OUR DATA DRIVEN
APPROACH TO INVESTING
In Part One, we trace recent developments leading up to the
Information Age stock market and provide a general over-
view of our data driven approach to investing. In addition,
we outline the key elements of our stock selection strategy
and trading tactics.
Chapter 1: The Stock Market in the Information Age | 3
THE STOCK MARKET IN THE INFORMATION AGE
Widely held beliefs concerning the underlying mechanisms thought to govern
stock price movements have undergone considerable change in recent years. It Pays To Be Skillful
According to the conventional wis-
For almost a half century, the view of the market taught at business schools dom, one’s expected return from
and held by a large percentage of investment professionals has been that the stocks is purely a function of the
stock market is “eﬃcient,” i.e., that no one can consistently outperform the risk one is willing to assume. One’s
risk-adjusted market return. prowess in selecting or trading
stocks should make no diﬀerence in
Eﬃcient Market Theory is multi-faceted, controversial and, in our view, pa-
tently absurd. But through sheer idiocy or self-de-
structive intent, one could choose
Eﬃcient Market Theory forms the basis for an analytical construct known strategies that are guaranteed to lose
money (by regularly placing market
as portfolio optimization, which assumes that no stock is inherently a better
orders to buy and sell thinly-traded
investment than any other stock. Though it is acknowledged that some stocks stocks, for example). And it’s safe to
are riskier bets than others, it is also assumed that the potential for reward say that, at any given time, there are
is always exactly commensurate with risk. According to this line of thought, plenty of misguided, if not self-de-
the only way to maximize a portfolio’s risk-adjusted return is by maximizing structive, participants in the stock
its diversiﬁcation. market. So, if some of their strate-
gies are doomed, isn’t it reasonable
to expect that other, more sensible,
The practical application of this theory entails buying stocks in all sectors, strategies are likely to do better than
however overvalued they might appear to be, in order to maximize diversiﬁca- an average that includes the results
tion. The wisdom of this approach went eﬀectively unchallenged for decades. of the ﬁnancially suicidal?
Shouldn’t an investor who makes
Then, in the 1990’s, along came the dot.com craze, when the market ascribed fewer mistakes than the average
astronomical valuations to companies that, in many cases, had never pro- investor be likely to beat market
duced a product or a dollar of earnings. We were told that mankind had averages?
entered a new era driven by technological innovations that would change (cont’d)
every aspect of life as we know it, including the behavior of stock markets.
4 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION
Revenue ﬁgures, hard assets, earnings, and cash ﬂow became less relevant to
Some games are so rigged (e.g., rou-
lette or slots) as to have a negative
valuation than the creativity of a hot young company’s business model or the
expected value for all who play (ex- iconoclasm inherent in its paradigm.
cept the house). The stock market
does not ﬁt this description since, Many industry veterans saw this for the speculative bubble that it was, but as
over the long-term, gains for the av- the market reached new high after new high, more and more of these older,
erage stock have been excellent. It is
wiser professionals succumbed to the sirens of the brave new information
an “inherently proﬁtable game,” in
that the expected value for a typical
era. Unfortunately for many, this period happened to coincide with the en-
passive participant (such as an owner trance into the market by vast numbers of new investors, individuals invest-
of an S&P 500 index fund) is greater ing through their 401k accounts who wanted a piece of the action. No one
than zero - in the long-term, anyway. wanted to be left behind in one of the biggest run-ups in market history.
Any inherently proﬁtable game
that can be consistently lost by the True believers in Eﬃcient Market Theory were compelled to mindlessly buy
actively incompetent should aﬀord into the speculative frenzy by the dictates of their imperative to diversify as
advantages to the actively skillful broadly as possible. Indeed, any portfolio not sporting a healthy slug of richly-
which are not available to the pas- priced tech stocks was, according to the prevailing wisdom, poorly diversiﬁed.
sive. In a 35-number roulette game
with a 36:1 payoﬀ (an inherently
Upon the collapse of the dot.com market, investors began to return to tra-
proﬁtable game), over the long run
all players are likely to win about as ditional notions of valuation, only to be assaulted by a barrage of ﬁnancial
often as the player who always bets reporting frauds and revelations of dishonest brokerage analyst recommenda-
on the same number (i.e., the pas- tions. These scandals profoundly aﬀected investors’ ability to evaluate stocks.
