Firm Size, Operational Risk and Performance: Evidence from Commercial and Services Companies Listed in Nairobi Securities Exchange

2019 ◽  
Vol 3 (VI) ◽  
pp. 372-379
Author(s):  
Susan Kerubo Onsongo ◽  
Stephen Muathe ◽  
Lucy Mwangi
Keyword(s):  
Risk Management ◽  
Financial Performance ◽  
Firm Size ◽  
Random Effect ◽  
Random Effect Model ◽  
Operational Risk ◽  
Target Population ◽  
Annual Reports ◽  
Operational Risks ◽  
And Performance

The study sought to assess the financial performance of the companies listed in the commercial and services sector at the Nairobi Securities Exchange (NSE), Kenya with an aim of determining the implications of firm size and operational risk on their performance. It was anchored on the agency theory. The study applied explanatory research design and the target population was the 14 companies listed under this sector. Secondary panel data contained in published annual reports for the year 2013 to 2017 was collected. A panel regression model was applied with the random effect model being used based on the Hausman specification test. Findings showed that operational risk had a positive insignificant effect on performance as proxied by return on assets (ROA). The findings further showed that firm size had a moderating effect on the relationship between operational risks and performance. It concluded that firm size played a role in the risk management of a company i.e. companies with higher total assets managed risk better than their counterpart. The study recommends that for companies to record improved financial performance, they needed to manage their operational risks by implementing risk management initiatives and increasing their total assets base.   

scholarly journals Intellectual Capital and its Impact on Financial Performance: A Study of Oil and Gas Sector of Pakistan

2014 ◽  
Vol 43 ◽  
pp. 125-140 ◽  
Author(s):  
Muhammad Arslan ◽  
Rashid Zaman
Keyword(s):  
Financial Performance ◽  
Intellectual Capital ◽  
Significant Relationship ◽  
Oil And Gas ◽  
Random Effect ◽  
Random Effect Model ◽  
Value Added ◽  
Annual Reports ◽  
Tangible Assets ◽  
Oil And Gas Sector

The study examines the Intellectual Capital (IC) performance of oil and gas sector of Pakistan over the period of 2007 to 2011 and its impact on corporate financial returns. The study uses value added intellectual coefficient (VAICitTM) to measure IC performance and its various components of VAICitTM like (HCEit, SCEit and CEEit) and its impact on financial performance (ROEit, ROIit and EPSit). Micro panel data of oil and gas sector registered in KSE-100 index is collected from their consolidated annual reports over the period of 2007 to 2011. The IC performance is measured by Ante Pulic Model (VAICitTM) and its effect on corporate returns (ROEit, ROIit and EPSit) is tested by Random Effect Model estimation. Hausman test suggests that study accepts null hypothesis (Chi2. Prop > 0.05) where for ui is uncorrelated with regressor means that random effect is preferred versus alternative fixed effect in all the proposed research models. The study reveals that VA is considered an important component for measuring the VAICitTM performance and it has positive and significant relationship with firm’s profitability (EPSit) and HCEit and SCEit have positive and significant relationship with firm’s financial performance (ROEit and ROIit) respectively. So, this study explores that Intellectual Capital Efficiency (ICE) has relatively larger contribution for measuring the VAICitTM performance where HCEit and SCEit execute substantive role to accelerate the financial performance of oil and gas sector of Pakistan as compare to tangible assets.

scholarly journals Competitive Intelligence Practices And Performance Of Firms Listed On The Nairobi Securities Exchange, Kenya

2016 ◽  
Vol 12 (19) ◽  
pp. 107
Author(s):  
Paul Waithaka
Keyword(s):  
Financial Performance ◽  
Secondary Data ◽  
Target Population ◽  
Business Environment ◽  
Competitive Intelligence ◽  
Annual Reports ◽  
Primary Data ◽  
Financial Measures ◽  
Listed Firms ◽  
And Performance

