This study deploys data envelopment analysis (DEA) to identify the appropriate variables for the performance valuation of stocks. For this purpose, sixty-nine non-financial stocks of the Nifty 100 index of The National Stock Exchange of India Ltd (NSE) were selected as a sample for this study. We segregated the selected stocks into three groups of inputs and outputs for DEA based on fundamental indicators (financial ratios); technical indicators (momentum indicators); and both, fundamental and technical indicators. The stock performance indicators are sourced from the ACE database from financial year 2014 to 2019. The results of the study suggest that all three sets of stock performance indicators help in the identification of efficient stocks. However, stocks identified under momentum indicators are seen to have been better performing in stock return compared to the other two groups. The outcome of this study may help academicians and investors construct an effective portfolio and analyse/study its performance evaluation
AbadC., ThoreS. A., & LaffargaJ. (2004). Fundamental analysis of stocks by two-stage DEA.Managerial and Decision Economics, 25(5), 231–241.
2.
AhmadzadeM., FazliS., KhosroanjomD., & MaviR. K. (2011). Utilising data envelopment analysis for selecting stock and benchmark firms in Tehran stock exchange.International Journal of Operational Research, 12(4), 446–463.
3.
ArifA., SadiqM., ShabbirM. S., YahyaG., ZamirA., & BaresLopez, L. (2020). The role of globalization in financial development, trade openness and sustainable environmental-economic growth: Evidence from selected South Asian economies.Journal of Sustainable Finance & Investment, 1–18. https://doi.org/10.1080/20430795.2020.1861865
4.
ArshinovaT. (2011). Construction of equity portfolio on the basis of data envelopment analysis approach.Scientific Journal of Riga Technical University. Computer Sciences, 45(1), 104–108.
5.
BahraniR., & KhedriN. (2013). Evaluation of relative efficiency and performance of companies using data envelopment analysis (DEA) approach.Elixir Finance Management, 56, 13299–13304.
6.
BeaverW. H. (1966). Financial ratios as predictors of failure.Journal of Accounting Research, 4, 71–111.
7.
BernardV. L. (1994). Accounting-based valuation methods, determinants of market-to-book ratios, and implications for financial statement analysis (Working Paper No. 9401). University of Michigan.
8.
BettmanJ. L., SaultS. J., & SchultzE. L. (2009). Fundamental and technical analysis: Substitutes or complements?Accounting & Finance, 49(1), 21–36.
9.
BlessingA., & OnojaE. E. (2015). The role of financial statements on investment decision making: A case of united bank for Africa PLC (2004–2013).European Journal of Business, Economics and Accountancy, 3(2), 12–37.
10.
BlumeL., EasleyD., & O’haraM. (1994). Market statistics and technical analysis: The role of volume.The Journal of Finance, 49(1), 153–181.
11.
ChenH. H. (2008). Stock selection using data envelopment analysis.Industrial Management & Data Systems, 108(9), 1255–1268.
12.
ChenK. H., & ShimerdaT. A. (1981). An empirical analysis of useful financial ratios.Financial Management, 10, 51–60.
13.
ChenH. Y., LeeC. F., & ShihW. K. (2016). Technical, fundamental, and combined information for separating winners from losers.Pacific-Basin Finance Journal, 39, 224–242.
14.
DiaM. (2009). A portfolio selection methodology based on data envelopment analysis.INFOR: Information Systems and Operational Research, 47(1), 71–79.
15.
DjemaH., & DjerdjouriM. (2012). A two-stage DEA with partial least squares regression model for performance analysis in healthcare in Algeria.International Journal of Applied Decision Sciences, 5(2), 118–141.
16.
D’InvernoG., CarosiL., & RavagliL. (2018). Global public spending efficiency in Tuscan municipalities.Socio-Economic Planning Sciences, 61, 102–113
17.
EjazS., AmirH., & ShabbirM. S. (2017). Public expenditure and its impact on economic growth: A case of Pakistan.Kashmir Economic Review, 26(1), 13–21.
18.
ElingM. (2006). Performance measurement of hedge funds using data envelopment analysis.Financial Markets and Portfolio Management, 20(4), 442.
19.
GardijanM., & KojićV. (2012). DEA-based investment strategy and its application in the Croatian stock market.Croatian Operational Research Review, 3(1), 203–212.
20.
