Aasheesh Dixit
Papers
1
Total Citations
2
H-Index
1
About
Aasheesh Dixit’s research centers on the application of artificial neural networks to financial forecasting, with a particular focus on stock market prediction. His most cited work, “Prediction of 2 Scrip Listed in NSE using Artificial Neural Network” (2016), explores how machine learning models can analyze trading patterns and market dynamics to forecast the performance of individual stocks on India’s National Stock Exchange. By demonstrating that neural networks can capture complex, non-linear relationships in financial data, Dixit contributes to the growing field of computational finance, offering tools that may help traders and analysts make more informed decisions. Though his citation count remains modest, his work addresses a topic of enduring interest—the intersection of AI and market behavior—and reflects the broader push toward data-driven investment strategies. For students and researchers exploring neural network applications in finance, Dixit’s research provides a practical entry point into modeling volatile, real-world systems.
Research Focus
Key Achievements
Top Papers
- 1Prediction of 2 Scrip Listed in NSE using Artificial Neural Network2 citations · 2016