Forecasting Financial Processes by Using Diffusion Models

P. Płuciennik
{"title":"Forecasting Financial Processes by Using Diffusion Models","authors":"P. Płuciennik","doi":"10.12775/DEM.2010.005","DOIUrl":null,"url":null,"abstract":"Time series forecasting is one of the most important issues in the financial econometrics. In the face of growing interest in models with continuous time, as well as rapid development of methods of their estimation, we try to use the diffusion models to modeling and forecasting time series from various financial markets. We use Monte-Carlo-based method, introduced by Cziraky and Kucherenko (2008). Received forecasts are confronted with those determined with the commonly applied parametrical time series models.","PeriodicalId":31914,"journal":{"name":"Dynamic Econometric Models","volume":"10 1","pages":"51-60"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dynamic Econometric Models","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12775/DEM.2010.005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

Time series forecasting is one of the most important issues in the financial econometrics. In the face of growing interest in models with continuous time, as well as rapid development of methods of their estimation, we try to use the diffusion models to modeling and forecasting time series from various financial markets. We use Monte-Carlo-based method, introduced by Cziraky and Kucherenko (2008). Received forecasts are confronted with those determined with the commonly applied parametrical time series models.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用扩散模型预测财务过程
时间序列预测是金融计量经济学中的重要问题之一。面对人们对连续时间模型的日益关注,以及对其估计方法的快速发展,我们尝试使用扩散模型对来自各种金融市场的时间序列进行建模和预测。我们使用由Cziraky和Kucherenko(2008)引入的蒙特卡罗方法。接收到的预报与常用的参数时间序列模型确定的预报相矛盾。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
2 weeks
期刊最新文献
Energy Consumption and Economic Growth in Ethiopia: Evidence from ARDL Bound Test Approach Demonetisation as an Economic Policy Tool: Macroeconomic Implications of a Monetary Market Shock. The Example of the Indian Monetary Reform Impact of Export and Import on Economic Growth: Time Series Evidence from India Revisiting the Import Demand Function: A Comparative Analysis Impact of the Sector and of Internal Factors on Profitability of the Companies Listed on the Warsaw Stock Exchange
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1