Forecast Confidence

Forecast confidence, also known as forecast certainty, indicates your confidence in the input investment forecast. (The forecast includes risk and return estimates, but not trading costs, quadratic penalties, or constraints).  Numerically it is on a scale with 0 representing no information (FC must technically be greater than 0, but 0.1 or greater is allowed), and 11 representing perfect confidence, i.e. Markowitz Classical Mean-Variance optimization. The numerical setting is displayed in the Forecast Confidence Field on the New Frontier ribbon.

The Optimizer relies on the forecast confidence level to determine the degree of dispersion of the resampling distribution and thus the variability among simulated efficient frontiers.  With a high level of confidence, generally 8 and above, the optimal portfolios resemble the classical and the rebalance test applies small statistical indifference regions and a narrow resampling dispersion.  This means that the rebalance test will be less tolerant of deviations from optimality and the confidence interval for portfolio weight ranges will narrow.  With a low level of confidence, the Optimizer applies large regions of equivalence and a wide resampling dispersion.  See the Information Correlation and Forecast Confidence description below for more information.

Toggle the Forecast Confidence drop down menu in the Optimize Section of the ribbon to adjust the confidence level.  You can also type in your forecast confidence, which permits you to enter a decimal point and specify non-integer values for forecast confidence.

If you set a classical confidence level (11), the Optimizer doesn't perform any simulations to correct for estimation error; you do not have to set the number of simulations in that situation.

The Ledoit Covariance Estimation option is enabled automatically when you have low forecast confidence in a case where the number of assets might exceed the number of simulated returns to determine resampled inputs.