Performance is critical for every listed firm, as it enhances shareholder’s value and capability to generate earnings from invested capital. Some of the firms listed on the Nairobi Securities Exchange (NSE) have been performing poorly as indicated by the rising number of firms issuing profit warnings. The competitive business environment is continuously working to drive down the rate of return on invested capital. To counter these competitive forces, firms have resorted to gathering information at their disposal and converting it into competitive intelligence through analysis and human judgment. This study sought to determine the effect of competitive intelligence practices on performance of firms listed on the NSE. Firm performance was evaluated using both financial and non-financial measures. The non-financial measures used in the study were goal achievement and customer satisfaction, while Return on Assets (ROA) and Return on Equity (ROE) were the financial measures used. The target population was the sixty firms listed on the Nairobi securities exchange. Primary data was collected using a semi-structured questionnaire; while secondary data was obtained from the firm’s published annual reports available at the NSE using a document review guide. Quantitative data was analyzed using both descriptive and inferential statistics. The findings indicate that competitive intelligence practices have a positive and a statistically significant effect on the non-financial performance of firms listed on the Nairobi Securities Exchange. The intelligence practices were found to have a positive but statistically insignificant effect on the financial performance of listed firms. Managers of listed firms should raise the utilization level of competitive intelligence practices to enable the firms to make accurate predictions on changes in the business environment, compete better in the marketplace against rivals, improve on innovation and automation, track competitors’ activities and improve the competitiveness of their firms by identifying threats and opportunities before they become obvious. The study suggests that future researches should focus on extending knowledge on competitive intelligence practices to non-listed corporate sector firms to support the generalization of the findings to all sectors in the economy.

scholarly journals EFFECT OF USAGE OF DERIVATIVE FINANCIAL INSTRUMENTS ON FINANCIAL PERFORMANCE OF NON-FINANCIAL FIRMS

2018 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
Mercelline Nafula Waswa ◽  
Dr. Joshua Matanda Wepukhulu
Keyword(s):  
Risk Management ◽  
Financial Performance ◽  
Financial Risk ◽  
Financial Structure ◽  
Target Population ◽  
Time Frame ◽  
Annual Reports ◽  
Unique Contribution ◽  
Financial Firms ◽  
The Impact

Purpose: The purpose of this study is to examine the effect of derivative financial instrument utilization on the financial performance of non-financial firms recorded at the Nairobi Securities Exchange. The objectives that guided this study are to assess the impact of use of derivatives in risk management on financial performance of non-financial firms listed on the Nairobi Securities Exchange (NSE). Methodology: The study embraced the regression model. A census of all the 47 non-financial firms listed at the NSE as at December 2017 constituted the target population where only 11 listed non-financial firms were financial derivative instruments users. The study utilized qualitative and quantitative research techniques especially the utilization of descriptive research design. The data for this study was collected using questionnaires, audited financial statements and annual reports of individual firms for the multi year time frame covering 2013-2017 (the two years comprehensive). Results: The study discovered that greater part of the firms (66.67%) utilizes Forwards, 22.22% utilize Swaps and 11.11% utilize Futures and Options for financial risk management. From the study the outcomes were as per the following: presence of debt in the financial structure of the non-financial firms listed at the NSE does not influence its financial performance as estimated by return on assets (ROA), use of derivatives in efficiency in trading influences the financial performance of the firms, use of derivatives in price stabilization is statistically significant and utilization of derivatives in price discovery does not influence the financial performance of the firms. By and large, the performance of the recorded non-financial firms at the NSE amid the time of study was 8.13 with a standard deviation of 10.67. Unique contribution to Theory, Practice and Policy: The study recommended that firms should combine both debt and equity in their financial structure. It is therefore incumbent on firms’ managers and financial advisors to continuously study the market and advice on the appropriateness of the proportions of the various sources of finance based on market circumstances at any given time.

scholarly journals Company Internal Factors and Their Influences on Financial Performance

2021 ◽  
Vol 3 (2) ◽  
pp. 177
Author(s):  
Lilis Renfiana ◽  
Yudhisthira Ardana
Keyword(s):  
Financial Performance ◽  
Firm Size ◽  
Time Series Data ◽  
Stock Exchange ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Series Data ◽  
Fixed Costs ◽  
Effect Model

