I got plenty of different comments for this post. I'd like to note that some users are very trustful and decided not to dig into the text itself and just comment on the comments. I would draw your attention to the fact that the post clearly stated that the LSE program for investment training in the cryptocurrency is worth $ 2,300, and not
Yale research, which is available online for free. And after one participant (Harlot) of the discussion said that the research is too expensive, others have already begun to develop the topic of the high cost of the research:) This post did not have any revolutionary information, but was designed to simplify the lives of those who do not have much time to cope with the 67-page research. Poor attention to the detail, in this case, was not worth the money. But still, friends, it's better to avoid such situations, because sometimes we can miss something really important.
Tip: Be more attentive. I also would like to note a comment about the fact that the only thing worth paying is insider info that reminded me of the good old movie Wall Street, 1987. If this info is valid, then, of course, it is worth its money, but as always, the problem is if the source is reliable. At the same time, in my opinion, there is no prejudice if you pay for processing large amounts of information that can lead to correct decisions. In addition to processing, there are various sources of information that cost money and those you do not have to pay for if you get "all services in one place" (from paid subscriptions to Bloomberg terminals, Capital IQ at $ 1.5-3.0K per month and above). However, this is all hard work, which, like everything on the market, does not provide you with a 100% guarantee. Insider info can be an absolute guarantee. But still, only in theory.
Tip: Be careful when choosing an information asymmetry provider, Mr. Gekko
In fact, everybody (professional players, professors, ordinary people) are trying to get close to unveil the secret of the Holy Grail and to add one more factor to the algorithm for predicting the traffic on cryptomarket. The professors from Yale tried to do this, and in general, you can just keep in mind this academic approach when making decisions in developing your model for assessing the market situation. Not so long ago, Tom Lee discovered a high correlation between the dynamics of EM with bitcoin (of course, on a certain horizon). We, in turn, suggested an even greater correlation with the dynamics of the spread of the 2-year and 10-year US Treasuries, because of which the curve will be inverted on the horizon of 1.5-2 years, which will be a significant negative signal for cryptomarket as well. If you are interested
here is a link to the article. But all these are separate signals in a multifactor analysis, which allows us all to come closer to understanding the behavior of the market.
And what factors do you rely on when making decisions and to what do you pay the most attention?