Skip to content

Booksellers & Trade Customers: Sign up for online bulk buying at trade.atlanticbooks.com for wholesale discounts

Booksellers: Create Account on our B2B Portal for wholesale discounts

Recent Advances in Stock Market Prediction: Applications of Machine Learning and Deep Learning

by Tianrong Zhuang
Save 8% Save 8%
Current price ₹4,469.00
Original price ₹4,851.00
Original price ₹4,851.00
Original price ₹4,851.00
(-8%)
₹4,469.00
Current price ₹4,469.00

Imported Edition - Ships in 18-21 Days

Free Shipping in India on orders above Rs. 500

Request Bulk Quantity Quote
+91
Book cover type: Paperback
  • ISBN13: 9789999332958
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Eliva Press
  • Publisher Imprint: Eliva Press
  • Publication Date:
  • Pages: 112
  • Original Price: USD 49.5
  • Language: English
  • Edition: N/A
  • Item Weight: 159 grams
  • BISAC Subject(s): Finance / General

This book provides a comprehensive assessment of forecasting models used in the stock market across both developed and emerging markets, utilising data from the UK, US, China, and India. The first section compares Particle Swarm Optimised Radial Basis Function Neural Networks (PSO-RBFNN) with standard RBFNN and two benchmark econometric models, ARIMA and Holt-Winters. The findings indicate that econometric models tend to perform better in developed markets, whereas neural networks show more evident advantages in emerging markets. PSO-RBFNN outperforms traditional RBFNN due to its improved parameter optimisation. The second section expands the analysis by examining Random Forest (RF), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM) models, along with their ensemble models. SVR performs well across most datasets, while some ensemble models show mixed but notable improvements depending on market conditions. Stacking LASSO reduces extreme prediction deviations in the UK and US, whereas in China and India, it also demonstrates solid performance. Other ensemble models, such as simple average, weighted average, and short moving averages, sometimes perform better on certain error metrics. Overall, the findings highlight how market structure influences the strengths of machine learning and econometric forecasting techniques, offering valuable insights for researchers, practitioners, and policymakers interested in financial prediction.

Trusted for over 49 years

Family Owned Company

Secure Payment

All Major Credit Cards/Debit Cards/UPI & More Accepted

New & Authentic Products

India's Largest Distributor

Need Support?

Whatsapp Us