WebSingle index model Jul. 12, 2024 • 39 likes • 27,818 views Education sharpe's single index model Sakina Ahmed Ali Follow Student at Jain university,Bangalore Advertisement Advertisement Recommended … Webcrossvalidation again fails in selecting the variables of a single-index model. However, leave-m-out crossvalidation is consistent for single-index models provided that r /nn - c E [2/3, 1), different from the requirements on m in linear regression models. Thus, no more than 1/3 of the samples should be used for model estimation, and this is ...
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WebA single index model (SIM) summarizes the effects of the explanatory variables X 1, ..., X d within a single variable called the index. As stated at the beginning of Part II, the SIM is one possibility for generalizing the GLM or for restricting the multidimensional regression E(Y X) to overcome the curse of dimensionality and the lack of interpretability. Web8 Semiparametric Single Index Models 8.1 Index Models A object of interest such as the conditional density f (y j x) or conditional mean E(y j x) is a single index model when it only depends on the vector x through a single linear combination x0 : Most parametric models are single index, including Normal regression, Logit, Probit, Tobit, maxwell city
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WebThe single-index model's formula for security i's mean return is Ri = α i + β i Rm Since Rm equals 8%, then, e.g., for security A we have: R A = α A + β A Rm = 2 + 1.5 x 8 = 2 + 12 = 14% Elton, Gruber, Brown, and Goetzmann 7-8 Modern Portfolio Theory and Investment Analysis, 7th Edition Solutions To Text Problems: Chapter 7 fSimilarly: RB = 13.4% … WebThe Single Index Model also greatly reduces the computations, since it eliminates the need to calculate the covariance of the securities within a portfolio using historical returns and the covariance of each possible pair of securities in the portfolio. WebNov 1, 2013 · Single index models are natural extensions of linear models and overcome the so-called curse of dimensionality. They have applications to many fields, such as medicine, economics and finance. However, most existing methods based on least squares or likelihood are sensitive when there are outliers or the error distribution is heavy tailed. maxwell city park iowa