Duration Weighted Strategy

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Environment

import sigtech.framework as sig

import pandas as pd
import datetime as dtm
import seaborn as sns

sns.set(rc = {'figure.figsize': (18, 6)})
env = sig.init(env_date=dtm.date(2024, 2, 22))

Define the universe

start_date = dtm.date(2018, 1, 5)
group = sig.obj.get('US GOVT BOND GROUP')
tenors = ['30Y', '5Y']

def create_otr(group: str, tenor: str, start_date: dtm.date) -> sig.RollingBondStrategy:
    return sig.RollingBondStrategy(
        # Assing the country of the bond group
        country=group.country,

        # The strategy denomination currency
        currency='USD',

        # Which bonds to be used as part of the strategy,
        # could e.g. be 'ON_THE_RUN', 'FIRST_OFF_THE_RUN',
        # 'SECOND_OFF_THE_RUN' etc.
        run_type='ON_THE_RUN',

        # Start date of strategy
        start_date=start_date,

        # Tenor of strategy
        tenor=tenor,

        # Name of strategy
        ticker=f'{tenor} {group.country} OTR'
    )

otr_dict = {
    tenor: create_otr(group, tenor, start_date)
    for tenor in tenors
}

Create the strategy

dur_dict = {
    tenor: otr_dict[tenor].ann01_series()
    for tenor in tenors
}

df= pd.DataFrame({otr_dict['5Y'].name:-(dur_dict['30Y']/dur_dict['5Y']),otr_dict['30Y'].name:1}).dropna()
df.head()

Construct the portfolio

signal_obj = sig.signal_library.from_ts(df)
signal_obj

duration_weighted_strat = sig.SignalStrategy(
    # Start date of strategy
    start_date=start_date,

    # Currency in which the strategy is denominated in
    currency='USD',

    # Reference to the signal object
    signal_name=signal_obj.name,

    # On the instruments which have a negative weight,
    # refrain from creating a short version of that
    # instrument
    convert_long_short_weight=False
)

Generate the performance report

sig.PerformanceReport(duration_weighted_strat.history()).report()