I’m working on a real-time stock analysis tool and I need to implement an Exponential Moving Average (EMA) calculation in C#. I’m familiar with the concept of EMA, which places a greater weight and significance on the most recent data points, but I’m unsure about the best way to implement this efficiently in C# for real-time data updates.

Could someone provide a sample implementation or guide me on how to set up an EMA calculation that can efficiently update as new data comes in without recalculating the entire average each time?

Here’s what I understand about the formula:

EMA_today = (Value_today × (Smoothing / (1 + Days))) + EMA_yesterday × (1 - (Smoothing / (1 + Days)))

Where Smoothing is typically set to 2 for a default EMA calculation.

Any advice on how to translate this into an efficient C# code that works well with real-time streaming data would be greatly appreciated!

Thank you!