This research aims to systematically, actual, and accurately explain the facts and characteristics of the company and their effect on financial performance. Data in the form of time-series data from 2015-2019 and cross-section data collected from the financial statements of automotive companies listed on the Indonesia Stock Exchange then obtained nine companies that meet the criteria. The independent variables are Firm Size, Leverage, Liquidity, and the dependent variable is financial performance as proxied by Return On Equity (ROA). The research used panel data techniques; Common Effect Model, Fixed Effect Model, and Random Effect Model. The results show that Firm Size partially has a negative and significant effect, meaning that the greater the assets owned by the company, the more complex the agency problems faced. The partial leverage variable has a negative and significant effect, means that the use of relatively high debt will cause fixed costs in the form of interest expenses and loan principal installments to be paid, the greater the fixed costs. The liquidity variable partially has a positive and insignificant effect. This means that changes that occur in both the number of current assets or current liabilities affect increasing profits so that the increase in Liquidity (CR) or the level of liquidity affects changes in increasing company performance (ROA).

scholarly journals Recapitalization Effectiveness and Performance of Banks in Malaysia

2016 ◽  
Vol 8 (4) ◽  
pp. 6-12
Author(s):  
Etri Ernovianti ◽  
Nor Hayati Binti Ahmad ◽  
Ahmad Rizal Mazlan
Keyword(s):  
Banking Sector ◽  
Random Effect ◽  
Random Effect Model ◽  
Banking System ◽  
Least Square ◽  
Annual Reports ◽  
Bank Failures ◽  
Term Survival ◽  
Capital Injection ◽  
And Performance

Recapitalization through capital injection is one of the strategies for banks to strengthen their banking system from the possibility of bank failures. Banks cannot deny that capital is one of the most important components to run their business. In spite of that, few studies have been conducted to assess the effectiveness of such strategy on Asian banks. This paper investigates the effectiveness of capital injection in the Malaysian banking sector which was adversely hit by the financial crisis. Panel data from 1997 to 2014 was used. The financial data is obtained from annual reports published in Bank Scope and The World Bank database. The data were processed using Panel Least Square and Random effect model. The empirical analysis reveals that, GDP, CAR, previous year capital injection and loan write-off (LWO) explain 89.6 percent of the variance in capital injection effectiveness. CAR and LWO/TA are significant at 5 percent confidence level. The evidence from the results shows that recapitalization is vital for long term survival of the banking sector. The study recommends that in order to improve the profitability of banking sector, the banks should write off bad loans and ensure they have adequate capital either through capital injection, or growth to withstand financial risks.

scholarly journals EVALUATING BANKS FINANCIAL PERFORMANCE USING FINANCIAL RATIOS: A CASE STUDY OF KUWAIT LOCAL COMMERCIAL BANKS

2019 ◽  
Vol 4 (2) ◽  
pp. 56-68
Author(s):  
Abuzarqa Rawan
Keyword(s):  
Financial Performance ◽  
Commercial Banks ◽  
Random Effect ◽  
Random Effect Model ◽  
Balance Sheet ◽  
Financial Ratios ◽  
Book Value ◽  
The Difference ◽  
And Performance ◽  
Retained Earnings

This study investigates the effect of Leverage, Total deposit to total assets, Total loans to total assets, Retained earnings to total assets, and Tangible book value per share ratios on banks’ financial performance for Return on Assets (ROA) as the dependent variable. The data were obtained from the financial statement (Income statement and Balance sheet) of the selected banks. The results were found by analyzing the financial ratios of five commercial banks in Al-Kuwait throughout five years (2013–2017). We used analytical methods which led us to the presented results. MANOVA and ANOVA analysis were used to show the difference between banks in their financial situation and performance, and then the panel regression model used to study relationships among variables. The Hausman test was applied to compare fixed and random effect models which were shown that the random effect model gives the better result. Our findings show that the independent variables “Total deposit” to “total assets” and “Retained earnings” to “total assets” have a strong significant impact on our dependent variable ROA. “Leverage” and “Total loans” to “total assets” have a less significant effect on the banks’ financial performance (ROA) while Tangible book value per share does not affect the ROA.

scholarly journals Financial Risk and Financial Performance: Evidence and Insights from Commercial and Services Listed Companies in Nairobi Securities Exchange, Kenya

2020 ◽  
Vol 8 (3) ◽  
pp. 51 ◽  
Author(s):  
Susan Kerubo Onsongo ◽  
Stephen M. A. Muathe ◽  
Lucy Wamugo Mwangi
Keyword(s):  
Financial Risk ◽  
Random Effect ◽  
Random Effect Model ◽  
Target Population ◽  
Annual Reports ◽  
Return On Equity ◽  
Service Companies ◽  
Effect Model ◽  
Negative Effect ◽  
Positive Coefficients

