One of the econometricians’ principle beliefs is that better understanding leads to better forecasts. But most of time, researchers are uncertain about what modelling strategies should be chose, what variables should be contain, and how to combine all the information to model the reality as real as possible. Moreover, combining information is usually time-costly and expense-costly. Rather than that, forecast combination combines forecasts directly and therefore save in time and expense. In addition, by combining forecasts, the technique indirectly combines the underlying information sets in each forecast figure. And thus the method takes advantage in broadening its information set, spreading risks of using certain modelling strategy, which are helpful to address the uncertain problem.
In address of the uncertainty in the market, portfolio selection diversifies portfolio (combines different assets) to reduce investment risks. By minimizing risks of a portfolio, investors assigns weights to each asset and form the optimal portfolio.
Forecast encompassing method, similar to portfolio selection in mathematical sense, minimizes forecast error of the combination formula and produces coefficients which measure the informational contribution of each model.
In face of the chaos nature in weather, ensemble forecast method is proposed to simulate possible outcomes to give a more accurate forecast. On the other front, while a better modelling strategy is unsure, the technique of combining short-term and long-term earthquake forecast models is used.
Human behavior is complex and therefore the results of psychological studies are usually conflicting. To reach an agreeable result of certain type of psychological studies, meta-analysis method is suggested. Loop analysis method gathers a cluster of models which have different ecological concerns to facilitate researchers to partially model the complex ecology system and form a satisfactory theory.
Almost all the fields covered in this thesis, except group consensus, are in face of either uncertainty problem or complex difficult. The combination techniques bring us practically acceptable results.
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