diff options
Diffstat (limited to 'python/thetas-durations.py')
| -rw-r--r-- | python/thetas-durations.py | 118 |
1 files changed, 59 insertions, 59 deletions
diff --git a/python/thetas-durations.py b/python/thetas-durations.py index 3959354f..bf7d41a7 100644 --- a/python/thetas-durations.py +++ b/python/thetas-durations.py @@ -36,9 +36,8 @@ def get_legs(index, series, tenors): contingent_legs[tenor] = (ContingentLeg(issue_date, maturity, True), ContingentLeg(issue_date, maturity_short, True)) # number of seconds since epoch - df.maturity = df.maturity.view(int) // int(86400 * 1e9) # number of days between 1900-1-1 and epoch - df.maturity += 134774 + df.maturity = (df.maturity.values.view("M8[D]").astype(int) + 134774) return fee_legs, contingent_legs, df def index_pv(fl, cl, value_date, step_in_date, cash_settle_date, yc, sc, recovery): @@ -46,63 +45,64 @@ def index_pv(fl, cl, value_date, step_in_date, cash_settle_date, yc, sc, recover cl_pv = fl.pv(value_date, step_in_date, cash_settle_date, yc, sc, True) return dl_pv - cl_pv -conn = serenitas_engine.raw_connection() -for index in ["IG", "HY", "EU", "XO"]: - if index in ["HY", "XO"]: - recoveries = np.full(len(tenors[index]), 0.3) - else: - recoveries = np.full(len(tenors[index]), 0.4) - for series in range(18, 33): - if index in ["EU", "XO"] and series == 32: - continue - fee_legs, contingent_legs, df = \ - get_legs(index, series, tenors[index]) +if __name__ == "__main__": + conn = serenitas_engine.raw_connection() + for index in ["IG", "HY", "EU", "XO"]: + if index in ["HY", "XO"]: + recoveries = np.full(len(tenors[index]), 0.3) + else: + recoveries = np.full(len(tenors[index]), 0.4) + for series in range(18, 33): + if index in ["EU", "XO"] and series == 32: + continue + fee_legs, contingent_legs, df = \ + get_legs(index, series, tenors[index]) - index_quotes = pd.read_sql_query( - "SELECT distinct on (date, tenor) id, date, tenor, version, close_price " - "FROM index_quotes_pre " - "LEFT JOIN index_risk USING (id) " - "WHERE index=%s AND series=%s " - "AND source='MKIT' AND duration is NULL AND tenor IN %s " - "ORDER BY date, tenor, version desc", - serenitas_engine, - params=(index, series, tenors[index]), - parse_dates=['date'], - index_col='id') - if index_quotes.empty: - continue - index_quotes.tenor = index_quotes.tenor.astype(tenor_t) - index_quotes = index_quotes.sort_values('tenor') - index_quotes['close_price'] = 1. - index_quotes['close_price'] / 100 - with conn.cursor() as c: - for value_date, data in index_quotes.groupby('date'): - yc = get_curve(value_date, "USD" if index in ["IG", "HY"] else "EUR") - # right_index?? is it a bug? - data = data.merge(df, on='tenor', right_index=True) - step_in_date = value_date + datetime.timedelta(days=1) - cash_settle_date = value_date + 3 * BDay() - start_date = previous_twentieth(value_date) - sc = SpreadCurve(value_date, yc, start_date, - step_in_date, cash_settle_date, - data.maturity.values, data.coupon.values, - data.close_price.values, - recoveries) - for r in data[['coupon', 'tenor', 'close_price']].itertuples(): - fl, fl_short = fee_legs[r.tenor] - cl, cl_short = contingent_legs[r.tenor] + index_quotes = pd.read_sql_query( + "SELECT distinct on (date, tenor) id, date, tenor, version, close_price " + "FROM index_quotes_pre " + "LEFT JOIN index_risk USING (id) " + "WHERE index=%s AND series=%s " + "AND source='MKIT' AND duration is NULL AND tenor IN %s " + "ORDER BY date, tenor, version desc", + serenitas_engine, + params=(index, series, tenors[index]), + parse_dates=['date'], + index_col='id') + if index_quotes.empty: + continue + index_quotes.tenor = index_quotes.tenor.astype(tenor_t) + index_quotes = index_quotes.sort_values('tenor') + index_quotes['close_price'] = 1. - index_quotes['close_price'] / 100 + with conn.cursor() as c: + for value_date, data in index_quotes.groupby('date'): + yc = get_curve(value_date, "USD" if index in ["IG", "HY"] else "EUR") + # right_index?? is it a bug? + data = data.merge(df, on='tenor', right_index=True) + step_in_date = value_date + datetime.timedelta(days=1) + cash_settle_date = value_date + 3 * BDay() + start_date = previous_twentieth(value_date) + sc = SpreadCurve(value_date, yc, start_date, + step_in_date, cash_settle_date, + data.maturity.values, data.coupon.values, + data.close_price.values, + recoveries) + for r in data[['coupon', 'tenor', 'close_price']].itertuples(): + fl, fl_short = fee_legs[r.tenor] + cl, cl_short = contingent_legs[r.tenor] - duration = fl.pv(value_date, step_in_date, - cash_settle_date, yc, sc, - True) - if cl_short.end_date <= value_date.date(): - theta = None - else: - pv = index_pv(fl_short, cl_short, - value_date, step_in_date, cash_settle_date, yc, sc, - recoveries[0]) - theta = r.close_price - pv + r.coupon + duration = fl.pv(value_date, step_in_date, + cash_settle_date, yc, sc, + True) + if cl_short.end_date <= value_date.date(): + theta = None + else: + pv = index_pv(fl_short, cl_short, + value_date, step_in_date, cash_settle_date, yc, sc, + recoveries[0]) + theta = r.close_price - pv + r.coupon - c.execute("INSERT INTO index_risk VALUES(%s, %s, %s)", - (r.Index, theta, duration)) - conn.commit() -conn.close() + c.execute("INSERT INTO index_risk VALUES(%s, %s, %s)", + (r.Index, theta, duration)) + conn.commit() + conn.close() |