Consequently there are more Christians who look like satanists than there are satanists who look like satanists" Unfortunately, the human brain does not always deal with evidence properly. 8.5 The Base Rate Fallacy. To date my second best sector based calls have been in fixed income pref shares, where I arrived late but still in time to join in. I think you could express the same ideas using the less daunting term 'conditional probability'. Not a bad shout to get it as an audio book too - I spend a lot of time reading (too much according to some) and have been looking around for material to listen to while I run etc. Ultimately, most of us are in this game to protect and grow our capital...not to convince ourselves and others that we're great stock pickers! In fact it is the opposite of drunken rationale and takes you though a history of the development of randomness theory and the need for the evolutionary human brain to look for cause and effect patterns that are either not there, or that we misinterpret. I was using Lord John Lee as an example of someone who been extremely successful at investing over many years, and whose success supports what Tom Firth wrote in that section. [Of course, some start-ups, biotechs and exploration stocks go onto doing extremely well, but the odds of selecting those in advance are small; by excluding such companies I think he improves his probability of out-performing the stock market as a whole.] In relation to stockpicking I am reminded of the book, "Simple, But Not Easy" - Stockpicking is simple but its not easy to be successful. On the other hand, with Sensitivity at 70% the probability of infection, given a negative test result, is not zero, but depends on the Base Rate. If Hand Dare events, then: P(P(HjD) = DjH)P(H) P(D) Our view is that Bayes’ theorem forms the foundation for inferential statistics. the proportion of those who have a given condition, is lower than the test’s false positive rate, even tests that have a very low chance of giving a false positive in an individual case will give more false than true positives overall. Someone else who fancies themselves at stock picking would be sticking individual companies under their microscope and assessing their potential as individuals. In fact, each new experiment and new observation (given that the experimental parameters allow a deduction of a new direction) updates our beliefs, i.e. Population growth was strong. The rate at which something happens in general is called the base rate. In other words, he greatly improved his 'base rate' probabilities of investing success by following those rules...." No shame in hedging your bets, it just helps to take the pressure off your own analysis after all. 2 Conditional Probability. yes but what on earth does any of that have to do with Bayes Theorem? Bayes Theorem is a mathematical equation where you can input the Base Rate for an event along with the probabilities associated with new information to get the actual overall probability for the event. [It is well known that 'value' stocks and stocks with high dividend yields tend as a group to out-perform over the long-run.] (GPAs) of hypothetical students. Base Rate Neglect or Base Rate Fallacy refers to our tendency to ignore data about what usually happens and instead focus just on new, recent, or interesting information. Cheat Sheets for Computational Biochemistry, "Once you know something, it's difficult to imagine oneself not knowing it.". But, the big but in general, hospitals double check some positive results and you therefore could trust your hospitals. 2. ". By the way, I thought that what you said here: Bayes’ theorem has been a controversial idea during the development of statistical reasoning, with many authorities dismissing it as an absurdity. However, to do that, we need to include the possibility that we could be one of the rare false positives. Pretty much any house builder you bought a few years ago would have done extremely well and if you knew the sector was undervalued, you could have saved yourself a lot of effort by just buying a basket of them. When the incidence, i.e. We will begin to justify this view today. ( Log Out / One great example of the Bayes theorem and how it impacts our daily decision making is the base rate fallacy. This is because I think a large part of John Lee's success was probably due to the rules he used to restrict the pool of stocks from which he constructed his portfolios. The description of John practically has the word Satanist on the tip of our tongues, and when the question comes, we are all too eager to declare that he is much more likely to be a Satanist than a Christian. The base rate fallacy is a specific mistake of this type, that is, a failure to use all relevant information in an inductive inference. People tend to simply ignore the base rates, hence it is called (base rate neglect). On the other hand, with Sensitivity at 70% the probability of infection, given a negative test result, is not zero, but depends on the Base Rate. That all makes sense and in particular your 3rd paragraph clarifies nicely. Empirical research on base rate usage has been domi nated by the perspective that people ignore base rates and that it is an errorto do so. I cannot find any of that reflected in your discussion of John Lee's approach that will help others to emulate it. Quite a few of his examples relate to gambling, but they could equally as well be attributed to our "investment" decisions. In fact at the moment I have a stockpicked quality/momentum type portfolio and a more recently a rules based high Stockrank portfolio to see what happens. - He tends to buy stocks of small, rather than big, companies. One great example of the Bayes theorem and how it impacts our daily decision making is the base rate fallacy. This updated belief (the resulting posterior probability) incorporates all the evidence of that claim. Why do knowers of Bayes's Theorem still commit the Base Rate Fallacy? As with the base rate fallacy, this process is best outlined with an example, for which I will use example 2 on the same Wikipedia page linked above. For manyyears, the so-called base rate fallacy, with its distinctive name and arsenal of catchy Terrorists, Data Mining, and the Base Rate Fallacy. We hope that these four examples helped clarify a misinterpretation of Bayes’ rule that is common among newcomers to Bayesian inference: change in belief does not equal posterior belief. really summarised the idea concisely and in very simple language - I may have to borrow your phrasing in the future! Multiple sclerosis is one of the more common, rare diseases. We have been oversold on the base rate fallacy in probabilistic judgment from an empirical, normative, and methodological standpoint. Now you have pointed it out it it seems blindingly obvious! Suppose you came to the realisation that the oil sector was poised to outperform. If I was to employ such a strategy, my worry would be that I've essentially replaced one forecasting problem (the stock picking problem) with another almost identical forecasting problem (the sector picking problem). Base Rate Fallacy。 The Base Rate in our case is 0.001 and 0.999 probabilities. But it is frequently possible to get a bearing on just one or two sectors - banks, oil companies, house builders and to act accordingly without having to complement that insight by picking the top performing individual stocks. Footnotes. This basically means. ... and so he commits himself to committing the base-rate fallacy. A witness claims the cab was green, however later tests show that they only correctly … In this case, throwing a coin will more accurately tell, if you have the disease. I have been listening to an excellent audiobook in the car (also available as a book) called, "The Drunkard's Walk: How Randomness Rules" by Prof L. Mlodinow . Base rate fallacy. All the best, [I think another way to look at this rule is he is using negative momentum to make some selling decisions, and it is well known that stocks with recent negative momentum tend to under-perform the market as a whole over the short-term.] Why are spam filters claimed to be so accurate and yet mess up so often? - He looks for moderately optimistic or better chairman's / CEO's most recent comments. Ian, P.S. Worldwide around 90 per 100,000 people are exhibiting this auto-immune disease. If you are not comfortable with Bayes’ theorem you should read the example in the appendix now. The base rate fallacy is also known as base rate neglect or base rate bias. If so, why? If we look at the investment process through this probabilistic lens, what can consideration of base rates and Bayes’ theorem offer us? Change ), You are commenting using your Facebook account. Therefore, in practice we almost always have to expand: Bayesian theorem basically tells us to look at all the cases where the evidence is true and then looking at the proportion of these evidences, where the hypothesis is also true. In the taxicab example, the base rate for blue cabs was \(15\%\). Bayes (in green) was sitting was sitting with his back to plain table, with a book and pen. Economic development was bringing many new consumers into the marketplace. 1 For a more extensive treatment see one of John Kruschke’s blog posts. In fact, with every ball and new information, Bayes was able to further narrow down the position of the first ball. My own experience is that it has several times been possible to call the oil sector and to position oneself with advantage. Interesting, thanks for getting back to me. I really think you are talking about something quite unrelated to the subject under discussion here.
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