Forecasting Financial Processes by Using Diffusion Models | Zendy

Piotr Płuciennik | Zendy

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Forecasting Financial Processes by Using Diffusion Models

Author(s) -

Piotr Płuciennik

Publication year - 2010

Publication title -

dynamic econometric models

Language(s) - English

Resource type - Journals

eISSN - 2450-7067

pISSN - 1234-3862

DOI - 10.12775/dem.2010.005

Subject(s) - series (stratigraphy) , econometrics , diffusion , monte carlo method , financial econometrics , financial market , finance , time series , computer science , estimation , financial modeling , economics , mathematics , statistics , machine learning , indirect finance , physics , thermodynamics , paleontology , management , biology

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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