Time Series Analysis - The Power of Exponentially Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a statistical tool for modeling or describing a time series. It is commonly used in the financial industry to evaluate the risk of securities or portfolios.
In this article, we will introduce you to the mathematical basics of the EWMA. We will also show you how to use EWMA models in Python using practical examples.
Understanding how EWMA works is essential for a data scientist or quantitative analyst, as it is widely used in the financial industry. You can immediately apply the knowledge from this article in your daily work.
Here’s an overview of the topics:
- What is the Exponentially Weighted Moving Average (EWMA)?
- Applications of the EWMA
- Technical Analysis
- Risk Management
- Practical examples with Python
- Technical requirements
- Use Case and Dataset
- Weaknesses of the Simple Moving Average (SMA)
- Exponentially Weighted Moving Average
- Conclusion
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