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Stock analyst common mistakes

Common sense
Stock analyst common mistakes

I want to begin by stating the obvious:

  • A stock analyst is not a trader.
  • Do not take trading advice from a stock analyst.
  • Data crunching is not sufficient and does not equal future performance.

Fooled by metrics

At the fundamental level, most stock analysts are fooled by metrics.

They try to find correlations between some metrics and the stock price where is none.

They think that if they just came up with just another financial metric then will figure it all out.

My point is not to say that financial metrics do not matter, they matter, but if you need to crunch financial numbers all day for a company to come out with a trading thesis, in most cases it’s not a good trading idea.

This kind of data crunching is most common for most follows companies (AAPL, FB, AMZN, TSLA, etc.). Most analysts do this kind of stuff to make a name for themselves, to appear more intelligent.

They do not have skin in the game, their thesis does not need to be a good, actionable, profitable trade idea.

I would like to make the point that even from a time management perspective it’s a bad idea to crunch numbers all day. Why will you spend so much time to find the needle in a haystack, when you can find companies that are industry leaders with a clear vision, and good management?


They have only one perspective for looking at a stock

Their perspective is always looking at past data and past performance and then extrapolating that into the future.

This is like driving a car looking at the rear mirror.

This kind of perspective is not flexible, it’s lazy work and unsophisticated.


Why the stock goes down if it beats EPS expectation?

All beginner traders are asking this question.

Traders and investors are looking for clear guidance for the next quarters/year.

Stocks move based on future performance expectations, not based on a current snapshot of financial metrics.

This is why a company can beat its EPS numbers substantially and still go down.

Conclusion

  • Data crunching is needed but not sufficient.
  • Do not be fooled by metrics
  • Do not argue with the market.

Stay well