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"item_title" : "Financial Economtrics with Python",
"item_author" : [" Reactive Publishing", "Alice Schwartz", "Hayden Van Der Post "],
"item_description" : "Reactive PublishingMaster financial econometrics and Python programming to analyze, predict, and strategize in financial markets. This comprehensive guide offers: Core Principles: Understand econometrics and its applications in finance with beginner-friendly Python programming.Advanced Techniques: Implement ARIMA, GARCH, VAR models, time series analysis, volatility modeling, and predictive analytics using Python.Real-World Applications: Solve practical problems with real financial data, including stock markets and cryptocurrencies.Data-Driven Insights: Use Pandas, NumPy, StatsModels, and SciPy for data processing and analysis. Visualize trends with Matplotlib and Seaborn.Practical Implementation: Follow step-by-step tutorials and exercises to develop and backtest trading strategies.Why Choose This Book: High Demand Skills: Equip yourself with sought-after financial and programming skills.Practical Focus: Hands-on examples and real data applications.Expert Author: Insights from a seasoned financial analyst and data scientist.Comprehensive Coverage: Suitable for beginners to advanced practitioners.Engaging Content: Clear explanations and practical exercises for easy learning.Ideal For: Financial analysts, economists, and data scientists.Students and academics in finance and data science.Finance professionals looking for data-driven insights.Unlock financial econometrics with Python to make informed investment decisions and develop effective trading strategies.",
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Financial Economtrics with Python : A Pythonic Guide for 2024
Overview
Reactive Publishing
Master financial econometrics and Python programming to analyze, predict, and strategize in financial markets. This comprehensive guide offers:
- Core Principles: Understand econometrics and its applications in finance with beginner-friendly Python programming.
- Advanced Techniques: Implement ARIMA, GARCH, VAR models, time series analysis, volatility modeling, and predictive analytics using Python.
- Real-World Applications: Solve practical problems with real financial data, including stock markets and cryptocurrencies.
- Data-Driven Insights: Use Pandas, NumPy, StatsModels, and SciPy for data processing and analysis. Visualize trends with Matplotlib and Seaborn.
- Practical Implementation: Follow step-by-step tutorials and exercises to develop and backtest trading strategies.
Why Choose This Book:
- High Demand Skills: Equip yourself with sought-after financial and programming skills.
- Practical Focus: Hands-on examples and real data applications.
- Expert Author: Insights from a seasoned financial analyst and data scientist.
- Comprehensive Coverage: Suitable for beginners to advanced practitioners.
- Engaging Content: Clear explanations and practical exercises for easy learning.
Ideal For:
- Financial analysts, economists, and data scientists.
- Students and academics in finance and data science.
- Finance professionals looking for data-driven insights.
Unlock financial econometrics with Python to make informed investment decisions and develop effective trading strategies.
This item is Non-Returnable
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Details
- ISBN-13: 9798329104905
- ISBN-10: 9798329104905
- Publisher: Independently Published
- Publish Date: June 2024
- Dimensions: 9 x 6 x 0.93 inches
- Shipping Weight: 0.99 pounds
- Page Count: 374
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