International Journal of Finance 2021-09-01T09:33:03+03:00 Journal Admin Open Journal Systems <p>International Journal of Finance is a high factor peer reviewed journal published both online and printed version by CARI. The International Journal of Finance demonstrates that finance factors cooperation shows the increasing scope of various financial management strategies in recent past and corroborates the importance of international knowledge about finance. A double blind peer review process is employed as far as the peer review of the research paper is involved which contributes to a high quality publication. It can be regarded to be one of the top academic journal publishers in the sector of publishing of finance research.</p> Autoregressive Neural Network EURO STOXX 50 Forecasting Model Based on Principal Component Stock Selection 2021-09-01T09:33:03+03:00 Ahmad Abu Alrub Tahir Abu Awwad Emad Al-Saadi <p><strong><em>Purpose:</em></strong> The given study looks into forecast accuracy of a traditional ARIMA model while comparing it to Autoregressive Neural Network (AR-NN) model for 984 trading days on EURO STOXX 50 Index.</p> <p><strong><em>Methodology:</em></strong> A hybrid model is constructed by combining ARIMA model and feed-forward neural network model aiming to attain linear and non-linear price fluctuations. The study also incorporates the investigation of component stock prices of the index, that can be selected to improve the predictability of the hybrid model.&nbsp;</p> <p><strong><em>Findings:</em></strong>The reached ARIMA (1,1,3) model showed higher scores than AR-NN model however integrating selected exogenous stock prices from the index components gave much notable accuracy results. The selected exogenous stocks were extracted after conducting PCA and model scores were compared via MAPE and RMSE.</p> <p><strong><em>Unique contribution to theory, practice and policy: </em></strong>The major contribution of this work is to provide the researcher and fnancial analyst a systematic approach for development of intelligent methodology to forecast stock market. This paper also presents the&nbsp; outlines of proposed work with the aim to enhance the performance of existing techniques. Therefore, Empirical analysis is employed along with a hybrid model based on a feed-forward Neural Network. Lesser error is attained on the test set of Index stock price by comparing the performance of ARIMA and AR-NN while forecasting. Hence, The components of extracted Index stock price like exogenous features are added to make an influence from the AR-NN model.&nbsp;</p> 2021-09-01T00:00:00+03:00 Copyright (c) 2021 International Journal of Finance Financial Factors Affecting Price-to-Earnings Ratios in Canada 2021-08-18T12:20:58+03:00 Natalia Popa Antalovschi Raymond A. K. Cox <p><strong>Purpose: </strong>The purpose of this study is to ascertain which financial factors affect the price-to-earnings ratios of Canadian firms.</p> <p><strong>Methodology: </strong>A sample of 578 Canadian firms, across 11 industries, listed on the Toronto Stock Exchange during 2011 to 2018 is examined. Stock prices and financial statements accounts data is collected from S &amp; P Capital IQ. We compute 27 financial factors to use as independent variables to regress on the price-to-earnings ratio dependent variables employing the Statistical Package for Social Sciences (SPSS) utilizing the software program’s forced, forward, and backward selection methods. Robustness tests are conducted using alternative dates (after the fiscal year end) to discover which model of financial factors best explains the forward price-to-earnings ratio as well as other statistical methods such as analysis of variance.</p> <p><strong>Results: </strong>We find a unique model for each of the 3 models based on the forward price-to-earnings ratio date. The financial factors that explain each of the dates after the end of the fiscal year (1 month, 2 months, and 3 months) are the 4 variables: net profit margin, return on investment, total asset turnover, and the natural logarithm of the total assets. For model 3 (1 month after fiscal year end), in addition to the previous 4 factors, the dividends per share is part of the regression equation. All 3 models have strong statistically significant results at an alpha level of one percent. Further, industry effects are deduced and presented.</p> <p><strong>Unique contribution to theory, policy, and practice: </strong>The results are unique to a Canadian sample of firms post- International Financial Reporting Standards (IFRS) adoption. Companies can utilize the empirical findings to manage their financial performance to maximize their price-to-earnings ratio. A product of a firm’s higher price-to-earnings ratio is a lower cost of capital which expands the corporation’s investment opportunities. Investors can apply this research to develop investment strategies hinged on price-to-earnings ratios to augment investment returns.</p> 2021-08-18T00:00:00+03:00 Copyright (c) 2021 International Journal of Finance Stochastic Forecasting of Stock Prices in Nigeria: Application of Geometric Brownian Motion Model 2021-08-16T14:32:40+03:00 Adolphus Joseph Toby Samuel Azubuike Agbam <p><strong>Purpose:</strong> &nbsp;The purpose of the study is to model and simulate the trends and behavioral patterns in The Nigerian Stock Market and hence predict the future stock prices within the Geometric Brownian Motion (GBM) framework.</p> <p><strong>Methodology:</strong> The methodology involves a comparison of forecasted daily closing prices to actual prices in order to evaluate the accuracy of the prediction model. Based on the model assumptions of the GBM with drift: continuity, normality and Markov tendency, the study investigated four years (2015 - 2018) of historical closing prices of ten stocks listed on The Nigerian Stock Exchange. The sample for this study is based on the most continuously traded stocks.