Application of Neural Network and Simulation Modeling to Evaluate Russian Banks’ Performance

Sharma, Satish and Shebalkov, Mikhail (2013) Application of Neural Network and Simulation Modeling to Evaluate Russian Banks’ Performance. Journal of Applied Finance and Banking, 3 (5). pp. 19-37. ISSN 1792-6599

Preview

Text (Full text) Application of Neural Network and Simulation Modeling.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (205kB) | Preview

Abstract

This paper presents an application of neural network and simulation modeling to analyze and predict the performance of 883 Russian Banks over the period 2000-2010. Correlation analysis was performed to obtain key financial indicators which reflect the leverage, liquidity, profitability and size of Banks. Neural network was trained over the entire dataset, and then simulation modeling was performed generating values which are distributed with Largest Extreme Value and Loglogistic distributions with estimated parameters providing robust results. Next, a combination of neural network and simulation modeling techniques was validated with the help of back-testing. Finally, we received nine bank clusters that describe the structural performance within the Russian Banking sector.

Actions (login required)

View Item

Downloads