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 investors, without special access to information, it offers what is likely the best financial advice they will ever get: It is hard to consistently beat the market, especially after fees. A passive strategy will do better in the long run.
Of course, no one thinks of oneself as a typical individual investor. That might be your brother-in-law or the guy across the hall. And index funds are just not as much fun as picking stocks. It’s called passive investing for a reason. Alpha, outperforming a passive benchmark, is the goal of active investing. Even Malkiel has admitted to actively managing some his own money.(*) Recent additions to the Forbes 400 list include more than a few people who seem unusually adept at finding alpha, and keeping a piece of it.
The basic fee structure in the hedge fund world is “2 and 20.” Managers are paid 2 percent of assets and 20 percent of alpha. Similar arrangements are also used for performance paid to institutional managers, blurring the distinction between these types of buy-side firms. To see how this works, consider a $100 million portfolio, benchmarked against Treasury bills. If the manager produced a return equal to the T-bills, the alpha would be zero, and the manager’s fee would be $2 million, all from the asset-based portion. Unless the firm gave really good parties or had a great story, it would probably be replaced, since the client would end up earning the T-bill rate minus 2 percent, or something like a passbook savings account.
With a skilled, lucky, or skilled and lucky manager, the situation could be quite different. If the T-bills returned 3 percent that year and the hedge portfolio returned 28 percent, then the manager’s alpha is 25 percent, $25 million on the original investment. Under the 2-and-20 plan the firm would get to keep 20 percent of that, another $5 million on top of the $2 million in asset-based fees. The client keeps $18 million, substantially more than the meager few percent the client would have gotten in Treasuries.
A $100 million portfolio is small as hedge funds go.
It costs money to do the research or proprietary trading to produce that 25 percent alpha, so by the time all the bills are paid, that $7 million the manager takes is seriously pared down. But when the fund gets larger, the economies of scale kick-in in a major way. Investment strategies don’t scale to the sky, but it is (approximately) true that the cost to run a $1 billion portfolio is not that much more than for $100 million. In that case, the manager on the 2-and-20 plan takes home $70 million with performance as in the example. On $10 billion, the manager takes home $700 million, which begins to look like serious coin—even on the right side of the tracks in Greenwich, Connecticut. Deliver this kind of performance consistently, and you can raise the rates to 4 percent of assets and 40 percent of alpha, which would pay the $10 billion manager $1.4 billion with the same performance scenario.
This is where those billion-dollar paydays for hedge fund managers we read about in Institutional Investor and Parade magazine come from, and why people with what seem like good, solid $5 million annual paychecks at places like Goldman Sachs leave to start their own hedge funds. The whole alpha ecosystem depends on, and is a creature of, technology. Before computers, it was sufficiently tedious to compute the alpha of a portfolio that no one did it.
Comparing one stock to another is easy. Real portfolios are much messier. They have cash flows in from additional investments, and cash flows out from payments or withdrawals. There are dividends paid in from long positions, and dividends paid out from shorts. Stocks split, companies merge, symbols change. International investments’ returns are subject to currency variations to the extent that they are not hedged, and if they are, there are costs associated with those hedge positions.
Bill Fouse, who started the world’s first index fund, tells a story about the early days of performance measurement. In the 1950s and 1960s the reporting from investment managers to clients was almost anecdotal. The manager would invite the clients up to the lavishly decorated dark wood-paneled office and show them a list of stocks in their portfolio, with the prices paid and the recent prices.
Nothing would be said about cash flows, holding periods, or dividends, and nothing about closed positions. It was easy to pretty up the report by cleaning out the losers. Everyone would sit around the conference table to review the list of holdings, and enjoy a fine n-martini lunch.
In 1968 A.G. Becker, a brokerage firm, changed the game by using computers to keep accurate annualized scores for clients’ accounts, and by comparing the results with index benchmarks. This was possible only because the firm had acquired one of the early mainframe computers, a room-filling behemoth like the IBM System 360. The news wasn’t pretty. Any asset managers were much better at telling a good story and coming up with a good lunch than they were at managing assets. As Fouse tells it, managers resisted the idea of quantitative performance measurement.
They sent out the word, “Hire them, and you can’t hire us.” Some of their objections were valid; a simple performance measurement doesn’t consider the risks that a manager is allowed to take. Other measures—like the Sharpe, Jensen, and Treynor ratios(**) — refined the idea, but the alpha industry was born and has been growing ever since.
Finance students and Wall Street sorts around the world yearn for knowledge that will let them find ever more alpha. This raises the simple question of Chapter 4 – Where does alpha come from? That question opens this part of the book. The chapter explains why the search for alpha is more than just a snipe hunt, and why the people who find it may be more than just plain lucky.
Chapter 5 – A Gentle Introduction to Computerized Investing, starts out with a description of indexing, the great granddaddy of all quant equity strategies, and how it is transformed into active quant strategies by adding information beyond knowledge of an index’s constituent stocks.
In the last of this part, Chapter 6 – Stupid Data Miner Tricks, we see how with the right mix of hubris, stupidity, and CPU cycles, it is possible to do some real damage to your financial health. In investing, as in the bomb squad, knowing what not to do is extremely worthwhile.
>>>>>> READ MORE HERE < <<<<<<
* This surprising admission came in a dinner speech at the Investment Management Network “Superbowl of Indexing” Conference (December 1996, Palm Springs, California). No performance figures were disclosed.
** The Sharpe ratio is a measure of management skill that adjusts pure alpha (value added) by the variability of that value added. The others (Jensen & Treynor) are refinements based on characteristics of the portfolio, such as beta. They are less commonly used. Details are here http://en.wikipedia.org/wiki/Sharpe_ratio.
Wall Street Analytics
- Forward by Ted Aronson (Nerds on Wall Street Forward by Ted Aronson
Quantitative finance is not a topic usually associated with laughter. That is about to change with the publication of Nerds on Wall Street.
I was first exposed to Dave Leinweber’s wit when he delivered a speech entitled “Nerds on Wall Street.” I believe the event happened 20 or 25 [...])
- Chapter 10 – 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 [...])
- Chapter 01 – 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 [...])
- Praise for “Nerds On Wall Street” ("Leinweber isn't half as crazy as people said! He foresaw the profound change that wired technology would bring to markets (robots trading millions of shares in six milliseconds). Now he nails the Stupid Financial Engineering Tricks that dumped the markets, and offers his patented, sound insights on how the nerds will help bring us back."
[...])
- Chapter 03 – Algorithm Wars (Algorithmic Trading Strategies and Automated Stock Trading
“How about a nice game of chess?” — WOPR computer in "War Games"
There used to be two market structures for U.S. equity traders to contend with: the NYSE (for listed stocks) and NASDAQ. Recent counts put the number at roughly 40. Many are sources of dark liquidity, which sounds [...])
- Sitemap (>>>>>> READ MORE HERE < <<<<<<
)
- 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 [...])
- More Praise for “Nerds on Wall Street” ("New technologies are exploited first by "alpha geeks," folks with the skills to push the envelope. This is as true on Wall Street as it was on the web. Leinweber was one of those alpha geeks, but is also the first to chronicle the innovation process from early adopter to mainstream acceptance."
Tim O’Reilly
Founder & CEO, [...])
- 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 12 – Shooting the Moon – Stupid Financial Technology Tricks (Stupid Financial Technology Tricks and Global Economic Collapse
Like many others from the stock side of greater Wall Street, I felt blindsided by the events of 2008. “Blindsided” is actually a gross understatement; I felt like the guy who comes home and finds the neighbors were running a meth lab that has exploded and flattened the [...])
- 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 [...])