When using the Exponential Moving Average (EMA) indicator on a graph with specific settings (Length = 50, Source = Close, Offset = 0, Smoothing Line = SMA, Smoothing Length = 1), careful attention was given to note the EMA value (EMA_From_Graph) of the close prices from the “values in status line.” Subsequently, to replicate the same EMA value in Python, the following condition was employed:
EMA_From_Python = df[‘close_ema_50’] = df[‘close’].ewm(span=50, min_periods=1, adjust=False).mean()
However, upon comparing both values, a slight deviation in price was observed. For instance, for the BANKNIFTY INDEX at Date & Time: 12-07-2024 10:40:00, EMA_From_Python was calculated as 52308.777848, whereas EMA_From_Graph was reported as 52306.28. My objective is to ensure Python generates an EMA value that exactly matches EMA_From_Graph.