Where Does Stock Alpha and Alpha Return Come From?
“Life Is Alpha. The Rest Is Details.” — Popular T-shirt at hedge fund manager events
There was a time not too long ago when, if you posed the question “Where does alpha come from?” to a roomful of academic financial economists, most of them would complain: “It’s a trick question! There is no alpha! Markets are strong-form efficient and you are a heathen!” Those complaints are rarer now, even among economists. Two of their own, Sanford Grossman and Joseph Stiglitz, crystallized the contradiction of strongly efficient markets in their eponymous paradox. It is summarized in Stiglitz’s 2001 Nobel Prize citation: If a market were informationally efficient, i.e., all relevant information is reflected in market prices, then no single agent would have sufficient incentive to acquire the information on which prices are based.(1)
Trading Alpha and Capital Market Efficiency
If there is no profit to be had from trading on information, traders with information will not trade, so prices will not reflect information and will not be efficient. The joke based on this paradox has an economist and his friend walking down the street, and the economist walks right over a $ 100 bill on the sidewalk. The friend asks why, and the economist replies, “If it was real, someone would have already picked it up.” (See Figure 4.1.)

- Figure 4.1 How Alfred E. Neuman might illustrate the Grossman-Stiglitz paradox. If markets are efficient, they reflect all information, and there is no profit to be had from trading on information. If there is no profit to be had, traders with information won’t trade, so markets won’t reflect it, and will not be efficient.
Warren Buffett expressed his appreciation to proponents of the efficient markets hypothesis (EMH) in the 1985 Berkshire Hathaway annual report: In the 1970s . . . institutions were . . . under the spell of academics at prestigious business schools who were preaching a newly fashioned investment theory: the stock market was totally efficient, and therefore calculations of business value — and even thought itself — were of no importance in investment activities.
We are enormously indebted to those academics. What could be more advantageous in an intellectual contest — whether it be bridge, chess, or stock selection — than to have opponents who have been taught that thinking is a waste of energy?(2)
Investment Alpha, Investment Information, and Inefficient Market
Some academics crossed the road as well. Fischer Black, after leaving MIT for Goldman Sachs, said, “Markets look a lot more efficient from the banks of the Charles than from the banks of the Hudson.”(3) Someone gets to pick up that $ 100 bill.
Back on the banks of the Charles in Boston 25 years later, Andy Lo wrote, “Profits may be viewed as the economic rents which accrue to [the] competitive advantage of . . . superior information, superior technology, financial innovation. . . .”(4) If this conjures up images of ever faster, better, larger computing engines at giant quantitative hedge funds, you are getting the message. But this idea is not suddenly true today; it has been true forever. Innovations used to use less electricity, though. In 1790, the technology that produced vast alpha for innovative traders was boats. After the American Revolution, war bonds were trading for less than a nickel on the dollar. There was a general expectation that the new country and the states would default on the substantial debt. George Washington thought this would be a bad rap for a new country, so the Funding Act of 1790 guaranteed, dollar for dollar, all debts of the new Union and the states. Word spread from the first Congress, in New York, by land messengers.
Technologically innovative traders chartered every fast-moving boat in the city, front-running the messengers and buying up bonds for pennies on the dollar.
Trading Alpha from Finance Technology and Innovation
In the early days of electronic market data feeds, the 1970s and 1980s, traders who noticed that the crusty slow centralized systems lagged the fast broadcast streams by up to 20 minutes played the same game — without boats.
In 1815, technological information advantage came from birds. In June of that year, there was a general panic in London that the empire would be routed by Napoleon. Financial markets crashed, and dealers frantically unloaded government bonds. Nathan Meyer Rothschild knew the outcome before the British press, by virtue of his use of fast carrier pigeons to bring him the news of Napoleon’s surprising defeat before the rest of the market knew. He quietly bought everything British he could get his hands on, and a few days later, when news of Napoleon’s catastrophic defeat at Waterloo arrived for the non-bird owning traders, prices soared, and Rothschild became one of Europe’s wealthiest men.
