7. In the taxicab example, the base rate for blue cabs was \(15\%\). Why would I be more likely to get it right just because I'm analysing a different aspect of the future? Although John Lee obviously has great skill as a stock-picker, I think it is very interesting [in the light of this excellent article by Tom Firth on Bayes Theorem and conditional probability] how John Lee has increased the odds of long-term success by the rules he uses to reduce the size of the pool of stocks that he picks from. Our intuition about what is, or is not evidence, and what is strong versus weak evidence, can be terribly wrong (see, for instance, the base rate fallacy). When the incidence of a disease in a population is low, unless the test … I came across the US Guru screens on AAII whose performance data goes back 10 years or more: http://www.aaii.com/stock-screens?a=menubarHome - Click on the different year tags for % gain rankings. Jun 8, 2020 epidemiology. We can avoid this fallacy using a fundamental law of probability, Bayes’ theorem. This means that the odds are still overwhelmingly in favour of John being a Christian. Base rate fallacy example. 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. Much of the time it is really difficult to get a read on most of the market. Consumption was growing strongly. Bayes’2. If house building is the place to be then it's more important to capture the sectoral gains than it is to agonise about which individual stock is best. [Again, this reduces the chances of fraud by the management at the expense of shareholders.] 1. As we shall see, assessments that underestimate the importance of a statistical base rate commit the fallacy known as ‘base rate neglect’. Why would I be more likely to get it right just because I'm analysing a different aspect of the future? Of course, John Lee's rules are not the only way to do that. ( Log Out / A generic information about how frequently an event occurs naturally. 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 other words the base rate for share price growth in the oil sector would likely be stronger than the base rate for some other sector - say retail. generic, general information) and specific information (information only pertaining to a certain case), the mind tends to ignore the former and focus on the latter. Conclusion5. You could if you wished simply buy the sector in toto by using a collective or by buying a basket of shares. Tom, thanks for an interesting and useful article. ( Log Out / [This aligns the interests of the management with those of the shareholders and reduces the chances of fraud by the management. 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. Birn-baum showed that behavior described as "ne-glect of base rate" may be consistent with ra-tional Bayesian utilization of the base rate. (P(S) = 100%. The base rate fallacy is also known as base rate neglect or base rate bias. Base-Rate Fallacy in Intrusion Detection3. Impact on Intrusion Detection Systems 5. Someone else who fancies themselves at stock picking would be sticking individual companies under their microscope and assessing their potential as individuals. 2. really summarised the idea concisely and in very simple language - I may have to borrow your phrasing in the future! Easy Definition of Base Rate Fallacy: Don't think "99% accurate" means a 1% failure rate.There's far more to think about before you can work out the failure rate. Terrorists, Data Mining, and the Base Rate Fallacy. Bayesian inference includes conditional probability. Change ), You are commenting using your Twitter account. Existing consumers were increasing their consumption. The rate at which something happens in general is called the base rate. The base rate fallacy and its impact on decision making was first popularised by Amos Tversky and Daniel Kahneman in the early 1970’s. In other words, he greatly improved his 'base rate' probabilities of investing success by following those rules...." That's not to say that I don't pick shares too because that is part of the fun of investing, but picking them from a pre-selection of shares that meet your criteria, does give an added confidence factor. This updated belief (the resulting posterior probability) incorporates all the evidence of that claim. This test can predict to 99.9 %, if you will develop this disease (true positive) and the probability of being tested negative, while still developing lactose intolerance is pretty low (false negative: 0.04 %). I have already explained why NSA-style wholesale surveillance data-mining systems are useless for finding terrorists. A recent opinion piece in the New York Times introduced the idea of the “Base Rate Fallacy.”. He avoids start-ups and biotech or exploration stocks. [This must greatly reduce the probability of any companies in his portfolio going bankrupt. Theorem. Hi Ian, This video by Julia Galef explains more about how you can use Bayes’ theorem, not just to avoid the base-rate fallacy, but also to improve your thinking more generally. I don't want to snark about this I just do not relate what you are saying to the subject under discussion. For manyyears, the so-called base rate fallacy, with its distinctive name and arsenal of catchy I chose the title because the dash of alliteration made it sound punchy (at least in my mind...). The structure of this problem is the same as that of the base rate fallacy. Base Rate Fallacy。 