A support vector machine based MSM model for financial short-term volatility forecasting-Reference-Cited by-同舟云学术

A support vector machine based MSM model for financial short-term volatility forecasting

Published:2011-10-14 Issue:1 Volume:22 Page:21-28
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Wang Baohua,Huang Hejiao,Wang Xiaolong

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-011-0742-z.pdf

Reference49 articles.

1. Poon S, Granger C (2003) Forecasting volatility in financial markets: a review. J Econ Lit 41(2):478–539

2. Mandelbrot B (1974) Intermittent turbulence in self-similar cascades: divergence of high moments and dimension of the carrier. J Fluid Mech 62(02):331–358

3. Vassilicos J, Hunt J (1993) Turbulent flamelet propagation. Combus Sci Technol 87(1):291–327

4. Mandelbrot B, Fisher A, Calvet L (1997) The multifractal model of asset returns. Cowles Foundation discussion paper no. 1164, Yale University, paper available from the SSRN database at http://www.ssrn.com

5. Calvet L, Fisher A (2002) Multifractality in asset returns: theory and evidence. Rev Econ Stat 84(3):381–406

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Investigation of Swedish krona exchange rate volatilityby APARCH-Support Vector Regression;2024-06-26

2. Use of Machine Learning in Volatility: A Review Using K-Means;Revista Universidad y Empresa;2023-06-23

3. An interpretable machine-learned model for international oil trade network;Resources Policy;2023-05

4. Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression;Computational Economics;2022-05-06

5. Short-term volatility forecasting with kernel support vector regression and Markov switching multifractal model;Quantitative Finance;2021-07-12