Successful investors are often viewed like celebrity chefs, with much time and effort spent by their acolytes, students and rivals alike in analysing their “recipes” for success. (One of the main differences being, of course, the size and nature of the steaks/stakes involved.)
Warren Buffett, in other words, is – to those keen to amass their own fortunes – what Jamie Oliver is to the home cook who yearns to be more than just a preparer of food.
In The Money Formula: Dodgy Finance, Pseudo Science, and How Mathematicians Took Over the Markets, authors Paul Wilmott (pictured above) and David Orrell (below, left) don’t make the comparison of successful financiers with successful chefs, but according to tax commentator Gerry Brown, who has had a read and whose review of their book is below, they do analyse in some detail the various formulas that experts have come up with over the years for ensuring investment success.
Paul Wilmott is an Oxford-educated, British mathematician, lecturer and quantitative finance expert who has managed his own hedge fund and acted as a consultant to well-known financial institutions.
David Orrell, a Canadian who also has a degree in mathematics from Oxford, is an applied mathematician who has worked extensively in the area of mathematical forecasting.
This book is divided into two parts. The first part covers the development of quantitative finance, and explains its key principles, such as risk analysis, bond pricing and portfolio insurance. It traces the development of financial derivatives, and shows that mathematical techniques have been used not simply to price these, but to expand their use to the point where they dwarf the “real” economy.
(It has been estimated, they note, that the notional value of derivatives in 2010 was $1.2 quadrillion ($1,200,000,000,000,000).)
The second part of the book is a critique of the current quantitative finance industry, and its ongoing development. The books ends with a thought provoking epilogue, which consists of the authors’ “wish list” of principles they argue should underpin a global financial engineering code, which at the moment doesn’t exist.
For those new to the world Wilmott and Orrell are describing here, “quantitative finance” is the term used to describe the for when mathematics are used to understand the evolution of financial markets – and ideally, make reliable predictions. (The authors use the term “quants” to describe practitioners of this area of finance.)
The book examines the development of investment theory, starting with Isaac Newton (who lost money in the South Sea Bubble, perhaps the earliest documented market crash), and moving, via Scotland’s Adam Smith, to the Chicago School of economists in the second half of the 20th century.
It also introduces some basic probability theory and the maths behind “random walks”. (Non-quant readers needn’t worry, as the maths involved is not intimidating.)
The authors take the reader to Eugene Fama’s efficient market hypothesis (EMH), which assumes that market participants have access to the same information, act in a rational manner and drive prices to an equilibrium between supply and demand.
However, we are well aware that investors do not, in fact, act in accordance with these assumptions – they have an asymmetric attitude towards losses and gains. Investors are more concerned with loss avoidance than generation of gains. They avoid selling poorly performing stocks, and blindly follow market trends.
The authors quote a study by the CFA Institute which suggests that “No investment strategy based on mainstream finance theory can … protect investors from market-wide crashes”.
So if investment theory has “failed”, what happens in practice?
Wilmott and Orrell discuss the development of derivatives, particularly options, and show how, given certain assumptions and using “dynamic hedging”, a portfolio could be constructed that was theoretically risk free.
The problem was (and is) that the assumptions might not hold good in all situations. Remember Enron?
According to the New York Stock Exchange, the average holding period for stocks fell from 100 months in 1960 to six months in 2010. Since then, trading has been dominated by “high frequency trading” (HFT) firms which can make millions of trades each day – often holding their purchases for a few seconds. Is this investment? Or gambling? Or something else?
Companies have developed “bots” that look for inconsistences in prices and execute trades, buying and then selling (or vice versa) within seconds, hoping to make tiny profits on a vast numbers of transactions.
Most of these trades are in derivatives – the nature and value of the underlying stock is largely irrelevant. If such companies are making huge profits, who is losing? Individuals with retirement funds, quite possibly.
For me, the second part of the book lacks the rigour of the first part. The authors are concerned with the prevalence of risk in financial markets, but they cover topics which, though interesting, seem to have little relevance to their arguments.
They argue that the bankers offering complex financial products don’t always understand the risks, and that when a bank goes bust, “the stock market collapses, and house prices tumble, it’s your bank account, your shares and your house equity that suffer”. Few would doubt that analysis.
Wilmott suggests a Tobin tax – a tax on transactions. He argues that this tax could be set at a level which dissuades HFT, but won’t affect deter hedging. A tax at a maximum level of 0.008%, he argues would achieve this objective.
His “wish list” also includes a desire for better regulation, better education and “negative bonuses”.
I enjoyed this book. It is written in a humorous, quirky style, although it is not always an “easy read”. It covers a lot of ground, and has three “exercises” for readers which I found particularly entertaining – and thought provoking.
Anyone interested in investment theory (and that should include everyone working in financial services) would find it a worthwhile read.
UK RRP £19.99 (€25.00/ US$32.50)