sive player), however whimsical their Unable to believe the reported earnings for prior periods, and facing the pros-
strategies for selecting numbers to pect that analysts (or management) might be lying about prospects for future
bet upon might be.
earnings, investors feel hard-pressed to make informed judgments concerning
Long-term stock market returns which stocks to own.
for any given investor, on the other
hand, are likely to approximate: Thus, we have seen perceptions shift from faith in an “eﬃcient market” to be-
a) the average market return lief in the “new era of mankind” market and then, sadly, to the current widely
PLUS or MINUS held view that the market is rigged in favor of insiders.
b) a return component attribut-
able to skill (or its lack) No doubt conventional thinking about the equity markets will continue to
MINUS evolve. Whatever the prevailing wisdom turns out to be in the next phase, we
c) market impact costs (driven by
continue to believe that investors can prosper in the stock market by aligning
amount of assets managed)
MINUS their strategies with the market’s predictable response to certain key factors.
d) brokerage commissions.
We mentioned two such factors in the introduction to this book: Federal
This reality is clearly at odds with the
Reserve policy and the Presidential Election Cycle. These two factors have
notion of an eﬃcient stock market.
inﬂuenced stock prices in highly predictable ways over many years, through
times of chaos, crisis, and uncertainty, as well as during periods of order
We identiﬁed these key factors – and measured their eﬀects on diﬀerent
investment styles – by analyzing more than ﬁve decades of historical market
Chapter 1: The Stock Market in the Information Age | 5
data, and we tested their practical worth in over three years of real world
Until recently, it would not have been possible for an individual or small ﬁrm
to engage in this kind of analysis. Nor would it have been possible for us
to develop Data Driven Investing– Professional Edition, with its emphasis on
quantitative stock selection strategies, quick reaction to breaking news, and fast,
cheap on-line trading.
Information Age technologies are facilitating a fundamental realignment of
opportunity away from big institutions and in favor of individuals and in-
dependent investment advisors. The Internet provides a convenient way to
gather information on stocks and monitor news sources. Computing tech-
nology enables individuals to perform the kinds of analysis that formerly took
teams of research assistants. And on-line, discount brokerage ﬁrms enable
anyone with Internet access to enter trades for as little as $7.
Of course, the advantages provided by the Information Age stock market
mean little to those who lack the expertise to exploit them.
Data Driven Investing– Professional Edition is dedicated to the proposition
that individual investors and small ﬁrms can beat the market by learning and
applying strategies that have worked consistently over long periods in the
past, and by utilizing information technologies to stay informed and achieve
better control over their trading.
6 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION
Chapter 2: Data Driven Investing | 7
DATA DRIVEN INVESTING
We believe that, in any ﬁeld of endeavor, success is a function of the wisdom
of one’s decision rules and the discipline with which those rules are applied. The Data Driven Philosophy
Nowhere is this more true than in the ﬁeld of investing.
The data driven approach is a pretty
good approach to life in general. If
Very broadly speaking, our rules for investing are: you study what has worked well in
the past and consistently apply this
Rule #1: Select stocks to own (and to avoid) based ONLY upon strategies knowledge to whatever you are do-
that have worked consistently over long periods in the past. ing, your chances of success will
probably be better than they other-
Rule #2: Employ trading tactics based on well-established patterns of in- wise would have been – especially if
vestor behavior. you are prepared to use this knowl-
edge on a moment’s notice when an
Rule #3: Develop pre-determined action plans so that the response to new opportunity arises.
data is swift, automatic, and appropriate. Closely monitor news
Good luck, it is said, occurs when
sources for stories and react as quickly as possible to news of ma-
preparation meets opportunity.
terial events. Preparation is all about the analysis
Rule #4: Stay with the program. Don’t deviate from rules 1-3, no matter of past data and the development
of contingency plans. Exploitation
how tempting the opportunity seems at the time.
of an opportunity requires the rec-
ognition of similarities between the
We call our approach Data Driven Investing™ because the strategies we opportunity and the contingency for
derive from our analysis of historical data interact continuously with real- which a plan has been devised, in ad-
time data to drive our investment process. dition to the ability to react swiftly
You can’t expect to exploit oppor-
tunities if you don’t have plans for
ﬁnding and reacting to them.
