scholarly journals Relationship between Capital Operation and Market Value Management of Listed Companies Based on Random Forest Algorithm

2017 ◽  
Vol 108 ◽  
pp. 1271-1280 ◽  
Author(s):  
Wen Long ◽  
Linqiu Song ◽  
Lingxiao Cui
2016 ◽  
Vol 8 (11) ◽  
pp. 124
Author(s):  
Yaqian Pan ◽  
Wenxin Song ◽  
Yanjun Xv

<p>Since 2005, China has implemented the split-share reform. After entering the full-circulation era of stock equity, the pursuit for maximize the company value has turned into the primary goal of listed companies in the course of their management and development. Thus, they attach great importance to the concept of market value management. The management of stockholders in listed companies began to pay attention to the inner values and the performances in the stock market of their enterprises, and thereby the concept of market value management is established. However, the weak efficiency of China’s capital market has resulted in the deviation between market values and inner values of companies. Thus, companies need to implement market value management and devise corresponding solutions so that two kinds of values can be well-matched.</p>This paper presents the definition of market value management at first. Next, it studies the background of the emergence of market value management as well as its development status in China, which are also compared with the overseas value management. And then, it makes a literature review and analyzes Economic Value Added Evaluation System (EVA), a performance evaluation system of market value management. It adopts the method of Rank Sum Ratio (RSR)and Principal Component Analysis to make empirical analyses,which evaluates the level of market value management of listed companies in China and discovers the weak links existing in the process of market value management .This paper eventually puts forward corresponding countermeasures and suggestions.


Author(s):  
A.E. Semenov

The method of pedestrian navigation in the cities illustrated by the example of Saint-Petersburg was investigated. The factors influencing people when they choose a route for their walk were determined. Based on acquired factors corresponding data was collected and used to develop model determining attractiveness of a street in the city using Random Forest algorithm. The results obtained shows that routes provided by the method are 14% more attractive and just 6% longer compared with the shortest ones.


2020 ◽  
Vol 15 (S359) ◽  
pp. 40-41
Author(s):  
L. M. Izuti Nakazono ◽  
C. Mendes de Oliveira ◽  
N. S. T. Hirata ◽  
S. Jeram ◽  
A. Gonzalez ◽  
...  

AbstractWe present a machine learning methodology to separate quasars from galaxies and stars using data from S-PLUS in the Stripe-82 region. In terms of quasar classification, we achieved 95.49% for precision and 95.26% for recall using a Random Forest algorithm. For photometric redshift estimation, we obtained a precision of 6% using k-Nearest Neighbour.


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