Transcript Slide 1

Seven Steps to Better Stock Trading
Teresa Lo, Founder,
InvivoAnalytics.com
Research Philosophy
Perry Mehrling, Fischer Black and the Revolutionary Idea of Finance:
“The best problems, like the best toys, are hard to exhaust. You can
approach them from a variety of different angles, each new angle
making the problem fresh again, and bringing the opportunity to
discover something new. Any idea, no matter how crazy seeming,
might work and can be worth exploring. Indeed, the harder the
problem, the more degrees of freedom one can allow in tackling it.
Fischer relished hard problems because he relished that freedom,
but in practice he did not try just anything. In his view, if a problem
does not yield to known methods, that doesn’t mean we need
more sophisticated methods, indeed probably just the opposite.
Usually problems are hard not because our technique is deficient
but because our understanding is deficient.”
The Mission
What type of trading?
I am focused on directional trading, that is,
trading when price moves up or down in one
direction. We’re not talking about any type of
arbitrage, pairs trading, market making,
portfolio timing, etc.
The Mission
The goal of directional trading is to
1. Be long when price is rising;
2. Be short when price is falling; and,
3. Be out of the market when it’s drifting.
We can also position for major reversals that set up
after a trend has been in place and exploit
mistakes made by uninformed traders.
What is Time Series Analysis?
The U.K. Office for National Statistics writes:
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A time series is broadly defined as a series of measurements of a variable taken at regular time
intervals.
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The information provided by any time series can be used as input for further analysis through time
series modelling. There are two main goals of time series modelling. Firstly, it is used to identify and
formalise the dynamic behaviour observed in time series data. This is known as time series
estimation.
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Secondly, it is used to predict the future values of time series variables. This is known as time series
forecasting. Time series forecasting is based on the idea that the past behaviour of a variable may
continue into the future. Consequently, current and past data may provide useful information for
predicting future values.
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Time series models can be broadly grouped into two categories: univariate and multivariate time
series models.
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Univariate time series models focus on a single variable. Their goal is to identify and estimate the
relationship between the current value of a variable and its own past values.
What is Time Series Analysis
In short, most traders are actually performing
UNIVARIATE TIME SERIES ANALYSIS of price or
market statistic. They are basically attempting
to forecast the future based on current and
past numbers, usually without the benefit of a
background in probability and statistics.
Economists call this econometrics. They share
the same difficulties as traders.
People Are Difficult to Predict
Federal Reserve Bank of Cleveland, March 2007: Mirror, Mirror, Who’s the Best Forecaster of Them All?
Predictions Worse Than Random
-- William Eckhardt in The New Market Wizards:
Conversations with America's Top Traders
Limitations of Time Series Analysis
Methods available are best suited to certain
types of data but it doesn’t stop people of
trying on anything and everything.
Econometricians perform tests on available data
to see if it can fit a certain model in order to
make a forecast, but this research is not
typically performed by the average trader.
Method Without a Model
Christopher Chatfield, Time Series Forecasting:
“[U]nivariate methods are particularly appropriate when there is a
large number of series to forecast, when the analyst’s skill is limited
or when multivariate methods require forecasts to be made of
explanatory variables. . . . [I]t is important to distinguish between a
forecasting method and a model. A model is a mathematical
representation of reality, while a method is a rule or formula for
computing a forecast. The latter may, or may not, depend on a
model. Arising from this distinction, we look in turn at univariate
forecasting methods based on fitting a univariate model to the
given data . . . and then at intuitively reasonable, but essentially adhoc, computational procedures. These two types of method are
quite different in character.”
Why It Works Until It Doesn’t
Price and market statistics are single, observable
data points, the result of complex interactions
between short term factors (animal spirits,
shocks) and long term factors (demographics,
economy).
Research indicates that asset prices are nonstationary, making them theoretically
impossible to forecast, no matter what the
advertisement says. All academics know this.
Further Reading
Introduction to Time Series Analysis
“This section will give a brief overview of some
of the more widely used techniques in the rich
and rapidly growing field of time series
modeling and analysis.”
http://www.itl.nist.gov/div898/handbook/pmc/
section4/pmc4.htm
The Problem in a Nutshell
We basically know that the asset prices go
through periods of trend and “chop”.
Have to be able to tell the difference between
the two in order to use the appropriate tools.
We know there is no way to make accurate
forecasts with known statistical and
econometric methods; otherwise, economists
would be able to do so consistently.
