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Investment Recommendations

How analysts develop an established investment thesis and recommendation. Understand the importance of both quantitative and qualitative factors, including the importance of the analyst's valuation and sensitivities, consensus forecasts, potential catalysts, and thesis risks.

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11 Lessons (34m)

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  • Description & Objectives

  • 1. Stock Recommendations

    03:20
  • 2. Stock Recommendations Workout

    03:00
  • 3. Research Rating Systems

    02:23
  • 4. Research Rating Systems Workout

    05:36
  • 5. Covering Analyst

    01:58
  • 6. Bull and Bear Scenarios

    01:35
  • 7. Consensus Forecasts

    05:03
  • 8. Identifying What is New

    05:02
  • 9. Catalysts for Stock Repricing

    03:19
  • 10. Risks to Your Thesis

    02:40
  • 11. Investment Recommendations Tryout


Prev: Present Value of Future Stock Price Next: Deferred Taxes

Identifying What is New

  • Notes
  • Questions
  • Transcript
  • 05:02

The main sources of 'new information' in an investment recommendation.

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Glossary

Market mispricing New information
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Transcript

Identifying what is new? As we've already seen a recommendation to buy or sell a stock is based on the analyst believing that the shares are mispriced by the market. However, this belief must be based on the analyst having new information, which is not already priced in by the market. It needs to be more than just having a hunch that share prices will rise or fall. Analysts have access only to public information. So what do we mean by new information? Well, this means that the analyst has gained new insights about the company and it's expected future performance. This new information is a result of research that they have conducted. Information can come from a range of sources. Let's have a look at these in more detail firstly industry insights or expertise if an analyst understands the company or industry better than other Market participants, they may be better able to interpret how economic developments Industries developments or even companies developments will affect the future performance of the company. For example, let's say there's a company announces supply chain issues for some of its major components and that it expects this to have a small negative impact on the current years results. However, the analyst has experienced and expertise in this industry and notes that these sorts of issues often take a couple of years to resolve due to the length of the supply chain and the geographic spread of the different suppliers. The analyst then has new or better information that they can then incorporate into their forecasts likely resulting in lower earnings forecasts, but not just for the current year for the next couple of years. The second source of new information is read across from other companies sectors or even other asset classes. The best analysts can quickly identify how information from these other sources might be relevant to the companies that they cover for example, a clothing retail analyst might track cotton prices and note that historically a 2% increase in Cotton prices has historically converted into a 50 basis points increase in the cost of goods sold for a particular retailer. The analyst then here is that a heavy Monsoon has damaged a significant proportion of next year's cotton crop and consequently cotton Futures are starting to increase. However, the clothing retail share price has not yet responded to this. The analyst has new information that they can incorporate into their forecasts likely resulting in lower earnings forecasts for next year. The third source of new information is new analysis from data site visits or surveys analyst a constantly looking for new data sources or new information on the company that they can use for their forecasts. For example many analyst these days are scouring social media using natural language processing to find information on trends that could be relevant for their forecasts. Let's say for example, an analyst has used some social media analysis to identify more positive consumer trends for a product sold by a company this new data allows the analyst to build improved forecasts over the expected growth in this market and they predict growth rates of 10% per annum despite the fact that most industry research anticipates growth rates of just 5% the analyst can then incorporate this new information into their model likely resulting in revenue forecast, which are ahead of consensus for the next few years even once an analyst has identified the new information. It's important that they think carefully about the impact on their forecasts valuation and rating three questions that an analy should ask themselves are firstly how is this new information reflected in my forecast and valuation? Is this new information isolated to one assumption in my model or could it affect multiple line items for example, if a company is often able to pass on cost increases to its customer or maybe an increase in the cost of goods sold won't have such a negative impact on gross profit and therefore earnings secondly is this new information reflected in the Delta between the analyst forecasts and consensus if the new information leads an analyst to increase Revenue growth forecasts, for example, well are these forecasts now ahead of consensus? If not is this because the new information isn't actually new and is already included into other analysts forecasts. Thirdly, is this new information stock specific or relevant to the sector or Market? If the new information affects all stops within a sector or sub sector and the analyst needs to incorporate the new information into the forecast of all companies affected by the information. For sector analysts often the most powerful items of new information are those which discriminate between stocks in their sector as it allows them to update the relative ratings of the stocks which are most and least affected by this new information.

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