COMPARATIVE STUDY OF ESTIMATION POWER OF ARTIFICIAL NEURAL NETWORKS AND AUTOREGRESSIVE TIME SERIES MODELS IN INFLATION FORECASTING

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HANAFIZADEH PAYAM; POURSOLTANI HOSSEIN; SAKETI PARISA

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Journal: Journal of Economic Research Year:2008 | Volume:- | Issue:81 Page(s): 25-35

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Information Journal Paper

Title

COMPARATIVE STUDY OF ESTIMATION POWER OF ARTIFICIAL NEURAL NETWORKS AND AUTOREGRESSIVE TIME SERIES MODELS IN INFLATION FORECASTING

Author(s)

HANAFIZADEH PAYAM | POURSOLTANI HOSSEIN | SAKETI PARISA | Issue Writer Certificate

Keywords

FORECASTINGQ2

INFLATIONQ2

MODEL SELECTIONQ3

NEURAL NETWORKQ2

TIME SERIESQ2

Abstract

This article is a comparative study of estimation power of artificial NEURAL NETWORKs and autoregressive TIME SERIES models in INFLATION FORECASTING. Using 37 years Iran’s INFLATION data, NEURAL NETWORKs performs better on average for short horizons than autoregressive models. This study shows usefulness of early stopping technique in learning stage of NEURAL NETWORKs for estimating TIME SERIES.

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APA: Copy

HANAFIZADEH, PAYAM, POURSOLTANI, HOSSEIN, & SAKETI, PARISA. (2008). COMPARATIVE STUDY OF ESTIMATION POWER OF ARTIFICIAL NEURAL NETWORKS AND AUTOREGRESSIVE TIME SERIES MODELS IN INFLATION FORECASTING. TAHGHIGHAT-E-EGHTESADI, -(81), 25-35. SID. https://sid.ir/paper/12019/en

Vancouver: Copy

HANAFIZADEH PAYAM, POURSOLTANI HOSSEIN, SAKETI PARISA. COMPARATIVE STUDY OF ESTIMATION POWER OF ARTIFICIAL NEURAL NETWORKS AND AUTOREGRESSIVE TIME SERIES MODELS IN INFLATION FORECASTING. TAHGHIGHAT-E-EGHTESADI[Internet]. 2008;-(81):25-35. Available from: https://sid.ir/paper/12019/en

IEEE: Copy

PAYAM HANAFIZADEH, HOSSEIN POURSOLTANI, and PARISA SAKETI, “COMPARATIVE STUDY OF ESTIMATION POWER OF ARTIFICIAL NEURAL NETWORKS AND AUTOREGRESSIVE TIME SERIES MODELS IN INFLATION FORECASTING,” TAHGHIGHAT-E-EGHTESADI, vol. -, no. 81, pp. 25–35, 2008, [Online]. Available: https://sid.ir/paper/12019/en

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