The Base Rate in our case is 0.001 and 0.999 probabilities. Tournesol wrote: "yes but what on earth does any of that have to do with Bayes Theorem? ( Log Out / Consequently there are more Christians who look like satanists than there are satanists who look like satanists. Ask Question Asked 6 years, 3 months ... ("prevalence" or base rate probability). The so-called Bayes Rule or Bayes Formula is useful when trying to interpret the results of diagnostic tests with known or estimated population-level prevalence, e.g. If we test 100,000 people with this test, we get: As a person that receives a positive test result, how confident should you be in trusting that result? The chance that somethingin the outcome space occurs is 100%, because the outcome space contains ever… What I'm trying to say is that if builders or banks are in a period of decline then the answer is to avoid those sectors not to invest time and energy trying to pick the best stocks therein. Base rate fallacy, or base rate neglect, is a cognitive error whereby too little weight is placed on the base, or original rate, of possibility (e.g., the probability of A given B). Tom. When the incidence, i.e. $\begingroup$ @Semoi The base rate in this case is high enough, and the accuracy of the test good enough (at least when doing it twice in a row) that this doesn't … General explanation from Wikipedia:. But if the Base Rate is higher, it is well above zero. Base rate fallacy. I really think you are talking about something quite unrelated to the subject under discussion here. Using Baye's theorem, we get actual probabilities of competing hypotheses. Good luck with your investing, Example 1 given on the Wikipedia page is clear and easy to picture. As far as I'm concerned, whatever works, works. - He looks for established companies with a record of profitability and dividend payments. Fill in your details below or click an icon to log in: You are commenting using your WordPress.com account. The Bayesian Doctor will calculate the updated belief based on this information using Bayes Theorem and update the chart of 'Updated Beliefs'. 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. This idea is linked to the Base Rate Fallacy. In this case, throwing a coin will more accurately tell, if you have the disease. [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.] - He tends to buy stocks of small, rather than big, companies. This is the base rate fallacy in a nutshell. He says this is a way of limiting the size of his loss if he has made a bad selection of a particular stock, thereby preserving capital for better use elsewhere. 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. Is it easier? So stockpicking for me its understanding that I have all the human bias's and need all the help I can get! is has the same 99.9% true positive rate and the probability of being tested negative, while still developing MS is also pretty low (false positive: 0.02 %). Namely, if the Base rate is low, say 0.1%, the probability is practically zero. 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. (The right sector is the one with the most favourable base rate. ) An overwhelming proportion of people are sober, therefore the probability of a false positive (5%) is much more prominent than the 100% probability of a true positive. 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. [Small companies tend to perform better over the long-run than larger ones, although that is not the case in every year.] Bayes noted each new information in his book and realized, that he was able to predict, where the very first ball has fallen simply based on the descriptions of where the other balls have fallen. When we rst learned Bayes’ theorem we worked an example about screening tests showing that P(DjH) can be very di erent from P(HjD). An overwhelming proportion of people are sober, therefore the probability of a false positive (5%) is much more prominent than the 100% probability of a true positive. So the learning I take from that is to spend more time choosing sectors than identifying individual stocks. kind of stuff which is at base rather unedifying. Again I think this must improve the probability of long-term success of the stocks in his portfolio.] Thanks, Christians might possess the same characteristics only rarely but their numbers are big. Student of Life Thomas Bayes and was first published in 1763, 2 years after his death. If so, why? 1 For a more extensive treatment see one of John Kruschke’s blog posts. - He likes to invest in companies in which a number of directors are buying stocks in their own company using their own savings (as opposed to being granted options). Answer to the Thought Experiment: The exact answer to this problem depends upon what percentage of the population is homosexual. This is where we find out that our minds are poorly primed to deal intuitively with probabilistic reasoning. In the taxicab example, the base rate for blue cabs was 15% 15 %. From a personal perspective, I am still a little wary as I do not have full faith in my ability to reliably identify such trends in a timely manner due to my inexperience, ignorance and so on. Does make me think that I am not quite so good a stock picker after all and that Stockrank factors which remove my stock picker logic should be given more prominence. P( H | E ) = probability of H(ypothesis) given that E(vidence) [so “|” means “given that”] or in other words, the probability that the hypothesis holds, given that the evidence is true. All the best, I'm not saying I disagree, I'm just curious as to how you (or anyone else?) 