利用扩散模型预测财务过程

P. Płuciennik
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引用次数: 6

摘要

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。
Forecasting Financial Processes by Using Diffusion Models
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.
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