Calculation window

Also seen as: In-sample (the field label in the strategy editor), lookback, lookback window, in-sample period, estimation window

What does the calculation window change?

The calculation window changes the weights a method produces without changing the method itself, because it changes the span of history the method measures over. The app's own note reads: "Historical window used by the active method for volatility, correlation, beta, and similar calculations. Default 12." A short window makes the weights react quickly to recent conditions and shift noticeably from one rebalance to the next; a long window averages across more market regimes and produces steadier weights that respond slowly. Neither is more correct than the other — they answer different questions about the same instruments.

The window is measured backwards from each rebalance date inside the backtest, not from today, so a method using a 12-month window at a rebalance in March 2015 reads 2014–2015 data, not recent data.

Which allocation methods read the calculation window?

Ranking-Based is the conditional case: it reads the window when its ranking metric is Price Change, Volatility or Sharpe Ratio, and ignores it for Average Momentum and P/E Ratio. When the active method does not read the window, the In-sample field is not displayed at all — there is nothing for it to set.

Defaults in Fincanva

• The default is 12 months. The field takes whole months with a minimum of 1 and no fixed ceiling; the unit shown beside it is "mo".
• The window belongs to the allocation profile, so a strategy that has a Risk-Off allocation can read one window in Risk-On and a different one in Risk-Off.
• Beta Neutral carries a second, separate window — its Ranking calculation window — for the metric it ranks on, while the profile's calculation window controls its beta estimation. The app spells the split out: "How far back the ranking metric reads — distinct from the Calculation window above, which controls the beta-estimation window."
• Changing the window changes a strategy's inputs, so the backtest has to be run again before the results reflect it.

Worked example

A strategy holds five ETFs and uses Inverse Volatility, which gives each holding a weight inversely proportional to its risk. With the calculation window at 6 months, the weights are set from the last six months of returns: an ETF that was turbulent through that half-year but calm before it measures as high-risk and receives a small weight. Change the window to 24 and that same turbulent half-year is averaged against eighteen quieter months, so its measured volatility falls and its weight rises. Same method, same five ETFs, same rebalance date — a different allocation, purely because the method was shown a different span of history.