More can be better

When it comes to forecasting stocks and other assets, I have long been a sceptic that more detailed information will improve forecasts. To me, the results of the seminal study by Stuart Oskamp in 1965 still hold. People who get more detailed information about a person or an asset tend to think their assessments are more accurate, but in reality, their accuracy does not change. But it seems in one respect, I have to revise my opinion.

True accuracy vs. expected accuracy of psychological assessment as information grows

Source: Oskamp (1965)

Peter Pope and Tony Wang thought about the forecasts made by sell-side analysts and wondered why some analysts provide forecasts that simply encompass the most common data like next year’s earnings per share and little else. Other analysts provide a battery of detailed forecasts ranging from earnings in all its varieties (EBITDA, EBIT, EPS, etc.) and for many years into the future plus additional forecasts for items like cash flows, net debt, and other balance sheet items, etc.

Obviously, the reason why some analysts provide such a battery of detailed forecasts is to demonstrate their competence and the detail of the work they have done on a stock. But Pope and Wang wondered if with this additional work comes an improvement in forecasts. These sell-side analysts had the same plethora of data available to them as all other analysts, but the ones that make more detailed forecasts for variables outside of earnings may have more accurate forecasts simply because they did the work and didn’t use any shortcuts.

It turns out that analysts who actually do the nitty gritty work do have better forecasts. The study found that analysts who publish a larger number of forecasts for variables other than earnings in the coming few years tend to have more accurate forecasts for earnings as well. And the resulting recommendations tend to be more accurate as well. For example, the chart below shows the performance of a long-short strategy for analysts with a high number of forecasts vs. a long-short strategy for analysts with a low number of forecasts. In both long-short strategies, the portfolio went long these stocks with a buy rating for 30 days (or until the rating changed if that happened within 30 days) and short the stocks with a sell rating.

Clearly, the analysts who provide a larger number of detailed forecasts are better able to differentiate between stocks to buy and stocks to avoid.

Long-short strategy based on the number of detailed forecasts given by analysts

Source: Pope and Wang (2023)

Note, however, that the results shown in the chart above are before transaction costs and assume that an investor can buy or sell stocks at the end of the trading day the analyst recommendations are published. The authors note that if the implementation lag is just one day, the performance drops a lot, and I would assume if transaction costs are taken into account it drops even more.

So, this strategy is not directly investable, but it provides a shortcut for investors to assess whether it is worthwhile reading an analyst note. If the analyst doesn’t provide long-term forecasts (for example only forecasts for the next two years and nothing for year three and beyond) or forecasts for major balance sheet items or cash flows, the likelihood is that the recommendation is less reliable and it doesn’t pay to read the analysis let alone meet the analyst for an hour to talk through the analysis. You are probably better off going elsewhere for some proper analysis.