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Portfolio Optimization for Stock Market in Ghana Using Value-at-Risk (VaR)
Eric Kwame Austro Gozah,
Eric Neebo Wiah,
Albert Buabeng,
Paul Yaw Addai Yeboah
Issue:
Volume 5, Issue 3, September 2020
Pages:
61-69
Received:
10 June 2020
Accepted:
23 June 2020
Published:
6 July 2020
Abstract: The study was conducted to identify the performing stocks as well as examine the portfolio optimization with associated Value at Risk (VaR) for some selected stocks on the Ghana Stock Exchange (GSE). A historical data of 15 companies categorized into Financial Stock Index (FSI) and Composite Index (CI) from 2000 to 2017 were obtained from Bank of Ghana (BoG), Ghana Stock Exchange (GSE) and Gold Coast Security (GCS). From the study, ETI, HFC, SIC, TOTAL, FML, UNIL and GOIL stocks were identified to be over performing on the Ghana Stock Exchange. Also, CAL, EBG, ALW, AYRTN, GOIL were identified as aggressive stocks; GCB, SCB, TOTAL, GGBL as defensive stocks; and ETI, HFC, SIC, FML, PZC, UNIL as inversely moving towards the market return. The optimal portfolio asset allocation, for the minimum VaR portfolio showed a marginal diversification in other stocks in the cases of FSI, but greater portion was invested in HFC. However, in the case of CI displayed no indication of diversification in the portfolio as 67.30% of investors invested in AYRTN and only 32.70% in the remaining securities. The study then proceeded to find the optimal portfolio with risk-free asset for both indexes. It was recommended that further study should extend the approaches used by considering Conditional Value at Risk (CVaR) as the VaR measure does not give any information about potential losses in the worst cases.
Abstract: The study was conducted to identify the performing stocks as well as examine the portfolio optimization with associated Value at Risk (VaR) for some selected stocks on the Ghana Stock Exchange (GSE). A historical data of 15 companies categorized into Financial Stock Index (FSI) and Composite Index (CI) from 2000 to 2017 were obtained from Bank of G...
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An SEIRD Epidemic Model for Predicting the Spread of COVID-19 over a Period of One Year: A Case of the United States
Joseph Roger Arhin,
Francis Sam,
Kenneth Coker,
Ernest Owusu Ansah
Issue:
Volume 5, Issue 3, September 2020
Pages:
70-76
Received:
26 June 2020
Accepted:
16 July 2020
Published:
28 July 2020
Abstract: COVID-19 is currently a perilous disease that has an incubation period of between 4 and 6 days. The United States Disease Control and Prevention Centers posited that in certain cases, coronaviruses are zoonotic, which means that they have been responsible for moving from animals to humans. The outbreak of the new coronavirus (COVID-19) disease has had an enormous impact globally. The World Health Organization (WHO) has put in place various safety measures that will help alleviate the spread of the epidemic. This paper presents an SEIRD epidemic model with government policy to predict the spread of COVID-19. Through mathematical analysis, the essence of the model is investigated. The basic reproductive number of the envisaged model is computed and decides whether or not the disease is present in the population. Disease-free and symptomatic equilibria are studied for their existence and stability via the Lyapunov function. It is established from our numerical simulations that the introduction of government policy helps to alleviate the spread of the disease, where the basic reproductive number takes part in sustaining their stability. In the prediction of infected and death cases that were very similar to real-life data, it was established that the model was effective.
Abstract: COVID-19 is currently a perilous disease that has an incubation period of between 4 and 6 days. The United States Disease Control and Prevention Centers posited that in certain cases, coronaviruses are zoonotic, which means that they have been responsible for moving from animals to humans. The outbreak of the new coronavirus (COVID-19) disease has ...
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Hurst Exponent Analysis on the Ghana Stock Exchange
Isaac Ampofi,
Akyene Tetteh,
Eric Neebo Wiah,
Sampson Takyi Appiah
Issue:
Volume 5, Issue 3, September 2020
Pages:
77-82
Received:
29 May 2020
Accepted:
11 June 2020
Published:
25 August 2020
Abstract: This paper talks about the application of Hurst Index on the Ghana Stock Exchange (GSE). The aim of the paper was to find out, whether GSE daily returns have some autocorrelation (long-term dependency) and multifractality using the Hurst Index analysis. Hurst Index of daily returns of some selected stocks in the period of January 2018 to December 2018 constituting 247 trading days were computed using Rescale Range Method and the Periodogram Method. The findings show that, 91.7% of the stocks considered possess long-term dependency and only 8.3% shows multifractality. Besides, the average percentage error of the geometric fractional Brownian motion (GFBM) model was 16.68% with an efficiency accuracy of 83.32% whilst that of the geometric Brownian motion (GBM) model percentage error is 20.90% with an accuracy of 79.10%. This indicates that, the GFBM model yielded better predicting accuracy than GBM in the long-run and par predicting accuracy in the short-run.
