When I first encountered this book I did a slight doubletake, "wait, THE Benoit Mandelbrot?"
"Why is he writing about financial markets?" I wondered.
I knew of Mandelbrot in mathematics, computer science, and natural sciences -- I had no idea how deep his obsession with economics was till I read this book.
In a way, it's almost depressing, his biggest contributions were to fields he didn't seem to care about as much as economics (a field that in turn didn't seem to care about his work).
Mandelbrot's work in economics, and Taleb's after him, has now become widely accepted, especially after the fact of recent financial disasters. Investors and non-investors learned the hard way that the current risk models (relying on bell curves) were inaccurate. The math that was telling us this has been around since the 1970s (arguably prior, but well-formulated in the 1970s).
Despite him sounding slightly egocentric in this book, as many reviewers charge, he's actually being incredibly modest: there's a VERY large body of natural science that would be impossible today had Mandelbrot not created a unified "fractal geometry". Personally, I found his tone more whimsical and intellectually curious than egocentric.
Historically, there was a very large and disparate body of mathematics that were unified by Mandelbrot. He defined "fractal dimension" which (in simple terms) is an exact measure of the change in detail to the change in scale of a given object. Most financial data, such as stock price over time, for example, has a "fractal dimension" greater than 1 (sometimes only slightly). This measurement of "fractal dimension" is stable and well-defined mathematically.
Furthermore, for a given object, if its "fractal dimension" is greater than its "topographical dimension", then it is, by definition, a fractal. This book does a decent job providing an overview of this idea (especially the part about measuring coastlines). Mandelbrot's account of this work is extremely fascinating, any other writer would have simply lavished praise on Mandelbrot for his ideas; Mandelbrot in turn told a wonderful story of how these ideas came to fruition.
Fractal modeling within the natural sciences is extremely common if not the norm (and technically speaking, even the internals to a Monte Carlo simulation rely on fractals, albeit simple ones). The name though is a bit of a misnomer, mathematically it means something different than what most people consider a "fractal".
That stock prices over time are "fractal" is true, again by definition, of how we measure stock prices; but not all "fractals" are simple, some of them have more than one "fractal dimension", stock prices unfortunately fall into that category.
A multifractal object is an object where more than one "fractal dimension" variable is needed to describe the object. This includes magnetic fields, fluid dynamics, and stock prices over time.
A simple fractal model would have been easier to figure out, and economists (or at least Hedge Fund managers) likely would have figured out a good formula long ago, before any mathematician labeled it as a "fractal".
All that said, a multifractal equation for investment theory, is unfortunately not fully articulated-- in other words, there's not yet an agreed upon formula that would apply to all markets (or all stocks)-- much work is still needed to get from "yes, stock prices over time are multifractal", that part we know is true and should not be controversial, to "here is the exact formula", that part, the E=mc^2 moment in finance, has not been defined. And I'm not sure economists (let alone investors) fully appreciate the implications of what that would mean.
A sound model of stock prices over time, would NOT (importantly) be a forecasting model. In other words, knowing this formula would not guarantee you money. Full stop, this is the point where investors usually lose interest.
There's an important difference between modeling the behavior of a system versus predicting exactly what the system will do several years from now.
Forecasting models are not the same as risk models and stock option pricing. The latter two are absolutely essential to a sustainable market, the first one (forecasting) is wishful thinking for relative wealth (that is, making easy money when other investors didn't). Unfortately, most of the effort in finance is put into forecasting stock prices (wishful thinking) rather than risk modeling or option pricing.
If someone discovers a sound model of stock prices over time, then it would be (by mathematic definition) a multifractal model (i.e., expressible as a multifractal model). And this would, importantly, provide an accurate risk measure that would in turn allow for usable stock option pricing, as well as provide a clear definition within portfolio management of just how risky is risky.
That said, because most markets behave somewhere between almost-normalized (almost a pure random walk, a clean and symmetric bell curve) to chaotic (highly volatile, non-symmetric and non-normalized), the typical risk measure of any market is provably higher than those currently used in modern portfolios or option prices. The exact amount higher is what remains to be understood.
To use the river dam analogy, our current investment dams are not sufficient to weather the actual storms that will (and have) hit. River networks are useful metaphors, but markets are a thing onto themselves, if rivers behaved like markets then we'd experience more turbulent waters, things like flash draughts and jumping water levels (imagine an entire river dropping a few meters instantly).
So, how to invest to survive a future collapse? This book demonstrates that this is a solvable problem yet remains unsolved (although Mandelbrot's work narrows in on an accurate range). In practice, this type of work tends to get lost in the body of inarticulate economic theories as well as in the desperately greedy investment practices.
I suspect the reason this gets so easily confused is that most people are looking for forecasting models ("what's the price tomorrow? when can I retire?") and not accurate models of risk and option pricing (ironically, preventing any forecasting model from even having a chance). Personally, forecasting models seem stupidly impossible (they would negate themselves when everyone tried to capitalize on them), but an accurate risk model and option pricing would be extraordinarly beneficial to everyone -- at the very least, to know how high our dams should be...