Journal of
Systemics, Cybernetics and Informatics
 



ISSN: 1690-4524 (Online)


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Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Editors

Journal's Reviewers
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Behavior of Cell in Uniform Shear Flow Field between Rotating Cone and Stationary Plate
Shigehiro Hashimoto, Hiromi Sugimoto, Haruka Hino
(pages: 1-7)

Teachers Continuing Professional Development: Trends in European Countries. Towards Teachers' Professionalism
Liliana Budkowska, Pawel Poszytek
(pages: 8-12)

Play, Connect and Learn: Using Mobile Phones to Improve Early Grade Reading Skills at Home
Ira Joshi
(pages: 13-16)

May Parental Reading Behavior Explain the Gender Differences in Subteeners’ Reading Attitude?
Aniko Joó, Erzsébet Dani
(pages: 17-22)

Leadership and Literacy Processes in School Improvement Creating and Supporting a Community of Success: A Case Study Examining the Principal’s Role in the Reconstitution of a Campus to Transform Literacy and Learning
W. Todd Duncan, Lisa E. Colvin
(pages: 23-28)

Rwandan Collaborative Model for Educator Capacity Building
Andrew Moore, Vincentie Nyangoma, Jaco Du Toit, Peter Wallet, Pascal Rukundo
(pages: 29-35)

Do You Know Where Your Students Are? Digital Supervision and Digital Privacy in Schools
Lorayne Robertson, Laurie Corrigan
(pages: 36-42)

A General Case Study of Complexity Science: Analytical and Logical Interconnection Between Soft and Hard Sciences (Invited Paper)
Jack Jia-Sheng Huang, Yu-Heng Jan
(pages: 43-48)

Novel Application of Immobilized Bacillus Cells for Biotreatment of Furfural-Laden Wastewater
Haneen A. Khudhair, Zainab Z. Ismail
(pages: 49-54)

Reliable Sub-Nanosecond Switching of a Perpendicular SOT-MRAM Cell without External Magnetic Field
Viktor Sverdlov, Alexander Makarov, Siegfried Selberherr
(pages: 55-59)

The Methodology and Implementation of Unique Technology Focused Entrepreneurship/Intrepreneurship Programs
Stephen A. Szygenda, Diana M. Easton
(pages: 60-66)

Intelligent Fault Pattern Recognition of Aerial Photovoltaic Module Images Based on Deep Learning Technique
Xiaoxia Li, Qiang Yang, Wenjun Yan, Zhebo Chen
(pages: 67-71)

Real-Time Implementation of Model Predictive Control in a Low-Cost Embedded Device
John Espinoza, Jorge Buele, Esteban X. Castellanos, Marco Pilatásig, Paulina Ayala, Marcelo V. García
(pages: 72-77)

Real-Time Sentimental Polarity Classification on Live Social-Media
Khalid N. Alhayyan, Imran Ahmad
(pages: 78-84)

Information Modeling and Information Retrieval for the Internet of things (IoT) in Buildings
Renata Baracho, Izabella Cunha, Mário Lúcio Pereira Junior
(pages: 85-91)


 

Abstracts

 


ABSTRACT


Parallel Prediction of Stock Volatility

Priscilla Jenq, John Jenq


Volatility is a measurement of the risk of financial products. A stock will hit new highs and lows over time and if these highs and lows fluctuate wildly, then it is considered a high volatile stock. Such a stock is considered riskier than a stock whose volatility is low. Although highly volatile stocks are riskier, the returns that they generate for investors can be quite high. Of course, with a riskier stock also comes the chance of losing money and yielding negative returns. In this project, we will use historic stock data to help us forecast volatility. Since the financial industry usually uses S&P 500 as the indicator of the market, we will use S&P 500 as a benchmark to compute the risk. We will also use artificial neural networks as a tool to predict volatilities for a specific time frame that will be set when we configure this neural network. There have been reports that neural networks with different numbers of layers and different numbers of hidden nodes may generate varying results. In fact, we may be able to find the best configuration of a neural network to compute volatilities. We will implement this system using the parallel approach. The system can be used as a tool for investors to allocating and hedging assets.

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