Abstract: This paper talks about the application of Hurst Index on the Ghana Stock Exchange (GSE). The aim of the paper was to find out, whether GSE daily returns have some autocorrelation (long-term dependency) and multifractality using the Hurst Index analysis. Hurst Index of daily returns of some selected stocks in the period of January 2018 to December 2...
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One Approach to the Problem of the Existence of a Solution in Neural Networks
Sargsyan Siranush,
Hovakimyan Anna
Issue:
Volume 5, Issue 3, September 2020
Pages:
83-88
Received:
7 August 2020
Accepted:
21 August 2020
Published:
16 September 2020
Abstract: Artificial neural networks are widely used to solve various applied problems. For the successful application of artificial neural networks, it is necessary to choose the correct network architecture, to select its parameters, threshold values of the elements, activation functions, etc. The problem of evaluating the neural network parameters, based on a study of the probabilistic behavior of the network is much promising. The study in the direction of developing probabilistic methods for perceptron-type pattern recognition systems is considered in different works. The concept of the characteristic function of the perceptron introduced by S. V Dayan was used by him to prove theorems on the existence of a perceptron solution. At the same time, issues of choosing a network architecture, theoretical assessment, and optimization of neural network parameters remain relevant. In this paper, we propose a mathematical apparatus for studying the relationship between the probability of correct classification of input data and the number of elements of hidden layers of a neural network. To evaluate the network performance and to estimate some parameters of the neural network such as the number of associative elements depending on the number of classification classes the mathematical expectation and variance of weights at the input of the output layer are considered. A theorem on the necessary and sufficient condition for the existence of a solution for a neural network is proved. By a solution of neural networks, the ability to recognize images with a probability other than zero is meant. The results of the proved theorem and its corollaries coincide with the results obtained by F. Rosenblat and S. Dayan for the perceptron in a different way.
Abstract: Artificial neural networks are widely used to solve various applied problems. For the successful application of artificial neural networks, it is necessary to choose the correct network architecture, to select its parameters, threshold values of the elements, activation functions, etc. The problem of evaluating the neural network parameters, based ...
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Surface Roughness and Density Effects in Thermal Elastohydrodynamic Lubrication Point Contacts
Samuel Macharia Karimi,
Mathew Ngugi Kinyanjui,
Mark Kimathi
Issue:
Volume 5, Issue 3, September 2020
Pages:
89-96
Received:
28 August 2020
Accepted:
10 September 2020
Published:
19 September 2020
Abstract: Elastohydrodynamic lubrication is a type of lubrication which most machine elements such as bearings operate. Density changes, thermal and surface roughness effects are also key factors in bearings, working under heavy loads and high speeds. Previous research has focused on smooth surfaces where density and thermal effects have been neglected. The present study intends to model the effect of surface roughness and density on thermal elastohydrodynamic lubrication for sliding-rolling bearing using non-Newtonian lubricant. The surface roughness is incorporated into the film thickness equation while the non-Newtonian nature of the lubricant is incorporated into the Reynolds and energy equation by using the Eyring model. The changes in compressibility of the lubricant is given by the lubricant’s density equation. The energy equation is solved simultaneously with the Reynolds-Eyring equation, film thickness, density and viscosity of lubricant equations. The equations are then discretized using the finite difference numerical method and are solved simultaneously in Matlab together with their boundary conditions. It is noted that an increase in surface roughness results to a reduction in the film thickness and an increase in both temperature and pressure. Increase in temperature lowers the density of the lubricant while increase in pressure leads to an increase in density. It is also noted that an increase in the density of the lubricant leads to an increase in the film thickness. The temperature profile shows that as the load in the bearing is increased, the temperature of the lubricant also increases.
Abstract: Elastohydrodynamic lubrication is a type of lubrication which most machine elements such as bearings operate. Density changes, thermal and surface roughness effects are also key factors in bearings, working under heavy loads and high speeds. Previous research has focused on smooth surfaces where density and thermal effects have been neglected. The ...
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