I am working on a financial data that entails forecasted revenue a company generates over a fiscal quarter and the actual revenue for that quarter.
import pandas as pd
df = pd.DataFrame({'Period': ["Q3'16", "Q1'17", "Q2'17","Q3'17"],'Predicted M1':[1000,1026,1023,1024],'Actual Earnings':[1010,1030,1020,1026]})
Every month throughout the quarter I generate a new forecast for what revenue will be at the end of the quarter.
A little background on the data. These are consensus earnings predictions/estimate for a quarter. If a company beats these predictions they enjoy a positive share price change. This gives an incentive for analyst/manager to under predict those earnings. Hence majority of predictions are underestimated.
My question is this: How can I prove/show presence of such biases in the forecast.