8 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION
Key Elements of Our Approach to Investing
Data Driven Investing– Professional Edition consists of a number of elements
which, in organizing this book, have been grouped into:
· Strategies for selecting stocks; and,
· Trading tactics
We will cover strategies for selecting stocks in Part Two. Trading tactics will
be presented in Part Three.
Our strategies and tactics combine to form a three step process.
How We Develop The ﬁrst step is to identify the types of stocks that are likely to achieve superi-
Screening Criteria or returns. We accomplish this by analyzing decades of historical market data
to determine the quantitative characteristics of stocks that have consistently
Data driven investing should not be performed well in each of the various monetary and political climates.
confused with what is commonly
referred to as “technical analysis.”
We do not study short-term pat-
The next step is to run quantitative screens to identify stocks possessing these
terns in stock charts to predict the characteristics. There are thousands of publicly traded companies from which
movements of individual stocks or to choose. Running screens allows us to better focus our attention on a “watch
the market as a whole. Instead, we list” of suitable candidates.
examine how fundamental forces
that move equity markets – such as
The third step is to employ time-tested tactics to trade stocks in response to
Federal Reserve monetary policy –
aﬀect traditional methods of picking
breaking news. The trading tactics that determine how and when we place
stocks (e.g., ratios of price to earn- our orders are derived both from analysis of historical data and experience
ings, price to book value, etc.), in or- gained while risking real money.
der to develop the quantitative stock
screening criteria that serve as the Success in the market requires more than just picking the right stocks. The
ﬁrst level of our selection process.
timing, pricing, and type of orders we enter can signiﬁcantly aﬀect perfor-
mance. Successful trading also depends on the discipline and consistency
with which we apply our tactics.
While we speak of this as a three step, sequential process, in practice all three
tasks may be performed more or less continuously. We constantly seek to
develop and maintain a watch list of the most desirable stocks to own, and
we apply our tactics to enter trades whenever breaking news creates an op-
portunity to buy or sell a watch list stock.
Chapter 2: Data Driven Investing | 9
Strategies for Selecting Stocks
It Pays To Be In Style
Our approach to selecting stocks involves:
The Fed Eﬀect on stock prices aﬀects
diﬀerent classes of stocks in diﬀer-
· Reacting to Federal Reserve Policy: Federal Reserve Bank monetary
ent ways. While the Fed was lower-
policy exerts a profound and predictable inﬂuence on the behavior of ing rates in 2001-2002, the overall
stock and commodity prices. The Fed Policy Cycle, alternating between market fell, contrary to conventional
expansive and restrictive phases, determines the kinds of stocks we buy expectations, but carefully selected
and sell. value stocks still did quite well.
· Buying High Relative Strength Stocks: The relative strength measure
compares a given stock’s return over a deﬁned period of time to the re-
turns of all other stocks in a given group. For example, a stock with a 12-
month relative strength of 90 has outperformed 90% of the stocks in its The Politics Behind The
group during the past 12 months. Stocks with high relative strength tend Election Cycle Effect
to outperform market indices most of the time. One notable exception
One theory attempting to explain
is “tax season” (late December through early February), when low relative the Election Cycle Eﬀect suggests
strength stocks are usually the best choice.* that presidential administrations
· Buying Nanocap Stocks: Other things being equal, we focus on stocks
tend to save initiatives favorable for
stocks until later in their terms, in
whose market capitalization is under $100 million, thereby proﬁting an eﬀort to concentrate the market’s
from the well-established pattern – supported by decades of market data gains during re-election campaigns.
