Benchmarking versus consensus.

An important way of sense checking our models is to compare our forecasts to consensus forecasts. Consensus numbers help us to understand what the market thinks they're often used as a proxy for market expectations.

Benchmarking our forecasts against consensus helps to challenge our own assumptions if we're materially different from consensus is this because we have significant new information or analysis or just because our numbers are wrong consensus forecasts are usually available for revenue ebitda. Net income and EPS and also for capex, and these are the line items that we would usually focus on. So, what do we need to think about when we're comparing our numbers to consensus? Well, if your forecasts are above or below consensus think about whether this is supported by your analysis and your views on the company, for example, if your research and analysis results in you being more bullish in your views and increasing your revenue growth rate, but your revenue forecasts are below consensus. We'll think about what it is that you might be missing in your forecasts. Look also for inconsistencies in how your KPIs compare to consensus. For example, if your revenue forecasts are below consensus, but your ebitda and net income forecasts are above consensus. This implies that you're operating costs forecasts are well below consensus. Do you have quite bullish views about their cost control or do you need to revisit your margin assumptions? If you are a research analyst doing this it's difficult not to get stuck in a mindset of working your numbers back to consensus. It's important that you use this to challenge the robustness of your model rather than trying to produce a model which shows consensus forecasts. If you're a research analyst taking non-consensus views is part of your job, but has to be supported by your research.