Forecasting Financial Processes by Using Diffusion Models

Piotr Pluciennik ()
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Piotr Pluciennik: Adam Mickiewicz University

Dynamic Econometric Models, 2010, vol. 10, 51-60

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.

Keywords: diffusion models; ex-post forecasts; Monte-Carlo simulation; the GARCH model; the ARIMA model; unit-root. (search for similar items in EconPapers)
Date: 2010
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