– that the smaller the market value of a company, the better its stock price The Bush administration’s activities
performance is likely to be. immediately following the 2002
mid-term elections suggest this pos-
· Reacting to the Election Cycle: The four-year Presidential Election Cy- sibility.
cle exerts a strong, predictable inﬂuence on stock market behavior. Our
Harvey Pitt, the colossally un-
data clearly indicate that overall market performance improves in the
popular SEC Chairman, and Paul
years leading up to an election. Furthermore, the Election Cycle Eﬀect, O’Neill, considered by many a failed
interacting with the Fed Eﬀect, aﬀects the performance of diﬀerent in- Secretary of the Treasury, resigned
vestment styles in diﬀerent ways. shortly after the mid-term elections.
About the same time, the adminis-
· Buying Stocks with Minimal Analyst Coverage: In general, companies tration’s proposal to eliminate the
that receive little or no coverage by brokerage analysts present better op- double-taxation of dividends and
portunities, because analyst coverage tends to drive stock prices higher capital gains was ﬂoated. The market
than they would otherwise be. Wall Street coverage reduces the potential responded with big gains in 2003,
despite temporary setbacks caused
for proﬁting from market ineﬃciencies and increases the likelihood of
by the Iraq war.
trading losses. (The absence of analyst coverage contributes to the supe-
rior performance of nanocaps. Few stocks with market caps under $100
million are well covered by analysts.) However, we nearly always avoid
very large companies with minimal analyst coverage. Brokerage analysts
tend to avoid covering large cap companies with problems, rather than
issue neutral or negative reports on them.
* Source: Stock Traders Almanac 2002, page 112.
10 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION
Neglected Large Caps · Proﬁting From Deﬁciencies in GAAP Accounting Rules: We take ad-
vantage of diﬀerences between a company’s true economic condition and
Bill Matson writes: performance, and its condition and performance as reported according to
GAAP accounting principles.
“When I was a retail broker in Mer-
rill Lynch’s San Francisco oﬃce, one · Proﬁting from Fundamental Analysis: We employ fundamental analy-
Silicon Valley CFO oﬀered to open sis to evaluate news stories within the context of the subject ﬁrms’ indus-
a large corporate account with me
try attractiveness, competitive position, ﬁnancial resources, and manage-
if I could get Merrill to cover his
ment quality. This helps us assess the impact of new developments on
critical earnings and cash ﬂow trends.
“Merrill’s industry analyst told me
that, even though the company Trading Tactics
was large enough to merit coverage,
he didn’t want anything to do with The key elements of the tactics with which we trade stocks can be
it. Shortly thereafter, the company’s summarized as:
stock nosedived. This illustrates a
major reason some large companies
don’t get their share of coverage
· Understanding and Applying the Psychology of Investing: When buy-
(i.e., they are accidents waiting to ing or selling shares, we remain acutely aware that we are interacting with
happen).” real people, who are motivated by the same psychological underpinnings
that drive us all. Prejudices, preferences, fears, and illusions impair inves-
When a large company is in such
tors’ ability to make rational decisions and delay their reactions to new
bad shape that analysts shun it, you
should too. information, leading to predictable patterns of behavior which can be ex-
ploited to our proﬁt.
(This is consistent with data pre-
sented in the September/October · Reacting to News Stories and Signiﬁcant Price Changes: We react
1997 Financial Analysts Journal ar- swiftly and surely to news stories and signiﬁcant price changes aﬀecting
ticle entitled “Is There a Neglected- the companies on our watch list. Usually, when a company meeting our
Firm Eﬀect?” by Craig Beard and selection criteria is the subject of a “good news” story, we try to be ﬁrst in
line to buy. When a company we own is the subject of a “bad news” story,
we sell immediately in most cases.