We see an important part of the beginnings of financial information technology innovation in the form of the blinking, humming refrigerator – sized computers of the 1970s. Bill Fouse, at Wells Fargo, bought a Prime computer and used it to run the first index fund, 5 the granddaddy of quantitative equity investing and the vast systematic investment industry.(6) John C. Bogle founded Vanguard in 1974, doing the same thing for retail mutual fund investors. Alas, I can’t find a picture of Bogle and his first computer, so Figure 4.2 shows Fouse with his.

- Figure 4.2 Indexing pioneer Bill Fouse with the Prime minicomputer used to run the first index fund. This machine has less computational power than a mid-range high-end digital watch of 2008. Source: Anise Wallace, “How Did Wells Fargo Get to the Top?” Institutional Investor, June 1976.
Further innovation came in the form of factor models, notably “Barr’s better betas,” a fundamental multifactor model developed by Barr Rosenberg at Berkeley. The beta that Barr had better versions of was the one in the capital asset pricing model (CAPM). The conventional wisdom in writing a book popularizing a technical topic is that each equation included cuts book sales in half.
The CAPM Capital Asset Pricing Model Does Not Address Stock-Specific Components of Investment Return
Bill Sharpe shared the Nobel Prize in economics for the capital asset pricing model. This is a simple representation of the key idea that the return to a stock is explained by the return to the broad market (e.g., the S & P 500) times the stock’s sensitivity to the market (beta) plus stock-specific returns (e.g., from news). This is a simple idea. Think of it as “a rising tide lifts all boats” and you’re pretty close. Some stocks, like utilities, are less sensitive to market returns than others (like tech or finance); they have lower betas. The average beta over all stocks is 1.0. Of course, the rising tide doesn’t explain everything; there are stock-specific components of return — things like news and earnings events — that are added on …
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All notes for this chapter about investment alpha and alpha returns:
1. The Royal Swedish Academy of Sciences, “The Prize in Economics 2001: Joseph Stiglitz,” Nobelprize.org , http://nobelprize.org/nobel_prizes/economics/laureates/2001/public.html
2. Warren Buffett, “Chairman’s Letter,” Berkshire Hathaway Inc. Annual Report 1985, www.berkshirehathaway.com/letters/1985.html
3. Fischer Black, quoted in Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein (New York: John Wiley & Sons, 1996), p. 7.
4. Andrew Lo, Market Efficiency: Stock Market Behavior in Theory and Practice (Lyme, NH: Edward Elgar Publishing, 1997).
5. Of course, there is no alpha in an index fund, unless you are doing something wrong. That came later, in enhanced index and more aggressive quant finance strategies.
6. For an excellent text on this, try Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk by Richard Grinold and Ron Kahn (New York: McGraw-Hill; 2nd edition, 1999).
7. Andrew Rudd, “Market Efficiency Revisited,” Journal of Accounting, Auditing and Finance (Spring 1984): 279 – 288.
8. Barr Rosenberg, Kenneth Reid, and Ron Lanstein, “Persuasive Evidence of Market Inefficiency,” Journal of Portfolio Management (Spring 1985): 9 – 16.
9. Barr Rosenberg and Andrew Rudd, “Factor Related and Specific Returns of Common Stocks: Serial Correlation and Market Inefficiency,” Journal of Finance (May 1982): 543 – 554. For a look at where these ideas have gone in the many intervening years, visit www.barra.com
10. For the complete math, see Pairs Trading: Quantitative Methods and Analysis by Ganapathy Vidyamurthy (John Wiley & Sons, 2004).
Wall Street Analytics
- Chapter 02 – Greatest Hits of Computation in Finance (Computational Finance, Stock Market Analysis, and Investment Trading
"A computer does not substitute for judgment any more than a pencil substitutes for literacy. But writing without a pencil is no particular advantage." - Robert McNamara
The Journal of Portfolio Management (JPM*) is one of the more upscale investment management publications around. For $500 a year, you get [...])
