Time for action – plotting price and volume returns with a scatter plot
We can easily make a scatter plot of the stock price and volume returns. Again, let's download the necessary data from Yahoo Finance.
The quotes data in the previous step is stored in a Python list. Convert this to a NumPy array and extract the close and volume values:
dates = quotes.T[4] volume = quotes.T[5]
Calculate the close price and volume returns:
ret = np.diff(close)/close[:-1] volchange = np.diff(volume)/volume[:-1]
Create a matplotlib figure object:
fig = plt.figure()
Add a subplot to the figure:
ax = fig.add_subplot(111)
Create the scatter plot with the color of the data points linked to the close return, and the size linked to the volume change:
ax.scatter(ret, volchange, c=ret * 100, s=volchange * 100, alpha=0.5)
Set the title of the plot and put a grid on it:
ax.set_title('Close and volume returns') ax.grid(True) plt.show()
The scatter plot for DISH appears as follows:
What just happened?
We made a scatter plot of...