1) + d[k] = df.rename(columns={k: "Best"}) + for k in ["pay_offer", "rec_offer"]: + # quotes[k].style.apply(highlight_min, axis=1) df = pd.concat([inside_quotes[k], quotes[k]], axis=1) - d[k] = df.rename(columns={k: 'Best'}) + d[k] = df.rename(columns={k: "Best"}) serenitas_pool.putconn(conn) return common_ref, pd.concat(d, axis=1) |