The Money Formula: Dodgy Finance, Pseudo Science, and How Mathematicians Took Over the Markets

Written by quants who are appropriately cynical about their whole profession, this is an excellent book (for readers familiar with basic mathematical probability and willing to think as they read) on quantitative finance in general, the circumstances surrounding the global financial crisis of 2007–2008 in particular, and with concrete suggestions for improving the profession's responsibility.The first half (Chapters 1-5) provides an engaging albeit somewhat standard background and history: the random walk/Brownian motion model, the efficient market hypothesis (EMH) and the observation that stock prices changes are more variable than the former predicts; fundamental analysis and technical analysis; "modern portfolio theory", the idea there is an optimal portfolio, based on assumptions for numerical values of future mean growth and correlations, and noting that future correlations are hard to predict; "value at risk" and the difficulty in assessing extreme events. They give a good explanation of the background and meaning of the Black-Scholes pricing model and basic "vanilla" options via dynamic hedging and mention more exotic options. They describe the explosive growth in CDOs and CFSs in the run-up to 2007-8.The second half can be summarized as miscellaneous commentary on what the quants have done: here are a few examples. There are intrinsic difficulties in applying analogs of Black-Scholes to options (such as interest rates or credit risk) that are not explicitly traded and therefore cannot be directly dynamically hedged. The copula method for guessing correlations is bizarrely arbitrary and unjustifiable. There are no plausible "standard toy models" for interest rates or volatility. They give an informative classification of quant jobs (junior quant; model validation; quant developer; risk management; research quant; front office; quant trader).The most distinctive features and their central critiques are in Chapters 9 and 10. They give cute and memorable examples of the many misaligned incentives within the industry, and discuss systemic risks exemplified by the financial crisis of 2007–2008. In an Epilogue they give detailed suggestions for making the profession more socially responsible (partly along the the "skin in the game" theme emphasized by Taleb). I won't try to summarize their analysis here, but it should all be required reading for anyone wishing to comment knowledgeably on the quant world.In terms of what it says, this book is excellent, so my minor criticisms concern what it doesn't say. Some comments as a professional mathematician:They do not distinguish clearly between the specific Brownian motion model and the general martingale model; the latter is what the EMH predicts.In chapter 7 it is observed that estimates of future volatility change weekly, but so they should: the issue in testing a model is whether they fluctuate more than a martingale should.Their rhetorical question "why do abstract fields such as measure theory have a stranglehold on [finance models]?" has a partial answer I give at the start of a graduate course. Measure theory is the operating system (OS) underlying probability theory. By analogy, you can learn to use your iPad or iPhone apps without knowing the device has an OS, but if you want to do novel developments then you need to have an interface with the OS.The presumption that Math Olympiad champions would do more socially beneficial work ("mathematician cures cancer!???") in other fields suggests the authors have never spent an hour in a roomful of such people.They make a big deal of attacking the EMH, pointing out correctly that many people have profited by finding and exploiting different small deviations from EMH predictions. But (in principle and surely also in practice) if these are indeed different deviations then their overall effect should be stabilizing. Their exposition tends to conflate this with the "herd behavior" of everyone ignoring a risk or planning to get out before the day of reckoning, the background to the 2007-8 crisis.

The book is provocative review of the history of mathematical finance peppered with some British humor. And although it deals with mathematics, it is quite easy to understand.

Great book. I have been involved in the business aspects of electronic trading and HFT for about 15 years, and prior to that a regulator for about 5. While there is not a lot that is new, it is presented in a way that just hits home, for me at least. The foundations of finance are presented essentially as science and the simplifying assumptions are glossed over. I think the best part of the book, and indeed one of its constant themes, is that the *regime* where the model is valid is everything, instead of the "footnote" that it is treated as. Having both an undergraduate and graduate degree in Finance from some recognized institutions, I can attest, at least when I went to school, that the regime of validity of financial models gets short shrift, and that is overstating the point. The issues around regulators and regulation are understated based upon my first hand experience. They are a substantial catalyst to the problems.

Excellent balance between intellectual insight and irreverence. The authors tackle a series of serious questions never taking themselves too seriously. You will question some basic assumptions about the financial markets and be entertained.

