A key problem in financial analysis is forecasting corporate revenue. Get this right and much of the problem of earnings forecasting (and valuation for that matter) becomes a lot simpler. The question inevitably arises as to how much weight to put on the exogenous drivers of revenue and how much to put upon those that originate within the firm.
The approach I take is to work the forecast through three stages: a 'course filter' where we use the historical revenues and use a statistical forecasting technique. A 'medium filter' which conditions the trend for expectations of GDP growth, inflation and other relevant market based data and finally a 'fine filter'. The fine filter is where the impact of the given company's plans upon the future path of revenue are evaluated and incorporated into the forecast.
The question then comes as to how much weight to put on the medium and the fine filter in conditioning the trend. One statistic can be very useful and that is the R2 value from the company's beta estimation. R2 tells us the degree of variablity in the company's returns that can be explained by the market. Put another way an R2 of 20% suggests that 20% of the volatility of returns is market driven and 80% is firm specific. That is the clue as to how much attention to pay to each dimension of the forecast - simple really.