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Abdellilah Nafia, Abdellah Yousfi and Abdellah Echaoui
In recent years, a great deal of attention has been devoted to the use of neural networks in portfolio management, particularly in the prediction of stock prices. Building a more profitable portfolio with less risk has always been a challenging task. In ...
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Hersugondo Hersugondo, Endang Tri Widyarti, Di Asih I Maruddani and Trimono Trimono
In the economic globalization era, mainly since 2010, ASEAN countries? financial and investment sectors have emerged to accelerate economic growth. The driving factor for the financial sector?s contribution is the public?s growing interest in financial a...
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Apichat Chaweewanchon and Rujira Chaysiri
With the advances in time-series prediction, several recent developments in machine learning have shown that integrating prediction methods into portfolio selection is a great opportunity. In this paper, we propose a novel approach to portfolio formation...
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I Made Akira Ivandio Agusta, Aliridho Barakbah, Arna Fariza
Pág. 279 - 293
Stock exchange trading has been utilized to gain profit by constantly buying and selling best-performing stocks in a short term. Deep knowledge, time dedication, and experience are essential for optimizing profit if stock price fluctuations are analyzed ...
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Abdellatif Moussaid, Sanaa El Fkihi, Yahya Zennayi, Ouiam Lahlou, Ismail Kassou, François Bourzeix, Loubna El Mansouri and Yasmina Imani
The overall goal of this study is to define an intelligent system for predicting citrus fruit yield before the harvest period. This system uses a machine learning algorithm trained on historical field data combined with spectral information extracted fro...
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Jaideep Singh and Matloob Khushi
Efficient Market Hypothesis states that stock prices are a reflection of all the information present in the world and generating excess returns is not possible by merely analysing trade data which is already available to all public. Yet to further the re...
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Jianguo Zheng, Yilin Wang, Shihan Li and Hancong Chen
Accurate stock market prediction models can provide investors with convenient tools to make better data-based decisions and judgments. Moreover, retail investors and institutional investors could reduce their investment risk by selecting the optimal stoc...
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Mudita Gunawan,Achmad Herlanto Anggono
Pág. 121 - 138
Safe-haven assets conserve their value or grow against another asset or portfolioduring market turmoil. Indonesian stock market, represented by the Jakarta composite index (JKSE), plunged in price because of COVID-19, pushing investors to look for&n...
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Rodgers Makwinja, Seyoum Mengistou, Emmanuel Kaunda, Tena Alemiew, Titus Bandulo Phiri, Ishmael Bobby Mphangwe Kosamu and Chikumbusko Chiziwa Kaonga
Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with incr...
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Katleho Makatjane and Ntebogang Moroke
During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alt...
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