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Financial Analysis with ARIMA and Time Series Forecasting
Financial Analysis with ARIMA and Time Series Forecasting

Financial Analysis with ARIMA and Time Series Forecasting: Master Time Series Forecasting with ARIMA for Financial Analysis

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Profile Icon Lazy Programmer
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$19.99 per month
Video Jul 2024 6hrs 40mins 1st Edition
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$9.99 $109.99
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Profile Icon Lazy Programmer
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$19.99 per month
Video Jul 2024 6hrs 40mins 1st Edition
Video
$9.99 $109.99
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Free Trial
Renews at $19.99p/m
Video
$9.99 $109.99
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Free Trial
Renews at $19.99p/m

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Key benefits

  • Comprehensive introduction to time series analysis and transformations
  • In-depth exploration of financial time series and baseline forecasts
  • Detailed study of ARIMA models with practical coding sessions

Description

Begin with an introduction to time series analysis, providing a solid foundation for understanding the nature and structure of time series data. You'll explore key concepts such as modeling versus predicting, and learn essential data transformation techniques including power, log, and Box-Cox transformations. These fundamentals set the stage for more advanced topics. As you delve deeper, you'll encounter a thorough examination of financial time series. You'll learn about random walks, the random walk hypothesis, and the importance of baseline forecasts. The course then transitions to a comprehensive study of ARIMA models. You'll explore autoregressive models (AR), moving average models (MA), and the combination of these in ARIMA. Practical coding sessions will reinforce your understanding, allowing you to apply stationarity tests, ACF, PACF, and Auto ARIMA techniques to real financial data. The latter part of the course focuses on the application of ARIMA models in forecasting. You'll learn how to implement ARIMA in various scenarios, from stock returns to sales data. The course wraps up with a detailed guide on forecasting out-of-sample data, ensuring you can apply your new skills in real-world situations. Supplementary sections offer guidance on setting up your coding environment and additional help for Python beginners.

Who is this book for?

This course is designed for financial professionals, data analysts, and enthusiasts with a basic understanding of statistics and Python. Prior experience with financial data is beneficial but not required.

What you will learn

  • Understand and analyze time series data
  • Implement data transformations for improved modeling
  • Apply ARIMA models to financial data
  • Perform stationarity tests and utilize ACF/PACF
  • Forecast financial data using ARIMA techniques
  • Develop data-driven decision-making skills

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 31, 2024
Length: 6hrs 40mins
Edition : 1st
Language : English
ISBN-13 : 9781836644231
Category :
Languages :
Concepts :

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Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
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View plans & pricing

Product Details

Publication date : Jul 31, 2024
Length: 6hrs 40mins
Edition : 1st
Language : English
ISBN-13 : 9781836644231
Category :
Languages :
Concepts :

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Frequently bought together


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Total $ 119.97 219.97 100.00 saved
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Financial Analysis with ARIMA and Time Series Forecasting
$9.99 $109.99
Python Data Analysis
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Table of Contents

8 Chapters
Welcome Chevron down icon Chevron up icon
Getting Set Up Chevron down icon Chevron up icon
Time Series Basics Chevron down icon Chevron up icon
Financial Basics Chevron down icon Chevron up icon
ARIMA Chevron down icon Chevron up icon
Setting Up Your Environment (Appendix) Chevron down icon Chevron up icon
Extra Help With Python Coding for Beginners (Appendix) Chevron down icon Chevron up icon
Effective Learning Strategies for Machine Learning (Appendix) Chevron down icon Chevron up icon
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