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Prediction Errors - Bias vs Variance Conflict

As #investors, we make #errors in our #forecasts. #Financial markets are #difficult to #model and #predict because they are #complex. This #difficulty means irreducible #error is high. Irreducible error cannot be reduced. #Bias error is when a model is precise but not #accurate. Variance error is when a model is accurate but not precise. Bias error is reduced as model #complexity increases, but variance error increases. #Optimal model complexity will #balance the tradeoff between bias error and variance error to minimize the total error. #Predictivemodeling is difficult, but #fundamental and #quantitative investors alike should strive to #optimize their models. #markets #datascience #analytics #dataanalytics #investmentmanagement #cfainstitute #caia #frm