Investigation on the Efficiency of Financial Companies in Malaysia with Data Envelopment Analysis Model

Siew, Lam Weng; Fai, Liew Kah; Hoe, Lam Weng

doi:10.1088/1742-6596/995/1/012021

Cited by 13 publications

(6 citation statements)

References 16 publications

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“…It is also seen that APX, JOH, ECML, MAA, BURSA, ACSM and LPI were fully efficient for all the time period. The results were approximately similar for most of the companies since Siew et al (2017) also found similar results during the time period 2010-2015 where LPI, BURSA, ACSM, APX were reported to be fully efficient.…”

Section: Technical Efficiency and Technical Efficiency Changesupporting

confidence: 68%

“…From the dataset of Table 3 it is obvious that the average technical efficiency was 0.935 which means companies were less than 7% inefficient to use their existing resources. On the other hand, Siew et al (2017) found average efficiency score 0.5865 for the financial company of Malaysia. It is also seen that APX, JOH, ECML, MAA, BURSA, ACSM and LPI were fully efficient for all the time period.…”

Section: Technical Efficiency and Technical Efficiency Changementioning

confidence: 98%

“…There are few studies on banking efficiency in Malaysia but they did not discuss productivity change and efficiency together. Siew et al (2017) studied analyses efficiency of the financial sector of Bursa Malaysia using DEA and found the most efficient company in the financial sector of Bursa Malaysia. Some studies have based on DEA in banking sector: Sufian et al (2016) found that banks from Asian countries to be relatively more efficient rather than foreign banks, and Davies (2017) postulated that technical efficiency of Malaysian commercial banks' technical efficiency was 71.33% and also found that domestic banks had been inefficient in controlling their costs due to their size.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Productivity and efficiency analysis using DEA: Evidence from financial companies listed in Bursa Malaysia

Sharif

Hasan²,

Kurniasari

et al. 2019

10.5267/j.msl

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This study evaluates the technical efficiency, productivity change of financial companies listed in the Malaysian stock exchange (Bursa Malaysia) and examines the effects of productivity change on efficiency over the period 2007-2016. Moreover, this study also concentrates on the ranking of financial companies according to their efficiency scores. Data Envelopment Analysis (DEA) is utilized on a Malmquist Productivity Index in order to calculate the financial companies' efficiency scores. The results of this study show that some firms were fully efficient. The results implied that these companies were in optimal control of their inputs or resources to generate the maximum outputs. Also, the results indicate a tremendous productivity gain was mostly because of a positive shift in frontier technology and positive shift in technical efficiency. This study is significant because it helps to identify the efficient companies from the financial sector in Malaysia based on multiple inputs and outputs by using the DEA model. Common misspecification problems observed that instability of efficiency scores over productivity.

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Section: Technical Efficiency and Technical Efficiency Changesupporting

confidence: 68%

Section: Technical Efficiency and Technical Efficiency Changementioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Productivity and efficiency analysis using DEA: Evidence from financial companies listed in Bursa Malaysia

Sharif

Hasan²,

Kurniasari

et al. 2019

10.5267/j.msl

View full text Add to dashboard Cite

show abstract

“…But the portfolio created was not able to generate a return higher than the average industry return. Lim et al (2014), Tehrani et al (2012), Shabbir and Muhammad (2019) and Siew et al (2017) used liquidity, activity, leverage and profitability ratios to find the efficiency of firms under investigation. The most common ratios used in these studies were current ratio, quick ratio, debt to equity ratio, debt to assets, account receivable turnover, inventory turnover, asset turnover, return on asset, return on equity, return on capital employed, net income, operating profit to sales, net profit margin, price to earnings and price to book.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The resulting portfolio yielded higher risk-adjusted returns when compared to other benchmark portfolios (Lim et al, 2014). Tehrani et al (2012) and Siew et al (2017) were able to identify the most efficient companies among a set of companies under investigation. In addition to the above-mentioned ratios Hwang et al (2007) used owners’ equity to fixed assets, times interest earned and achieved a 100% hit rate in classification of stocks for investors used by employing DEA data analysis (DA) approach.…”

Section: Literature Reviewmentioning

confidence: 99%

Selection of Variables in Data Envelopment Analysis for Evaluation of Stock Performance

Arasu

Kannaiah²,

Christina

et al. 2021

Management and Labour Studies

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Data envelopment analysis (DEA) is a relative measurement technique used to evaluate the efficiencies of a homogeneous group of samples with multiple inputs and/or outputs. DEA can be highly effective when right variables are chosen. The objective of this study is to identify the most appropriate variables for DEA to evaluate stock performance and find the efficient ones from a pool of stocks. Evaluation of stocks are carried out either by assessing their financial strength or by assessing their past price behaviour in the secondary market or both. In any case, it is imperative to use suitable variables to evaluate the performance of stocks. For this purpose, three different combinations of variables were tested on 69 non-financial stocks listed in the National Stock Exchange (NSE), which were selected based on their market capitalization. The results obtained suggest that all the three sets of variables taken for the study help in the identification of efficient stocks. The average returns of the stocks selected in all the three cases are higher than the market return. Among the three sets, stocks identified using the past price behaviour give a higher return when compared to the other two sets. The study can help academicians and investors to percolate efficient stocks from a large pool of stocks. The selected stocks can be further analysed to construct an effective portfolio.

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Data Analysis on the Performance of Technology Sector in Malaysia with Entropy-TOPSIS Model

Siew

Hoe

Fai

2018

Communications in Computer and Information Science

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Investigation on the Efficiency of Financial Companies in Malaysia with Data Envelopment Analysis Model

Cited by 13 publications

References 16 publications

Productivity and efficiency analysis using DEA: Evidence from financial companies listed in Bursa Malaysia

Productivity and efficiency analysis using DEA: Evidence from financial companies listed in Bursa Malaysia

Selection of Variables in Data Envelopment Analysis for Evaluation of Stock Performance

Data Analysis on the Performance of Technology Sector in Malaysia with Entropy-TOPSIS Model

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