This notebook uses a parameter scan to gauge the impact of the rebalancing seasonality effect on the QMOM strategy.
As a reminder, QMOM rebalances a month before quarter end to capture a seasonality effect caused by window dressing. Let's gauge the impact of pre-quarter-end rebalancing by comparing the peformance to standard quarter-end rebalancing:
As with the backtest, we use
segment="A"
to run the scan in 1-year segments.
from quantrocket.moonshot import scan_parameters
scan_parameters("qmom",
param1="REBALANCE_INTERVAL",
vals1=["Q-NOV", "Q"],
start_date="2010-01-01",
end_date="2018-01-01",
segment="A",
filepath_or_buffer="qmom_scan_REBALANCE_INTERVAL.csv")
Use moonchart to view a tear sheet of the scan results:
from moonchart import ParamscanTearsheet
ParamscanTearsheet.from_csv("qmom_scan_REBALANCE_INTERVAL.csv")