- Sitemap (>>>>>> READ MORE HERE < <<<<<<
)
- Overview of “Nerds on Wall Street” (Technology has transformed global markets, but this is nothing new. Markets have been shaped by machinery for hundreds of years, and this continues at a rapid pace today.
Author David Leinweber—a computer scientist who accidentally stumbled upon Wall Street and became an innovator in the application of modern information technology in trading and investing—is a well-qualified [...])
- Chapter 05 – A Gentle Introduction to Computerized Investing (Computerized Investing, Index Funds, Quantitative Investing, and Active Management
“Life would be so much easier if we only had the source code.” — Hacker proverb
The beginning of index investing in the 1970s was the result of a convergence of events, one of those ripe apple moments. Institutional investors began to use firms like A.G. Becker to actually [...])
- Contents of “Nerds on Wall Street” (Foreword by Ted Aronson
Part 1 - Wired Markets
Chapter 1: An Illustrated History of Wired Markets
Chapter 2: Greatest Hits of Computation in Finance
Chapter 3: Algorithm Wars
Part 2 - Alpha as Life
Chapter 4: Where Does Alpha Come From?
Chapter 5: A Gentle Introduction to Computerized Investing
Chapter 6: Stupid Data Miner Tricks
Part 3 - Artificial Intelligence and Intelligence Amplification
Chapter [...])
- Chapter 14 – Nerds Gone Green – Nerds on Wall Street, off Wall Street (Clean Energy and Nerds off Wall Street
This book closes with another chapter that, like the previous two, I didn’t expect to be writing. Recent headlines (Wall Street layoffs could reach 200,000, Citigroup is cutting 50,000 jobs) imply that many nerds on Wall Street (NOWS), mostly innocent bystanders in the meltdown, may soon find themselves on [...])
- Introduction to Nerds on Wall Street (Introduction to "Nerds on Wall Street"
I hope people think of this book as sort of a Hitchhiker’s Guide to Wired Markets. There are no robots parking cars for six million years, but there are robots trading millions of shares in six milliseconds, so maybe that’s close enough.
In 2006, I got a call from another nerd [...])
- Chapter 11 – Three Hundred Years of Stock Market Manipulations (300 Years of Stock Market Manipulations - From the Coffeehouse to the World Wide Web's Stock Manipulations
In previous chapters, we saw that many of the changes in securities markets brought about by information technology in general and the Internet in particular are positive, democratizing access to markets and information. We also saw that technology is [...])
- Chapter 08 – Perils and Promise of Evolutionary Computation on Wall Street (Using Genetic Algorithms, Optimization Models, and Evolutionary Computation on Wall Street
“Be careful what you ask for — you might get it.”
My enthusiasm for machine learning, described at the end of the previous chapter, led me to kiss many artificial intelligence ( AI ) frogs. This included many flavors of inductive and explanation - based learning, [...])
- Chapter 06 – Stupid Data Miner Tricks (To Err Is Human. To Really Screw Up, You Need a Computer.
— Popular Campus T-shirt, circa 1980
Stupid Data Miner Tricks in Quantitative Finance
This chapter started out over 10 years ago as a set of joke slides showing silly, spurious correlations. Originally, my quantitative equity research group planned on deliberately abusing the genetic algorithm (see Chapter [...])
- Alpha as Life
(Passive Investing - Active Investing - Alpha Returns
Index funds are passive investments; their goal is to deliver a return
that matches a benchmark index. The Old Testament of indexing is Burton
Malkiel’s classic A Random Walk Down Wall Street, first published in
1973 by W.W. Norton and now in its ninth edition. For typical
individual [...])
