Set out the obstacles an analyst meets when producing forecasts for capital markets

Problems sit in the data, the methods and the analyst. Economic data arrive with lags, are revised and rebased. Series suffer transcription errors, survivorship bias and appraisal smoothing, which makes private assets look less volatile and less correlated than they are. History may span different regimes, so a long sample is not automatically better; realised risk can be a poor guide to future risk when a rare event did not happen in the sample (the peso problem). Data mining and time-period bias create false patterns, and ignoring conditioning information hides how relationships change with the state of the economy. Finally anchoring, confirmation, status quo and overconfidence bias distort judgement. A good answer names the specific distortion and its remedy.