Measuring Dhaka stock exchange market efficiency: A stochastic frontier analysis

PurposeIntellectual capital (IC) has been recognized in improving the efficiency of businesses and gaining competitive edge in the developed world. The present study offers perspectives into the effect of IC on the efficiency of the Indian financial sector companies.Design/methodology/approachFor the purpose of evaluating efficiency, the research has used stochastic frontier analysis (SFA). All Indian financial sector companies listed in National Stock Exchange (NSE-500) for the timeframe of ten years (2008–2018) have been considered. The paper has employed modified Pulic's Value Added Intellectual Coefficient (VAICTM) as a proxy to measure IC. Correlation and panel data regression have been used in order to examine the relationship.FindingsThe results of the study indicate positive and significant relationship between IC and efficiency of the firm. The results also show that all the components of IC, that is, human capital, relational capital, process capital and capital employed have a significant impact on firms' efficiency. Additionally, it has been seen that sample companies do not invest in research and development leading to no innovation capital.Practical implicationsThe research will assist managers in managing and controlling the IC, investors in matters related to investment and financial experts in improving the company's IC and value creation.Originality/valueThe current research is one of the pioneering studies in the context of Indian financial sector that examines the impact of modified VAIC on operational efficiency calculated using SFA.

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Contribution of Co-Skewness and Co-Kurtosis of the Higher Moment CAPM for Finding the Technical Efficiency

Economics Research International ◽

10.1155/2014/253527 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Md. Zobaer Hasan ◽

Anton Abdulbasah Kamil

Keyword(s):

Risk Factors ◽

Stock Market ◽

Technical Efficiency ◽

Stochastic Frontier Analysis ◽

Stock Exchange ◽

Stochastic Frontier ◽

Frontier Analysis ◽

Two Factors ◽

Input Variables ◽

The Individual

The objective of this paper is to present the technical efficiency of individual companies and their respective groups of Bangladesh stock market (i.e., Dhaka Stock Exchange, DSE) by using two risk factors (co-skewness and co-kurtosis) as the additional input variables in the Stochastic Frontier Analysis (SFA). The co-skewness and co-kurtosis are derived from the Higher Moment Capital Asset Pricing Model (H-CAPM). To investigate the contribution of these two factors, two types of technical efficiency are derived: (1) technical efficiency with considering co-skewness and co-kurtosis (WSK) and (2) technical efficiency without considering co-skewness and co-kurtosis (WOSK). By comparing these two types of technical efficiency, it is noticed that the technical efficiency of WSK is higher than the technical efficiency of WOSK for the individual companies and their respective groups. As per available literature in the context Bangladesh stock market, no study has been conducted thus far to measure technical efficiency of companies and their respective groups by using the risk factors which are derived from the H-CAPM. In this research, the link between H-CAPM and SFA is established for measuring technical efficiency and it is believed that the findings of this study may be applied to other emerging stock markets.

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The effects of efficiency on banks’ market risk: Empirical evidence from China

Asian Academy of Management Journal of Accounting and Finance ◽

10.21315/aamjaf2021.17.2.4 ◽

2021 ◽

Vol 17 (2) ◽

pp. 81-106

Author(s):

Mohd Fahmee Ab-Hamid ◽

Hawati Janor ◽

Aisyah Abdul-Rahman ◽

Mariani Abdul-Majid

Keyword(s):

Value At Risk ◽

Stochastic Frontier Analysis ◽

Stock Exchange ◽

Risk Measures ◽

Panel Data Analysis ◽

Stochastic Frontier ◽

Market Risk ◽

Frontier Analysis ◽

Risk Increase ◽

The Cost

This article investigates the effect of efficiencies on market risk using a sample of Chinese commercial banks from 2000 to 2015 using different measures of market risk; the Value at Risk (VaR) and Expected Shortfall (ES). The cost and profit efficiencies are estimated by the Stochastic Frontier Analysis (SFA) on the 12 biggest banks listed on the Shanghai Stock Exchange. In testing the effect between efficiency and market risk, this study applied four different models to uncover the relationship between VaR and ES as measures of market risk on cost and profit efficiencies. Utilising a panel data analysis, the results show that different banks efficiencies affect market risk measures differently. While bank cost efficiency reduces market risk, increase in profit efficiency increase market risk. The analysis in this study helps explain the unconvincing evidence of an inefficiencies-risk connection in the bank sector. Bank regulators and managers may need to focus on the cost and profit efficiencies-related initiatives to better manage the market risk. These findings provide bank managers with more understanding of bank risk and serve as an underpinning for bank supervision efforts aimed at strengthening the joint risk management of efficiency market risks.

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Analysis of Banking Industry Performance Efficiency in Indonesia Using Parametric and Nonparametric Methods

The Winners ◽

10.21512/tw.v19i1.4760 ◽

2018 ◽

Vol 19 (1) ◽

pp. 53

Author(s):

Banon Amelda ◽

Erna Bernadetta Sitanggang

Keyword(s):

Cross Section ◽

Stochastic Frontier Analysis ◽

Banking Industry ◽

Stock Exchange ◽

Parametric Method ◽

Stochastic Frontier ◽

Nonparametric Methods ◽

Frontier Analysis ◽

Efficient Performance ◽

High Efficient

This research aimed to measure the efficiency performance of the banking industry in Indonesia by using parametric and nonparametric methods, as measured by the stabilization of bank performance efficiency based on the time series from year to year and to identify which variables to the value of efficiency. The analytical method applied the parametric method with cross section approach of Stochastic Frontier Analysis (SFA) while for nonparametric method used intermediation approach from Data Development Analysis (DEA) CRS and VRS model. The data of this research was the financial statements of banks listed on the stock exchange for the period 2012-2016 with 29 databanks processed with the help of Stata 12. From the results of the analysis using the three measures of efficiency, it is known that the efficiency value with Cross Section Stochastic Frontier Analysis shows a stable and high efficient conditions for all banks. While nonparametric methods show different efficiency levels for each bank, which with DEA CRS model not all banks show an efficient performance, only 26,90% on average each year banks have efficient performance, and 99,31% of banks perform efficiently according to VRS model.

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Stochastic Frontier Analysis of Indonesian Firm Efficiency: A Note

International Journal of Banking and Finance - Vol. 15, Number 2, 2020 ◽

10.32890/ijbf2011.8.2.8426 ◽

2011 ◽

Author(s):

T. Handono E. Prabowo ◽

Emilyn Cabanda

Keyword(s):

Performance Measurement ◽

Stochastic Frontier Analysis ◽

Stock Exchange ◽

Manufacturing Sector ◽

Stochastic Frontier ◽

Model Performance ◽

Managerial Decision ◽

Frontier Analysis ◽

Listed Firms ◽

Time Period

This research attempts to model performance measurement for the firms listed on Indonesia Stock Exchange (IDX) using the stochastic frontier approach. There are 121 firms analyzed over the period of 2000-05 with 726 pooled observations. We also test whether firm’s age, size, market share, manufacturing classifications and time period have effects on the technical inefficiency of the manufacturing sector. Our findings reveal that the average technical efficiency of the tested firms is 0.7149, which is below the efficiency frontier: factors that affect inefficiency are found and explained. Our research has offered notable original contributions to performance measurement and provides insights or managerial decision making on operational performance of listed firms in an increasingly competitive Indonesian economy.

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