scholarly journals Volatility Model For Financial Market Risk Management : An Analysis on JSX Index Return Covariance Matrix

2006 ◽  
Author(s):  
Erie Febrian ◽  
Aldrin Herwany
Keyword(s):  
Risk Management ◽  
Covariance Matrix ◽  
Financial Market ◽  
Market Risk ◽  
Volatility Model ◽  
Financial Market Risk

scholarly journals Practical Volatility and Correlation Modeling for Financial Market Risk Management

2005 ◽  
Author(s):  
Torben Andersen ◽  
Tim Bollerslev ◽  
Peter Christoffersen ◽  
Francis Diebold
Keyword(s):  
Risk Management ◽  
Financial Market ◽  
Market Risk ◽  
Financial Market Risk

scholarly journals Practical Volatility and Correlation Modeling for Financial Market Risk Management

2013 ◽  
pp. 513-544 ◽  
Author(s):  
Torben G. Andersen ◽  
Tim Bollerslev ◽  
Peter F. Christoffersen ◽  
Francis X. Diebold
Keyword(s):  
Risk Management ◽  
Financial Market ◽  
Market Risk ◽  
Financial Market Risk

scholarly journals Practical Volatility and Correlation Modeling for Financial Market Risk Management

2005 ◽  
Author(s):  
Torben G. Andersen ◽  
Tim Bollerslev ◽  
Peter Christoffersen ◽  
Francis X. Diebold
Keyword(s):  
Risk Management ◽  
Financial Market ◽  
Market Risk ◽  
Financial Market Risk

Analyzing the Internet financial market risk management using data mining and deep learning methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ran Feng ◽  
Xiaoe Qu
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Risk Management ◽  
Deep Learning ◽  
Financial Market ◽  
Rbf Neural Network ◽  
Market Risk ◽  
The Internet ◽  
Content Type ◽  
Financial Market Risk

PurposeTo identify and analyze the occurrence of Internet financial market risk, data mining technology is combined with deep learning to process and analyze. The market risk management of the Internet is to improve the management level of Internet financial risk, improve the policy of Internet financial supervision and promote the healthy development of Internet finance.Design/methodology/approachIn this exploration, data mining technology is combined with deep learning to mine the Internet financial data, warn the potential risks in the market and provide targeted risk management measures. Therefore, in this article, to improve the application ability of data mining in dealing with Internet financial risk management, the radial basis function (RBF) neural network algorithm optimized by ant colony optimization (ACO) is proposed.FindingsThe results show that the actual error of the ACO optimized RBF neural network is 0.249, which is 0.149 different from the target error, indicating that the optimized algorithm can make the calculation results more accurate. The fitting results of the RBF neural network and ACO optimized RBF neural network for nonlinear function are compared. Compared with the performance of other algorithms, the error of ACO optimized RBF neural network is 0.249, the running time is 2.212 s, and the number of iterations is 36, which is far less than the actual results of the other two algorithms.Originality/valueThe optimized algorithm has a better spatial mapping and generalization ability and can get higher accuracy in short-term training. Therefore, the ACO optimized RBF neural network algorithm designed in this exploration has a high accuracy for the prediction of Internet financial market risk.

Risk Management Research of Financial Market Based on Dynamic Copula Model

2013 ◽  
Vol 380-384 ◽  
pp. 4472-4475
Author(s):  
Yi Xian Chai ◽  
Yan Li Xu ◽  
Dan Liu
Keyword(s):  
Risk Management ◽  
Financial Crisis ◽  
Financial Market ◽  
Financial Risk ◽  
Market Risk ◽  
Copula Model ◽  
Management Research ◽  
Financial Risk Management ◽  
Dynamic Copula ◽  
Financial Market Risk

Copula model and the application of the model in financial market risk management are discussed in this paper. The paper establishes a dynamic Copula model to solve the financial market risk management problems on the basis of Copula research. Through the use of statistics and financial theories and Copula model, the thesis studies the applications of Copula model in the financial risk management and resolves the problem whether there exists financial crisis contagion or not. The results indicate that the applications of model in the financial market risk management are effective, and the research on the problem should be done in-depth.

Study on Financial Market Risk Management Based on the Dynamic Copula Model

2011 ◽  
Vol 467-469 ◽  
pp. 2072-2077
Author(s):  
Yan Li Xu ◽  
Ling Ling Wang
Keyword(s):  
Risk Management ◽  
Financial Market ◽  
Financial Risk ◽  
Market Risk ◽  
Financial Contagion ◽  
Copula Model ◽  
Financial Risk Management ◽  
Dynamic Copula ◽  
Management Problems ◽  
Financial Market Risk

This thesis mainly studies Copula model and the application of the model in financial market risk management. On the basis of studying copula, this thesis builds a dynamic Copula model to solve the financial market risk management problems. Using statistics and financial theories and Copula model, the thesis studies applications of Copula model in the financial risk management and resolves the problem that whether the financial contagion exists. The results indicate that the applications of model in the financial market risk management are effective, and should study in deep.

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