Great post, thank you for writing. Definitely makes me re-evaluate my own priors on fraud, and also think about structural risks inherent in companies where:
there is a trading house and fund owned by the same person (as in Bernie Madoff’s case)
the nature of the business and / or investments may not be a ponzi scheme by nature or have multi-level marketing built in, but where it’s growth model in effect looks a bit like that; i.e. growth seems highly driven by enthusiasm, is activated through social networks / word of mouth, and the intrinsic value of the business / commodity is subject to a lot of debate (in contrast with e.g. stock prices of minerals necessary in electronics manufacturing)
Cheers. For what it’s worth, I’m not sure how much one should update one’s priors based on this list, because it’s not clear how many people in finance there are in total (though maybe one could quickly do a back of the envelope calculation here). So I think that this kind of thing is more useful when thinking about what happens once you know there is fraud.
Yeah I had the same thought too. Though when I said priors I personally did not mean updating quantifiably (i.e. 0.05 --> 0.1); more in the folk sense of priors, or base rates.
Also the examples I gave are more about certain features of a business / company that I should be more sceptical about.
Right, what I meant is that you probably shouldn’t update all that much about the frequency of fraud within finance, the same way that you shouldn’t update on how often redheads are evil are after reading a list of evil redheads.
Great post, thank you for writing. Definitely makes me re-evaluate my own priors on fraud, and also think about structural risks inherent in companies where:
there is a trading house and fund owned by the same person (as in Bernie Madoff’s case)
the nature of the business and / or investments may not be a ponzi scheme by nature or have multi-level marketing built in, but where it’s growth model in effect looks a bit like that; i.e. growth seems highly driven by enthusiasm, is activated through social networks / word of mouth, and the intrinsic value of the business / commodity is subject to a lot of debate (in contrast with e.g. stock prices of minerals necessary in electronics manufacturing)
Cheers. For what it’s worth, I’m not sure how much one should update one’s priors based on this list, because it’s not clear how many people in finance there are in total (though maybe one could quickly do a back of the envelope calculation here). So I think that this kind of thing is more useful when thinking about what happens once you know there is fraud.
Yeah I had the same thought too. Though when I said priors I personally did not mean updating quantifiably (i.e. 0.05 --> 0.1); more in the folk sense of priors, or base rates.
Also the examples I gave are more about certain features of a business / company that I should be more sceptical about.
Right, what I meant is that you probably shouldn’t update all that much about the frequency of fraud within finance, the same way that you shouldn’t update on how often redheads are evil are after reading a list of evil redheads.
Oh darling, I understood your point which is why I said...