Statistical and NN Forecasting Models of Financial Data: Making Inferences about the Accuracy and Risk Evaluation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F11%3A%230004056" target="_blank" >RIV/47813059:19240/11:#0004056 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.oldcitypublishing.com/MVLSC/MVLSC.html" target="_blank" >http://www.oldcitypublishing.com/MVLSC/MVLSC.html</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Statistical and NN Forecasting Models of Financial Data: Making Inferences about the Accuracy and Risk Evaluation

Popis výsledku v původním jazyce

For both accurate and easy risk consideration in decision making, it is necessary to have flexible and soft methods that adapt to the input data and problem conditions. In this paper, we consider the accuracy of forecasting models based on statistical (stochastic) methods sometimes called hard computing and soft methodology based on the soft or granular computing. A new method for finding the forecasting horizon within which the risk is minimal is also presented. To evaluate the risk we used methods based on the analysis of forecast errors by applying the exponential smoothing concept. It is also found that the risk estimation process based on soft methods is simplified and less critical to the question whether the data is true crisp or white noise

Název v anglickém jazyce

Statistical and NN Forecasting Models of Financial Data: Making Inferences about the Accuracy and Risk Evaluation

Popis výsledku anglicky

For both accurate and easy risk consideration in decision making, it is necessary to have flexible and soft methods that adapt to the input data and problem conditions. In this paper, we consider the accuracy of forecasting models based on statistical (stochastic) methods sometimes called hard computing and soft methodology based on the soft or granular computing. A new method for finding the forecasting horizon within which the risk is minimal is also presented. To evaluate the risk we used methods based on the analysis of forecast errors by applying the exponential smoothing concept. It is also found that the risk estimation process based on soft methods is simplified and less critical to the question whether the data is true crisp or white noise

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

<a href="/cs/project/GA402%2F08%2F0022" target="_blank" >GA402/08/0022: Nejnovější inteligentní metodologie pro modelování a predikci ekonomických časových řad</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Mult.-Valued Logic & Soft Computing

ISSN

1542-3980

e-ISSN

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Svazek periodika

17

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

321-337

Kód UT WoS článku

000291082800004

EID výsledku v databázi Scopus

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