TY - JOUR
T1 - Neural network DEA for measuring the efficiency of mutual funds
AU - Hanafizadeh, Payam
AU - Reza Khedmatgozar, Hamid
AU - Emrouznejad, Ali
AU - Derakhshan, Mojtaba
PY - 2014/7/7
Y1 - 2014/7/7
N2 - Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs.
AB - Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs.
KW - back-ropagation DEA
KW - data envelopment analysis
KW - DEA
KW - large dataset
KW - mutual fund
KW - neural network
UR - http://www.scopus.com/inward/record.url?scp=84904011725&partnerID=8YFLogxK
UR - http://www.inderscience.com/offer.php?id=63229
U2 - 10.1504/IJADS.2014.063229
DO - 10.1504/IJADS.2014.063229
M3 - Article
AN - SCOPUS:84904011725
SN - 1755-8077
VL - 7
SP - 255
EP - 269
JO - International Journal of Applied Decision Sciences
JF - International Journal of Applied Decision Sciences
IS - 3
ER -