Multi-level Pattern Prediction of Unstructured Financial Data : Extended Hidden Markov Decision Model Prediction System

Language: English

Published by LAP LAMBERT Academic Publishing, 2019

6200258171 / 9786200258175

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nach der Bestellung gedruckt Neuware - Printed after ordering - Predicting the future is one aspect in designing profitable day trading strategies. Technical analysis analyses price, volume and other market information, whereas fundamental analysis looks at the facts of the company, market, currency or commodity. Most large brokerage, trading group, or financial institutions will typically have both a technical analysis and fundamental analysis team. Technical analysis is considered for the research work. The design of HMDM based stock market trend prediction system and the EHHMM for predicting the future trend of the CBOE and Nigerian 7up bottling company data is presented in this research work. Features are extracted from the historical CBOE closing price data. Extracted features are used to generate the prediction. HHMMs are useful in applications dealing with sequences of symbols. It is observed by study that the EHMDM based system is more accurate than the HMDM based system. It was observed that the EHMDM combined with EST prediction system produces a better accuracy. The HMDM combined with MAT prediction system, with hidden states, produced a lower accuracy. It can be concluded from the present study that prediction system with EHMDM.

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Title
Multi-level Pattern Prediction of Unstructured Financial Data : Extended Hidden Markov Decision Model Prediction System
Author
Kayode Akinbode
Publisher
LAP LAMBERT Academic Publishing
Publication year
2019
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6200258171
ISBN 13
9786200258175
Item weight
227 grams
Dimensions
220x150x9 mm

AHA-BUCH GmbH

Einbeck, Germany

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AbeBooks seller since August 14, 2006

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