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Python for Finance Cookbook – Second Edition

You're reading from   Python for Finance Cookbook – Second Edition Over 80 powerful recipes for effective financial data analysis

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781803243191
Length 740 pages
Edition 2nd Edition
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Author (1):
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Eryk Lewinson Eryk Lewinson
Author Profile Icon Eryk Lewinson
Eryk Lewinson
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Table of Contents (18) Chapters Close

Preface 1. Acquiring Financial Data FREE CHAPTER 2. Data Preprocessing 3. Visualizing Financial Time Series 4. Exploring Financial Time Series Data 5. Technical Analysis and Building Interactive Dashboards 6. Time Series Analysis and Forecasting 7. Machine Learning-Based Approaches to Time Series Forecasting 8. Multi-Factor Models 9. Modeling Volatility with GARCH Class Models 10. Monte Carlo Simulations in Finance 11. Asset Allocation 12. Backtesting Trading Strategies 13. Applied Machine Learning: Identifying Credit Default 14. Advanced Concepts for Machine Learning Projects 15. Deep Learning in Finance 16. Other Books You May Enjoy
17. Index

Building an interactive web app for technical analysis using Streamlit

In this chapter, we have already covered the basics of technical analysis, which can help traders make their decision. However, until now everything was quite static - we downloaded the data, calculated an indicator, plotted it, and in case we wanted to change the asset or the range of dates, we had to repeat all the steps. What if there was a better and more interactive way to approach this challenge?

This is exactly where Streamlit comes into play. Streamlit is an open-source framework (and a company under the same name, similarly to Plotly) that allows us to build interactive web apps using only Python, all within minutes. Below you can find the highlights of Streamlit:

  • It is easy to learn and can generate results very quickly
  • It is Python only; no front-end experience required
  • It allows us to focus purely on the data/ML sides of the app
  • We can use Streamlit’s hosting services for our apps

In this recipe...

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