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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.

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