GarkazM., & PesaraklooF. (2011). Determination of portfolio through fuzzy data envelopment analysis in companies accepted in Tehran securities exchange.Middle East Journal of Scientific Research, 8(5), 942–946.
21.
HwangS. N., LinC. T., & ChuangW. C. (2007). Stock selection using data envelopment analysis-discriminant analysis.Journal of Information and Optimization Sciences, 28(1), 33–50.
22.
LimS., OhK. W., & ZhuJ. (2014). Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market.European Journal of Operational Research, 236(1), 361–368.
23.
LingO. P., & KamilA. A. (2010). Data envelopment analysis for stocks selection on Bursa Malaysia.Archives of Applied Science Research, 2(5), 11–35.
24.
LiuY., SaleemS., ShabbirR., ShabbirM. S., IrshadA., & KhanS. (2020). The relationship between corporate social responsibility and financial performance: A moderate role of fintech technology.Environmental Science and Pollution Research.https://doi.org/10.1007/s11356-020-11822-9
25.
LopesA., LanzerE., LimaM., & daCosta, N.Jr. (2008). DEA investment strategy in the Brazilian stock market.Economics Bulletin, 13(2), 1–10.
26.
MinH., MinH., JooS. J., & KimJ. (2008). Data envelopment analysis for establishing the financial benchmark of Korean hotels.International Journal of Services and Operations Management, 4(2), 201.
27.
MuhammadI., ShabbirM. S., SaleemS., BilalK., & UlucakR. (2020). Nexus between willingness to pay for renewable energy sources: Evidence from Turkey.Environmental Science and Pollution Research, 28, 2972–2986.
28.
MurphyJ. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. Penguin.
29.
NguyenV. K., ShabbirM. S., SailM. S., & ThuyT. H. (2020). Does informal economy impede economic growth? Evidence from an emerging economy.Journal of Sustainable Finance & Investment. http://doi.org/10.1080/20430795.2020.1711501
30.
OuJ. A., & PenmanS. H. (1989). Financial statement analysis and the prediction of stock returns.Journal of Accounting and Economics, 11(4), 295–329.
31.
PowersJ., & McMullenP. (2000). Using data envelopment analysis to select efficient large market cap securities.Journal of Business and Management, 7(2), 31–42.
32.
SaleemH., ShabbirM. S., KhanB., AzizS., HusinM. M., & AbbasiB. A. (2020). Estimating the key determinants of foreign direct investment flows in Pakistan: New insights into the co-integration relationship.South Asian Journal of Business Studies. https://doi.org/10.1108/SAJBS-07-2019-0123
33.
ShabbirM. S. (2016). Contributing factors of inland investment.Global Journal of Management and Business Research. https://journalofbusiness.org/index.php/GJMBR/article/view/2031
34.
ShabbirM. S., & MuhammadI. (2019). The dynamic impact of foreign portfolio investment on stock prices in Pakistan.Transnational Corporations Review, 11(2), 166–178.
35.
ShabbirM. S., & KeifeW. (2020). The relationship between corporate social responsibility, environmental investments and financial performance: Evidence from manufacturing companies.Environmental Science and Pollution Research.https://doi.org/10.1007/s11356-020-10217-0
36.
ShabbirM. S., BashirM., AbbasiH. M., YahyaG., & AbbasiB. A. (2020). Effect of domestic and foreign private investment on economic growth of Pakistan.Transnational Corporations Review, 1–13. https://doi.org/10.1080/19186444.2020.1858676
37.
SiewL. W., FaiL. K., & HoeL. W. (2017). An empirical investigation on the efficiency of the financial companies in Malaysia with DEA model.American Journal of Information Science and Computer Engineering, 3(3), 32–38.
38.
SohailM. K., and AnjumM. S. (2016). Efficiency dynamics of initial public offerings using data envelopment analysis and Malmquist Productivity Index approach.Engineering Economics, 27(2), 175–184.
39.
TehraniR., MehraganM. R., & GolkaniM. R. (2012). A model for evaluating financial performance of companies by data envelopment analysis: A case study of 36 corporations affiliated with a private organization.International Business Research, 5(8), 8.
40.
TreynorJ. L., & FergusonR. (1985). In defense of technical analysis.The Journal of Finance, 40(3), 757–773.
41.
YuS., SialM. S., ShabbirM. S., MoizM., WanP., & CherianJ. (2020). Does higher population matter for labour market? Evidence from rapid migration in Canada.Ekonomska Istraživanja [Economic Research], 1–18.