</p> <p><strong>Findings: </strong>The results show that in the simulation there are some actual stock prices located outside trajectory realization that may be from GBM model. Thus, the model did not predict accurately the price behavior of some of the listed stocks.&nbsp; The predictive power of the model is declining towards the longer the evaluated time frame proven by the higher value of the mean absolute percentage error. The value of the MAPE is 50% and below for the one- to two-year holding periods, and above 50% for the three-year holding period.</p> <p><strong>Unique Contribution to theory, Practice and Policy:</strong> &nbsp;The MAPE and directional prediction accuracy method provide support that over short periods the GBM model is accurate. Meaning that the GBM is a reasonable predictive model for one or two years, but for three years, therefore, it is an inaccurate predictor. It is recommended that the technical analyst whose primary motive is to make gain at the expense of other participants should identify high volatile portfolio in any holding period for effective prediction Investors with long-range holding position as investment strategy should concentrate more on low capitalized stocks rather than stocks with large market capitalization. This is a unique contribution to theory, practice and policy.&nbsp;</p> 2021-08-16T00:00:00+03:00 Copyright (c) 2021 International Journal of Finance THE INFLUENCE OF INTENAL AUDIT ON FINANCIAL MANAGEMENT IN MARSABIT COUNTY GOVERNMENT- KENYA 2021-08-26T16:05:07+03:00 Abudo Yohana Dambala Dr. Nancy Rintari Fredrick Mutea <p><strong>Purpose</strong>: The purpose of this study was to determine the effect of internal audit on the financial management in the County Government of Marsabit.</p> <p><strong>Methodology:</strong> The study adopted descriptive survey was adopted for this study. The targeted study population was 63 staff members who are Job group K and above from the department of Finance in the directorate of Accounts, Revenue, Procurement and Internal Audit. The study employed simple structured questionnaires to gather primary data which was analyzed using SPSS.</p> <p><strong>Results:</strong> The study revealed that internal audit function had a significant influence on financial management at the county government of Marsabit (r=0.691, p=0.00)</p> <p><strong>Unique contribution to theory, policy and practice:</strong> Good financial management is very essential in protecting the public funds. This study encourages good practices of accountability, transparency and wealth creation with public funds. The study is beneficial to not only Marsabit County but other counties in Kenya. The study concludes that the Marsabit County has a functional internal audit committee and internal auditors perform their duties with great autonomy and independence. The study further concludes that internal audit has strong positive effect on the financial management in Marsabit County. The study recommends internal audit to be well staffed and resourced so that it is able to carry out regular audits of the county government. This will improve financial management of the County Government since it has been established that internal audit has strong positive effect on the financial management. Additional research can be conducted in the National government on factors influencing financial management and drawing comparisons.</p> 2021-08-26T00:00:00+03:00 Copyright (c) 2021 International Journal of Finance THE RELATIONSHIP BETWEEN LEVERAGE RISK AND PERFORMANCE OF SELECTED REAL ESTATE INVESTMENTS IN MERU COUNTY- KENYA 2021-08-18T11:57:56+03:00 Kenneth Mburugu Dr. Nancy Rintari Fredrick Mutea <p><strong>Purpose</strong>:&nbsp; The purpose of this study was to investigate the Influence of leverage risk on performance of selected real estates in Meru County Kenya.&nbsp;</p> <p><strong>Methodology:</strong> This study employed a descriptive research design. The target population comprised of 390 real estate owners and the sample size was 197 respondents. Stratified random sampling and purposive sampling procedures were used to select the sample size from the target population. Data was analyzed by use of SPSS version 23. Descriptive statistics and inferential statistics such as Regression, and Analysis of variance (ANOVA) were used to present the results in tables and figures.</p> <p><strong>Results:</strong> This study revealed statistically significant relationships between leverage risk and performance of real estate investments.&nbsp; This study established that Leverage risk had a statistically significant influence on real estate investment performance (r=.686, p&lt;0.01), (f=12.29, p&lt;0.01). However, Real estate investments was not affected by market risk since it had the least influence on its performance.</p> <p><strong>Unique contribution to theory, policy and practice:</strong> The study added value to Investors on necessity to evaluate leverage risk, as well as maintain a well-balanced capital structure when making real estate investment decisions. There is dire need for central bank of Kenya to amend lending rates specifically on mortgages. The study informed policy decision to the ministry of finance &amp; central bank of Kenya on implementing fiscal and monetary policies that create an enabling environment. A further study on determinants of leverage in real estate investments need to be done.</p> 2021-08-18T00:00:00+03:00 Copyright (c) 2021 International Journal of Finance