Very educational book with real guy. This book is opening my eyes. Please read without prejudice. Good good good and good

Yes, folks in quant finance should be more ethical.* Regulators should be more attentive and competent, and less captured. The public should be more engaged,and require reasonable restraints on people playing with their money and their financial system (with too little downside for failure). I just said what the last 90 pages or so of this book said, aside from the authors self-consciously cracking up at their own quips. I enjoyed the review of basic financial concepts the book opens with, and its critique of those concepts.OK, there are some constructive suggestions with a little more focus here. This book explains things well as far as it goes, but is remedial for the thorough reader and thinker about this field and its economics.Speed bumps for high-frequency trading -- that I've seen in multiple other places.The authors opine the HFT's crowd's self-justifications are flimsy -- that the touted service of providing liquidity in this way doesn't hold up, and when we really need liquidity, the HFTs flee anyway. OK, maybe, but there's not real guidance here for policymakers or businesses.There are complexities in this whole picture, not reached here, in my opinion. Players (high and low, financial barons to quants to consumers) will always all exploit information asymmetries, from ancient times to now. (Even pre-human:deception is a biological and evolutionary phenomenon, that will never leave, merely assume different forms, and perhaps be fenced some, temporarily and locally. It is at the heart of survival, perhaps as the Tubes once sang, "to try and be happy while you do the nasty things you must," and is an evolutionary path-dependent process from the first cell to now, embedded in all our behaviors and cognition). This is like oxygen as a building block of our life processes, and oxygen has its destructive sides too. But back to our human-markets-today level, in perhaps a hierarchy or ecosystem of sucker-hood, borrowers of subprime loans will take the candy in front of them, as will the matching lenders making sales bonuses on the front ends of quants doing same with dodgy models (and sucker investors at the other end to take the toxic junk off their hands), and overtaxed or perhaps hack regulators will all dance in their own little pools of incentives. It is a big awkward mess that sometimes tips over, but a lot of people get value. Everybody tries to do feints while extracting their piece of the action. Everybody has original sin so to speak, and on some occasions. inflection points of failure will not be avoided, given the sprawling messiness of this whole thing. On the bright side, the lack of an educated, engaged public (this book is, I admit, trying to remedy but who will pick it up?) will perpetuate the particular subset of flaws (bugs or features?) focused on here. Our economy is fraught end to end with this. Is there really a solution proposed here? Or even the building blocks for it? A framework to go forward? My opinion is, darn little if any. The next pieces in the bridge to solutions beg to be defined (imagined first, maybe). These are financial and legal and even mass-behavioral. Credit to the authors for getting me to this thought-stage. But in this book, in the face of this challenge, the solution, (perhaps arrived at mid-book?), IMO, was when the thinking really gets tough, let's lapse into a little adolescent humor. So, credit for what was done, but I shelled out $20-plus, and expected more from a supposed (at least self-promoted) wizard of quant finance. He's been looking at this stuff a lot longer than I have, and the lack of big picture, penetrating thinking is a bit of a surprise. That won't stop me from buying his quant finance books, because I like the way the tech side is described here. So, a tip of the hat, but a tepid one.* By "ethical," the take it the authors mean, broadly public-spirited. This is a bit problematic: in this legal and competitive framework, to a quant, this would mean, "leave money on the table where others like me will take it anyway, and in fractions o;f a second." Because, it may seem, the ill-defined broad public is too slothful or ignorant or whatever, to take it, much less equitably distribute it, what is to "fix" this sentimentalist-ethical gap? This would be a quant career-killer, and markets don't seem to be "fixing" this, so I think the suggested idea is(?), government has to step in and reshape the playing field to force more to be left on the table. But this thread is not well-articulated to begin with, and then left hanging. Other than taxing a few HFT traders, and maybe the half-joke about embarrassing leaders not to hire people from Goldman Sachs (deeply dubious and repeated a few times here), I don't see much else even claimed to be productive on that here. The marginally better public knowledge this book brings to the dozen or so random people motivated to read it, and self-identifying as its audience, will not do the trick. A sequel, perhaps, gentlemen?

Wilmott books are amazing and are best known for Quant Finance. I got this book second time, for this time, as a gift to my boss's son who's going to college, I thought it would be a good thing for him to get some interest and insight into the finance world.