diff options
Diffstat (limited to 'python/analytics/curve_trades.py')
| -rw-r--r-- | python/analytics/curve_trades.py | 10 |
1 files changed, 6 insertions, 4 deletions
diff --git a/python/analytics/curve_trades.py b/python/analytics/curve_trades.py index 73afaa0f..6c20994d 100644 --- a/python/analytics/curve_trades.py +++ b/python/analytics/curve_trades.py @@ -66,8 +66,10 @@ def theta_matrix_by_series(index="IG", rolling=6): return theta_matrix[["3yr", "5yr", "7yr", "10yr"]] -def ratio_within_series(index="IG", rolling=6, param="duration"): +def ratio_within_series(index="IG", rolling=6, param="duration", max_series=None): otr = on_the_run(index) + if max_series is not None: + otr = max_series df = get_index_quotes( index, list(range(otr - rolling, otr + 1)), tenor=["3yr", "5yr", "7yr", "10yr"] ).unstack() @@ -187,9 +189,9 @@ def forward_loss(index="IG"): df["fwd_loss_rate"] = df.indexel.diff(2) / df.duration.diff(2) -def curve_model(tenor_1="5yr", tenor_2="10yr", index="IG"): +def curve_model(tenor_1="5yr", tenor_2="10yr", index="IG", max_series=None): # OLS model - df = ratio_within_series(index, param="close_spread") + df = ratio_within_series(index, param="close_spread", max_series=max_series) df = pd.concat( [ df.duration[tenor_1], @@ -204,7 +206,7 @@ def curve_model(tenor_1="5yr", tenor_2="10yr", index="IG"): ) df = np.log(df) ols_model = smf.ols( - "ratio ~ close_spread + duration1 + theta1 + theta2", data=df + "ratio ~ np.log(close_spread) + np.log(duration1) + theta1 + theta2", data=df ).fit() return df, ols_model |