In Kenya, the last few years has seen the performance of companies listed under the commercial and services segment on the Nairobi Securities Exchange (NSE), experience mixed fortunes. The study sought to assess the implications of financial risk on the performance of these companies. The study applied explanatory research design. The target population were the 14 companies listed under this segment of NSE. Secondary panel data contained in published annual reports for the period 2013–2017 was collected. Panel regression model was applied with the random effect model being used based on the Hausman specification test. Findings showed that credit risk had an insignificant positive effect on return on equity (ROE) while liquidity risk had a significantly negative effect on ROE and operational risk had a positive insignificant effect on ROE. The positive coefficients from the data analysis indicated that commercial and service companies at NSE were able to take in more credit to boost performance of these companies however the negative coefficients shows that within the period of study these companies experienced high liquidity problems in that the current liabilities exceeded the current assets. Thus, concluding that these companies were unable to pay all their obligation when they were due.

scholarly journals ICT evaluation models and performance of medium and small enterprises

2014 ◽  
Vol 20 (1-2) ◽  
pp. 9-24
Author(s):  
Anass Bayaga ◽  
Emmanuel O. Adu
Keyword(s):  
Risk Management ◽  
Analysis Of Variance ◽  
Repeated Measures ◽  
Operational Risk ◽  
Small Enterprises ◽  
Operational Risk Management ◽  
Evaluation Models ◽  
Ict Adoption ◽  
And Performance ◽  
Medium And Small Enterprises

Abstract Building on prior research related to (1) impact of information communication technology (ICT) and (2) operational risk management (ORM) in the context of medium and small enterprises (MSEs), the focus of this study was to investigate the relationship between (1) ICT operational risk management (ORM) and (2) performances of MSEs. To achieve the focus, the research investigated evaluating models for understanding the value of ICT ORM in MSEs. Multiple regression, Repeated-Measures Analysis of Variance (RM-ANOVA) and Repeated-Measures Multivariate Analysis of Variance (RM-MANOVA) were performed. The findings of the distribution revealed that only one variable made a significant percentage contribution to the level of ICT operation in MSEs, the Payback method (β = 0.410, p < .000). It may thus be inferred that the Payback method is the prominent variable, explaining the variation in level of evaluation models affecting ICT adoption within MSEs. Conclusively, in answering the two questions (1) degree of variability explained and (2) predictors, the results revealed that the variable contributed approximately 88.4% of the variations in evaluation models affecting ICT adoption within MSEs. The analysis of variance also revealed that the regression coefficients were real and did not occur by chance

scholarly journals How Can Enterprise Risk Management Help in Evaluating the Operational Risks for a Telecommunications Company?

2021 ◽  
Vol 14 (3) ◽  
pp. 139
Author(s):  
José Ruiz-Canela López
Keyword(s):  
Risk Management ◽  
Banking Sector ◽  
Operational Risk ◽  
Field Work ◽  
Risk Identification ◽  
Enterprise Risk Management ◽  
Management Tool ◽  
Self Assessment ◽  
Operational Risks ◽  
Enterprise Risk

Operational risk is defined as the potential losses resulting from events caused by inadequate or failed processes, people, equipment, and systems or from external events. One of the most important challenges for the management of the company is to improve its results through its operational risk identification and evaluation. Most of Enterprise Risk Management (ERM) scholarship has roots in the finance/risk management and insurance (RMI) discipline, mainly in the banking sector. This study proposes an innovative operational risk assessment methodology (OpRAM), to evaluate operational risks focused on telecommunications companies (TELCOs), on the basis of an operational risk self-assessment (OpRSA) process and method. The OpRSA process evaluates operational risks through a quantitative analysis of estimates which inputs are the economic impact and the probability of occurrence of events. The OpRSA method is the “engine” for calculating the economic risk impact, applying actuarial techniques, which allow estimation of unexpected losses and expected losses distributions in a TELCO. The results of the analyzed business unit in the field work were compared with standardized ratings (acceptable, manageable, critical, or catastrophic), and contrasted against the company’s managers, proving that the OpRSA framework is a reliable and useful management tool for the business, and leading to more research in other sectors where operational risk management is key for the company success.

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