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3.72 AVERAGE
3.72 AVERAGE
informative
slow-paced
The author does a good job of explaining the main issues regarding prediction in today's financial markets, with an extension really to most human matters. Taleb is the philosopher in this book; the finance part is just his background and what the news could immediately latch on to. His essential claim (I hope I got this right) is that many real-life things have a scalable distribution which exposes them to very extreme events in linear scale: something twice as strong is half as likely to happen. This is in direct contract to basic Central Limit Theorem approximations, which say something twice as strong is usually much much less likely to happen (it has exponential scale).
The four stars is for the readability as well as the theory. It is a very accessible book for non-mathematicians yet it wasn't too frustrating for me. That's because a) he has chapters that have some math terms to satiate me like sugar crystals, and b) the philosophy is still very interesting and scientific. His style is preachy and in spite of that you are not put off by his words. Part of the reason is that he is playing the negation: he is not claiming to predict an event's time, just its future existence. By laying off, he invites you to admit the possibility first and the eventuality later.
I docked him a star because when he started applying it to other events (eating schedules, etc.) it seemed more like him defining a philosophy by its ubiquity. That's not the case; a philosophy does not need to universally fit to teach a lesson and set a path that is better than the past. In this case, it is clear that for many real-life and asymmetric instances, using basic statistics is not going to cut it. We don't need to preach it onto other things like eating.
The book is still a fun read and in my opinion far better than Fooled by Randomness, which is just different. This is the book from Taleb that you want to read; it's the one that speaks to what you've inherently considered in the contradiction between models & performance.
The four stars is for the readability as well as the theory. It is a very accessible book for non-mathematicians yet it wasn't too frustrating for me. That's because a) he has chapters that have some math terms to satiate me like sugar crystals, and b) the philosophy is still very interesting and scientific. His style is preachy and in spite of that you are not put off by his words. Part of the reason is that he is playing the negation: he is not claiming to predict an event's time, just its future existence. By laying off, he invites you to admit the possibility first and the eventuality later.
I docked him a star because when he started applying it to other events (eating schedules, etc.) it seemed more like him defining a philosophy by its ubiquity. That's not the case; a philosophy does not need to universally fit to teach a lesson and set a path that is better than the past. In this case, it is clear that for many real-life and asymmetric instances, using basic statistics is not going to cut it. We don't need to preach it onto other things like eating.
The book is still a fun read and in my opinion far better than Fooled by Randomness, which is just different. This is the book from Taleb that you want to read; it's the one that speaks to what you've inherently considered in the contradiction between models & performance.
Made me remember why I studied math instead of philosophy.
Eclectic. Rich. Fun. Non technical-friendly. Nassim is a proper BS detector and is also a diva and we’re all here for it.
My quick takeaway is that people are terrible at risk assessment and predicting, including the "experts". That doesn't sound so crazy but there's no way you can read Taleb without changing your perspective on the way the world works and how people interpret what's going on.
Love the theory and concepts, but didn't care for the writing.
challenging
informative
reflective
slow-paced
I really didn't like the fact he's so full of himself in the book. He ignores other's opinion out right and sure maybe they're partially wrong, but the author speaks as if he's completely right and other's are absolutely wrong.
I almost gave up at least four times. This book makes good points, but the meandering prose, mixed with the author’s (mostly) unfounded disdain for several disciplines and the Nobel prize, while not missing a single opportunity to remind the reader how amazing and smart he is made this feel like a diary written as a stream of consciousness.
Take the same points, condense them down without the self aggrandizement and the snark and you have a great 100-page book!
Take the same points, condense them down without the self aggrandizement and the snark and you have a great 100-page book!
Challenged my thoughts with a pinch of humour + realism.
Black Swan event;
• an outlier/rarity
• extreme impact
• retrospective
Black Swan logic: what you do not know is far more relevant than what you do know.
Key points from Black Swan:
• The normal bell-curve distribution predict approximation of results that does not necesserily accounts for Black Swan outliers —shift the distribution significantly. Contributed by pure chance and the tendency for obvious outliers which leads to significant impact due to specific circumstances.
* Gaussian bell curve —few data sets can be effectively analysed using the normal bell distribution in reality.
• Platonifying: The human mind tends to create an illusion of understanding things that are too complex for it to grasp, making chaotic events seem orderly and predictable in retrospect, and overvaluing neat classifications.
• Complex systems are viewed as random due to the lack of available or comprehensible information —predictability is relative to knowledge.
• Predictive models are distorted as a result of generating simplified narratives of the causes of Black Swans and demonstrating their probability after the fact prevents people from taking into account the many complex factors that actually caused the event caused the event, which then distorts predictive models.
• Bad predictions are mostly rooted in extrapolating from the past, which does not always take into account actual, current threats faced.
• Almost evryone of us, especially experts in rapidly changing fields, have tendency to be overconfident in their knowledge —additional information of a topic leads to blind confidence in uninformed determination and unwillingness to revise conclusions and predictions.
Strategy for withstanding Black Swan:
• Be true to ourselves especially on our ignorance/things we do not know
• consider decisions based on available information instead of long-term assumptions
• contemplate on possible risk and adopt methods to minimise risk
I have a lot of comments on it as well but honestly a good read
I'd read this once before a while back and decided to read it again. It is a thought provoking book and Taleb spares no punches for government officials, bankers, economist and statisticians. It comes across that he is anti prediction and anti building any sort of models but that is not the case. What he is against is having an overconfidence because you have a model and blindly applying a model for prediction that doesn't work. I guess as a statistician, I could be offended and dismiss the book as a bunch of rubbish, but there is some truth in what he says and I'm not a particular strong fan of models. I am a big fan of the data and making good decisions based on the data, which doesn't necessarily require one to build a model, particularly where there is a lot of data. Fun book to read, quite different than most that you will read.