- Wired Markets (
Financial Markets - Electronic Markets
Not too long ago, going to a stock market meant you would meet lots of
new people who were energetically shouting, running around, and making
a mess with great quantities of paper. No more. Visiting a financial
market now is more like visiting a telephone exchange. It can be a wild
ride versus parking your cash in a few money market funds. Computers
and
network gear [...])
- Nerds
Gone Wild – Wired Markets in Distress (Financial Nerds Gone
Wild - Global Markets in Distress
The original plan for this book stopped after the three parts that
you’ve just read. These parts are about how markets became machines,
and about using more machines to pick stocks and trade them
electronically, bringing in an assortment of nifty ideas from finance
and computer science [...])
- A
Little Artificial Intelligence Goes a Long Way on Wall Street
(A Little AI Goes a Long Way on Wall Street: Artificial Intelligence
and Securities Trading
“If you give someone a program, you will frustrate them for a day; if
you teach them how to program, you will frustrate them for a lifetime.”
This is a history and technical overview of one of the earliest
artificial intelligence re (AI), and is a far cry from simple financial
planning software [...])
- Collective
Intelligence, Social Media, and Web Market Monitors (Web
Market Monitors and the Impact of Social Media on Financial Markets
"The words of the prophets are written on the subway walls." — Simon
& Garfunkel, The Sound of Silence
Opinions vary widely on the value of collective wisdom, with ample
supporting evidence both for and against. The Internet has many
positive examples: The collective ratings [...])
- Artificial
Intelligence and Intelligence Amplification (Artificial
Intelligence and Intelligence Amplification in Financial Markets
Securities Markets are Machinery Now.
This raises the question of how to best participate in the world’s new
wired markets, and this is anything but simple.
People who use information technology most effectively
will be rewarded.
Artificial intelligence (AI) as an academic discipline began at the
famous 1955 Dartmouth conference organized by John McCarthy from
Stanford [...])
- AI,
IA, and the New Research (Hunting Investment Alpha and
Trading Alpha from Online News, Social Media, and Rumors
Alpha hunters are always looking for new territory. When a strategy
becomes known and used by too many players, the collective market
impact of getting in and getting out will squeeze out all the profit
juice, and only the lowest-cost transactors (large sell-side [...])
- Stupid Data
Miner Tricks (To Err Is Human. To Really Screw Up, You Need a
Computer.
— Popular Campus T-shirt, circa 1980
Stupid Data Miner Tricks in Quantitative Finance
This chapter started out over 10 years ago as a set of joke slides
showing silly, spurious correlations. Originally, my quantitative
equity research group planned on deliberately abusing the genetic
algorithm (see Chapter [...])
- Greatest
Hits of Computation in Finance (Computational Finance, Stock
Market Analysis, and Investment Trading
"A computer does not substitute for judgment any more than a pencil
substitutes for literacy. But writing without a pencil is no particular
advantage." - Robert McNamara
The Journal of Portfolio Management (JPM*) is one of the more upscale
investment management and financial
article publications around. For
$500 a year, you get [...])
- An
Illustrated History of Wired Markets (An Illustrated History
of Wired Capital Markets
"Progress might have been all right once, but it has gone on too long."
-- Ogden Nash
This chapter is based on a number of ever-evolving dinner and lunch
talks I have given over many years, all called “Nerds on Wall Street"
irrespective of their actual subject. Many financial conference [...])
- A
Gentle Introduction to Computerized Investing (Computerized
Investing, Index Funds, Quantitative Investing, and Active Management
“Life would be so much easier if we only had the source code.” — Hacker
proverb
The beginning of index investing in the 1970s was the result of a
convergence of events, one of those ripe apple moments. Institutional
investors began to use firms like A.G. Becker to actually [...])
- Three
Hundred Years of Stock Market Manipulations (300 Years of
Stock Market Manipulations - From the Coffeehouse to the World Wide
Web's Stock Manipulations
In previous chapters, we saw that many of the changes in securities
markets brought about by information technology in general and the
Internet in particular are positive, democratizing access to markets
and information. We also saw that technology is [...])