Industry classification is a crucial step for financial analysis. However, existing industry classification schemes have several limitations. In order to overcome these limitations, in this paper, we propose an industry classification methodology on the basis of business commonalities using the topic features learned by the Latent Dirichlet Allocation (LDA) from firms’ business descriptions. Two types of classification – firm-centric classification and industry-centric classification were explored. Preliminary evaluation results showed the effectiveness of our method
Linear Discriminant Analysis (LDA) performs well for classifica-tion of business phases – even thoug...
whether NAICS or GICS codes offer improvement over SIC codes as a methodology to identifi high-techn...
Standard sector classification frameworks present drawbacks that might hinder portfolio manager. Thi...
Industry classification is a crucial step for financial analysis. However, existing industry classif...
Industry classification is a crucial step for financial analysis. However, existing industry classif...
Purpose To overcome the shortcomings of traditional industry classification systems such as the Stan...
MasterConvergence between industries is blurring the boundaries of existing industry classification ...
Classifying companies by industry sector is an important task in finance, since it allows investors ...
This paper investigates industry classification systems. During the last 50 yearsthere has been a co...
Industry assignment, which assigns firms to industries according to a predefined industry classifica...
In this work we use clustering techniques to identify groups of firms competing in similar technolog...
This paper proposes an index to measure the industry relatedness between an origin firm and a target...
In this paper, we evaluate the self-declared industry classifications and industry relationships bet...
This paper proposes an index to measure the industry relatedness between an origin firm and a target...
Dissertation supervisor: Dr. Dan French.Includes vita.This study examines return based correlations ...
Linear Discriminant Analysis (LDA) performs well for classifica-tion of business phases – even thoug...
whether NAICS or GICS codes offer improvement over SIC codes as a methodology to identifi high-techn...
Standard sector classification frameworks present drawbacks that might hinder portfolio manager. Thi...
Industry classification is a crucial step for financial analysis. However, existing industry classif...
Industry classification is a crucial step for financial analysis. However, existing industry classif...
Purpose To overcome the shortcomings of traditional industry classification systems such as the Stan...
MasterConvergence between industries is blurring the boundaries of existing industry classification ...
Classifying companies by industry sector is an important task in finance, since it allows investors ...
This paper investigates industry classification systems. During the last 50 yearsthere has been a co...
Industry assignment, which assigns firms to industries according to a predefined industry classifica...
In this work we use clustering techniques to identify groups of firms competing in similar technolog...
This paper proposes an index to measure the industry relatedness between an origin firm and a target...
In this paper, we evaluate the self-declared industry classifications and industry relationships bet...
This paper proposes an index to measure the industry relatedness between an origin firm and a target...
Dissertation supervisor: Dr. Dan French.Includes vita.This study examines return based correlations ...
Linear Discriminant Analysis (LDA) performs well for classifica-tion of business phases – even thoug...
whether NAICS or GICS codes offer improvement over SIC codes as a methodology to identifi high-techn...
Standard sector classification frameworks present drawbacks that might hinder portfolio manager. Thi...