Monte Carlo simulations such as Adaptive’s Forward Test tool are only as good as their assumptions about the probability of what is being simulated.
If these assumptions are incorrect or poorly calibrated, the simulation results may be inaccurate or misleading. To address this, it is important to use realistic and well-calibrated inputs, and to perform sensitivity analysis to test the robustness of the results to different assumptions.
Please contact us for more technical information. Forecasting tools tend to assume long-term growth in stocks, in keeping with long-term trends. Adaptive’s Forward Test, however, does not currently assume growth—instead it assumes a market on the whole that goes nowhere even though this likely underestimates the gains in long-term portfolios. Some of other Adaptive’s inputs include: historical returns for correlation estimates; implied volatility for calculating forward returns; and historical volatility, in part as a sanity check for implied volatility calculations.