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Model selection is the task of selecting a model from among various candidates on the basis of performance criterion to choose the best one. [1] In the context of machine learning and more generally statistical analysis , this may be the selection of a statistical model from a set of candidate models, given data.
The assumption of constant investment opportunities can be relaxed. This requires a model for how ,, change over time. An interest rate model could be added and would lead to a portfolio containing bonds of different maturities. Some authors have added a stochastic volatility model of stock market returns.
The Gated Three-Tower Transformer (GT3) is a transformer-based model designed to integrate numerical market data with textual information from social sources to enhance the accuracy of stock market predictions. [12] Since NNs require training and can have a large parameter space; it is useful to optimize the network for optimal predictive ability.
Stock selection is the value added by decisions within each sector of the portfolio. In this case, the superior stock selection in the equity sector added 1.40% to the portfolio's return [(5% − 3%) × 70%]. Interaction captures the value added that is not attributable solely to the asset allocation and stock selection decisions.
In finance, Jensen's alpha [1] (or Jensen's Performance Index, ex-post alpha) is used to determine the abnormal return of a security or portfolio of securities over the theoretical expected return. It is a version of the standard alpha based on a theoretical performance instead of a market index .
The result was an asset allocation model that PRI licensed Brian Rom to market in 1988. Mr. Rom coined the term PMPT and began using it to market portfolio optimization and performance measurement software developed by his company. These systems were built on the PRI downside- risk algorithms.