While doing time series analysis, you can show buy/sell signal on the ghraph itself.
Following is the script for doing the same.
While working on this code, I wasted quite a lot of time on below error.
Traceback (most recent call last): File "timeseries_simple_with_pointer.py", line 35, in <module> plt.scatter(df.loc[df['SMA20'] >1400.0 , 'Date'],df.loc[df['SMA20'] >1400.0, 'Close Price'], label='skitscat', color='red', s=25, marker="<") File "/usr/local/lib/python3.6/site-packages/matplotlib/pyplot.py", line 3378, in scatter edgecolors=edgecolors, data=data, **kwargs) File "/usr/local/lib/python3.6/site-packages/matplotlib/__init__.py", line 1717, in inner return func(ax, *args, **kwargs) File "/usr/local/lib/python3.6/site-packages/matplotlib/axes/_axes.py", line 4023, in scatter offsets = np.column_stack([x, y]) File "/usr/local/lib/python3.6/site-packages/numpy/lib/shape_base.py", line 369, in column_stack return _nx.concatenate(arrays, 1) TypeError: invalid type promotion
On further research I found that matplotlib scatter plot does not support pandas series and the scatter plot output needs to be converted into list so I had to use .values to make it work.
Output of my strategy using SMA 5 and SMAA12
As you can see, in range bound market it creates a lot of whipsaw, however, it was able to capture a very good bull run.
I tried using larger duration SMA to see another strategy. Second time, I tried with SAM20 and SMA100 and here is the output
As expected, longer duration SMA strategy provides lesser number of signals, lesser whipsaw’s.
This result does not mean you need to use higher duration SMA. I am planning to run this logic for approx 200 securities, will update this post with the feedabck later.