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 . Change ), You are commenting using your Google account. An example is scrutiny (and subsequent demolition) of Fortune 500 companies who hire or fire their CEO's for what turns out to be random short term financial success of failure. Tom Firth's article above has a section entitled "Applying the Theory". I do not claim any generalised success in other sectors but I'm working on it. 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. Etc etc etc. 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. One great example of the Bayes theorem and how it impacts our daily decision making is the base rate fallacy. I'd look at things from a different angle. Ian, P.S. One criticism or thing to notice, is that the whole calculation is dependent on the “prior”, the starting hypothesis, that is waiting to be updated by the new evidence. - He uses a 20% stop-loss rule to sell any poorly-performing stocks, but he ignores stop-losses if there is a major overall market fall. We will begin to justify this view today. I concluded that what was needed was a historically successful set (or sets) of screening criteria and an investment approach that suits your personality so you stick with it. Bayes' theorem for the layman. If you are not comfortable with Bayes’ theorem you should read the example in the appendix now. At the very least, how else could you improve them but through rigorous and regular assessment? noted that research on the "base-rate fallacy" used an incomplete Bayesian analysis. Bayesian models are more intuitive to correctly specify than frequentist tests. Especially once you consider that these trends can persist for extended periods of time I suppose it could indeed be easier to identify a sector that is performing well and is likely to continue to do so. If you will allow me to play Devil's advocate for a minute though, how would you say that picking sectors is different from picking stocks? If a woman has breast cancer, the probability that she tests positive is 90% ("sensitivity" or reliability rating). Always good to question your own stock picking skills in my view. We have been oversold on the base rate fallacy in probabilistic judgment from an empirical, normative, and methodological standpoint. … Applications and examples. Seems to me that your thought process leads to the idea of emulating investment heroes - "What would Warren Buffett do?" It is turning out to be the same market beating success story in the UK with many of the Stocko Guru and Stockrank screen selections to date. Hope that makes sense. This example, I’ve visualized from a video by Veritassium called “The Bayesian Trap”. Let A and B be events. The evidence would suggest that experts and amateurs alike are poor forecasters whether it comes to company earnings or macro events - it seems the future just isn't all that clear, whatever the scale! might address those concerns. There is an old rubric to the effect that it is more important to invest in the right sector than it is to invest in the right stock - and actually that is really a restatement of Bayesian thinking. - He looks for moderately optimistic or better chairman's / CEO's most recent comments. And if oil companies are in the ascendant then you can harvest much of the potential gains without succeeding in picking the very best stock. 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. The English statistician Thomas Bayes has done an interesting experiment on how to visualize that. Change ), How to do Science: Bayes Theorem and the base rate fallacy, Distinction between Frequentist and Bayesian Approaches, being identified positive, given that you’re sick, being identified positive, given that you not carry the disease, being identified negative, while not carrying the disease, being identified negative, but actually having the disease. A person receiving a positive test could be around 97.7% confident that it correctly indicates the development of the lactose intolerance. Value stocks, for example - it seems self evident that buying dollars for 50 cents will always prove to be profitable. 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. Ask Question Asked 6 years, 3 months ... ("prevalence" or base rate probability). [I think this reduces the probability of him selecting a stock that will perform badly in the short-term.] Tom, http://www.aaii.com/stock-screens?a=menubarHome. Base-Rate Fallacy in Intrusion Detection 4. In short, it describes the tendency of people to focus on case specific information and to ignore broader base rate information when making decisions involving probabilities. I found it a bit confusing when I first read it, because I had wrongly assumed from the title that it is about the Bank of England's base rate, but of course it is nothing to do with that!

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