diff options
Diffstat (limited to 'python/exploration/curve_trades.py')
| -rw-r--r-- | python/exploration/curve_trades.py | 26 |
1 files changed, 20 insertions, 6 deletions
diff --git a/python/exploration/curve_trades.py b/python/exploration/curve_trades.py index 4e99fc94..fa545b21 100644 --- a/python/exploration/curve_trades.py +++ b/python/exploration/curve_trades.py @@ -17,16 +17,10 @@ spreads_diff.plot() df = index_returns(index='IG', series=[24, 25, 26, 27, 28], tenor=['3yr', '5yr', '7yr', '10yr']) ## on-the-run returns returns = df.price_return.unstack(-1).dropna().groupby(level='date').nth(-1) -<<<<<<< Updated upstream -strategy510 = returns['5yr'] - 0.56 * returns['10yr'] -strategy710 = returns['7yr'] - 0.75 * returns['10yr'] -strategy3510 = -2*returns['3yr']+3*returns['5yr'] - returns['10yr'] -======= strategy510 = 1.78 * returns['5yr'] - returns['10yr'] strategy710 = 1.33 * returns['7yr'] - returns['10yr'] strategy3510 = -2 * returns['3yr']+ 3 * returns['5yr'] - 1 * returns['10yr'] ->>>>>>> Stashed changes monthly_returns510 = strategy510.groupby(pd.TimeGrouper(freq='M')).agg(lambda df:(1+df).prod()-1) monthly_returns710 = strategy710.groupby(pd.TimeGrouper(freq='M')).agg(lambda df:(1+df).prod()-1) monthly_returns3510 = strategy3510.groupby(pd.TimeGrouper(freq='M')).agg(lambda df:(1+df).prod()-1) @@ -42,3 +36,23 @@ monthly_sharpe3510 = monthly_returns3510.mean()/monthly_returns3510.std()*math.s worst_drawdown510 = strategy510.nsmallest(10) worst_drawdown710 = strategy710.nsmallest(10) worst_drawdown3510 = strategy3510.nsmallest(10) + +def forward_loss(): + from db import dbengine, dbconn + serenitasdb = dbengine('serenitasdb') + index = 'IG' + start_date = (pd.Timestamp.now() - pd.DateOffset(years=3)).date() + + df = pd.read_sql_query("SELECT date, index, series, tenor, duration, closespread, closespread*duration/100 as indexel " \ + "FROM index_quotes WHERE index=%s AND date >= %s " \ + "ORDER BY date DESC, series ASC, duration ASC", + serenitasdb, parse_dates=['date'], params=[index, start_date]) + df1 = pd.read_sql_query("select index, series, tenor, maturity from index_maturity", serenitasdb, parse_dates=['maturity']) + + df = df.merge(df1, on=['index','series','tenor']) + df = df.set_index(['date','index', 'maturity']).dropna() + df = df.groupby(level=['date','index', 'maturity']).nth(-1) + # annual change, to take out some noise + df['fwd_loss_rate'] = df.indexel.diff(2)/df.duration.diff(2) + + |