· Responding to Volume: Our trading decisions are informed by volume,
meaning that our evaluation of events (such as price movements and
Trading Illiquid Stocks news stories) is partly based on the volume of other investors’ trades en-
tered in response. Market reactions conﬁrmed by high volume are more
Orders to buy or sell $1,000 worth credible and likely to be sustained than reactions accompanied by low
of stock can cause multi-million dol- volume.
lar changes in a thinly-traded com-
pany’s market cap, but signiﬁcant · Proﬁting from the Impatience of Others: On thinly-traded stocks with
price changes accompanied by light wide bid-ask spreads, we enter standing orders to buy and sell shares at
volume are almost always temporary.
the edges of the spread. We call this tactic shopkeeper trading, because
Knowing that the price will probably
gravitate back to where it was before
by maintaining an “inventory” of open orders, we supply convenience
can provide valuable trading insight. (i.e., liquidity) similar to the way the owner of a retail store provides a
quick, convenient way to make purchases. We earn the spread whenever
impatient traders enter market orders to buy or sell (except in the rare
Chapter 2: Data Driven Investing | 11
instances when these traders have correctly anticipated a signiﬁcant price
trend – then we lose). A Really Stupid Thing To Do
· Proﬁting from Established Trading Patterns: We trade on the basis of Placing a market order to buy or sell
short-term patterns established over many years. Examples include tax- a thinly-traded stock is usually a re-
motivated year-end trading patterns (e.g., the “January Eﬀect”), weekly ally stupid thing to do – but lots of
people do it anyway.
patterns that often lead to temporarily depressed Monday morning prices,
and patterns in the trading of spinoﬀ stocks.* Shopkeeper trades provide a way to
proﬁt from such stupidity.
· Making Money from Losers: We buy put options or short sell in situ-
ations where a falling stock price is highly predictable, such as when an
overpriced stock is the subject of a very bad news story. When a company
reports its ﬁrst quarterly proﬁt following an extended period of losses,
we often buy the stock before the market can fully respond to the turn-
· Staying Fully Invested: Except during conditions we call “Panic Years”
(see Chapter 11), we typically remain fully invested in equities, augment- Why Spinoffs Bounce Back
ing our exposure with margin borrowing. Whenever our portfolio runs
out of buying power, we sell the worst performers and reinvest the pro- When a company spins oﬀ a busi-
ceeds in stocks associated with good news stories. ness unit, it issues shares in the new-
ly formed corporation to its existing
· Hedging Against Catastrophe: We cross-hedge a portion of our hold- shareholders.
ings in order to reduce our overall risk. We typically buy put options on
The recipients of these shares often
the NASDAQ 100 index (i.e., QQQ’s) or richly-priced growth stocks sell them shortly thereafter, prompt-
during Fed-Election Cycle phases that favor value stocks, switching to ed by brokers who earn easy money
puts on the Dow Jones Industrial Average (DIA’s) during phases that by telling clients to unload the stock
favor growth stocks. and buy something “more in line
with their ﬁnancial plans.” Also,
many institutional investors are
Integrating Stock Selection Strategy and Trading Tactics forced to sell spinoﬀ shares due to
prohibitions against their investing
To summarize our data driven approach to investing, we continuously reﬁne in small cap stocks.
our stock selection criteria by backtesting investment strategies against the
backdrop of critical cycles, such as the Federal Reserve monetary and Presi- In general, share prices of spinoﬀ
companies bounce back after this
dential Election Cycles. We periodically run quantitative screens to update a
watch list of stocks possessing the appropriate criteria, focusing primarily on
nanocap stocks (deﬁned as companies with market caps of between $10 mil-
lion and $100 million).
We carefully monitor news sources, especially the Internet, for news stories
aﬀecting the companies on our watch list. We also watch for signiﬁcant price
changes on these stocks (because signiﬁcant price movements often presage
news events). When a news story breaks or a signiﬁcant price change occurs,
we swiftly implement predetermined actions in response.
* “Institutional Demand and Security Price Pressure: The Case of Corporate Spinoﬀs,”
Financial Analysts Journal, Sept./Oct. 1993 by Brown and Brooke, and “Restructuring
Through Spinoﬀs” Journal of Financial Economics, 1993, by Cusatis, Miles, and Woolridge.
12 | DATA DRIVEN INVESTING– PROFESSIONAL EDITION
We buy stocks on the watch list when good news stories break. When there
is bad news or a signiﬁcant price decline on heavy volume, we usually sell the
aﬀected stock immediately.
We try to stay fully invested, including buying on margin, and cull our losing
positions whenever we run out of purchasing power in order to free up funds
for new purchases. We hedge against catastrophe with put options on major