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Numpy for Quantitative Finance: Harness the Python Power of NumPy for Advanced Quantitative Finance Solutions

by Reactive Publishing
Save 11% Save 11%
Current price ₹2,699.00
Original price ₹3,044.00
Original price ₹3,044.00
Original price ₹3,044.00
(-11%)
₹2,699.00
Current price ₹2,699.00

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Book cover type: Paperback
  • ISBN13: 9798327530287
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 546
  • Original Price: GBP 23.41
  • Language: English
  • Edition: N/A
  • Item Weight: 722 grams
  • BISAC Subject(s): Economics / Theory

Reactive Publishing

Unlock the potential of NumPy in the realm of quantitative finance with "NumPy with Quantitative Finance," an essential guide for financial analysts, data scientists, and quantitative researchers. This expert-level book bridges the gap between Python programming and financial theory, providing a comprehensive resource for applying NumPy to solve complex financial problems.

Dive into financial data manipulation, statistical analysis, and mathematical modeling using NumPy's robust array processing capabilities. This book offers practical, hands-on examples and detailed explanations to help you master key concepts such as portfolio optimization, risk management, derivatives pricing, and algorithmic trading.

Written by industry experts, "NumPy with Quantitative Finance" covers:

  • Efficient data handling and preprocessing for financial datasets
  • Advanced statistical methods and time series analysis
  • Implementation of Monte Carlo simulations for risk assessment
  • Optimization techniques for portfolio management
  • Pricing of complex derivatives using numerical methods
  • Development of quantitative trading strategies

With this book, you'll gain the knowledge and skills to leverage NumPy for powerful quantitative finance applications, enhancing your analytical capabilities and driving more informed financial decisions. Elevate your expertise and stay ahead in the competitive financial landscape.

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