Reframing The Approach
99.9% of people enter trading with the belief that
there is order in chaos, and therefore, forecasting
(with fundamentals, indicators, cycles, E-wave,
Fibonacci numbers, etc.) becomes the focus of
their research efforts.
From what I have observed, history does repeat
mainly because people behave somewhat
predictably in that their reaction to events goes
through typical phases. The catch is that
circumstances are never exactly like the last
time.
Know Our Limitations = Profits
Once we know what we don’t know, once we
know the limitations of the usual tools used
by the average trader, we are well ahead of
the crowd that thinks there is a way to make
accurate forecasts.
We work with some simple definitions and what
can see with our eyeballs. We also learn what
uninformed traders are up to in order to
exploit their mistakes.
Trade Selectively with Visual Analysis
• Most traders look for patterns, and in the end,
they all see the same thing and try to execute
the same “breakout” trades.
• Most traders look at a number of moving
averages, now routinely announced on
financial TV.
• We must let uninformed traders take action
on these “setups of last resort”.
Color The Price Bars
Trade What You Can Identify
Price bars are classified according to the definitions
below and colored accordingly. Price bars that do not
fit the definition are not colored.
• UP (green) = higher high and higher low than the
previous bar.
• DOWN (red) = lower low and lower high than the
previous bar.
• INSIDE (yellow) = lower high and higher low than than
the previous bar.
• OUTSIDE (cyan) = higher high and lower low than the
previous bar.
Connect The Swings
Trade What You Can Identify
Price swings are connected according to the
principle that upswings will feature mostly up
bars and downswings will feature mostly
down bars.
The swings are connected accordingly and will
help identify emerging patterns, tests and
retracements as they unfold.
There is no guessing, only a process of
elimination.
Karaoke Trading
Now for Some Stylized Facts
Stephen J. Taylor, Asset Price Dynamics, Volatility, and Prediction:
“General properties that are expected to be present in any set of
returns are called stylized facts. There are three important
properties that are found in almost all sets of daily returns obtained
from a few years of prices. First, the distribution of returns is not
normal. Second, there is almost no correlation between returns for
different days. Third, the correlations between the magnitudes of
returns on nearby days are positive and statistically significant.
These properties can all be explained by changes through time in
volatility. . . . Incidentally, the three major stylized facts are
pervasive across time as well as across markets. They are apparent
in daily returns at the Florentine currency market from 1389 to
1432 (Booth and Gurun 2004), the London market for stocks from
1724 to 1740 (Harrison 1998), and the London fixed-income market
from 1821 to 1860 (Mitchell, Brown, and Easton 2002).”
Step 1: Sentiment Analysis
Start by looking at recent news headlines. This
information helps us determine which phase
of the Investor Sentiment Cycle the stock is in.
Check (i) Google Finance for market cap, recent
news stories and discussion, (ii) Yahoo Finance
for the News & Info and Analyst Coverage
sections, and (iii) CNBC Video to see who said
what on air or at the site.
Justin Mamis Investor Sentiment Cycle
http://invivoanalytics.com/2007/12/07/the-sentiment-cycle/
Ask Questions
If this stock has been rising into expected good
news, will investors take profits on the
announcement?
If this stock has been falling into expected bad
news, will buyers show up on the
announcement?
Has everyone who wants to buy it bought? If so,
who is left to take it higher?
Has everyone who wants to sell it sold? If so, who
is left to drive it lower?
Step 2: Check the Moving Averages
There are many superstitions in the world of folk
finance. We must know “the signals” because
people act on them.
For example, the 50/200 “cross” is a very popular
scan criteria used by legions of retail traders.
Their thesis goes something like this: the up or
“golden” cross (50-day MA moves above 200-day
MA) is supposed to be bullish while the down or
“death” cross (50-day MA moves below 200-day
MA) portends to weakness.
The Moving Average Cross
http://invivoanalytics.com/2010/09/17/the-magic-of-the-moving-average/
Step 3: Check Volatility
A stock that is thrashing wildly increases risk for
traders since a stop loss must be wide enough to
accommodate the price action.
Standard deviation (“historical”, or “realized”
volatility), true range and my _Smarter.Range
indicator provides us with a measurement.
In general, a low reading means the stock price is
pretty tame (even though it may be in an up or
downtrend) while a high reading means the stock
is all over the place and demands extraordinary
risk management.
Measuring Range and Volatility
http://invivoanalytics.com/2010/09/09/qa-how-to-measure-range-and-volatility/
Step 4: Check Relative Momentum
Relative momentum is an objective measurement of the
price of A against the price of B over a period of time.
This type of analysis is often called “relative strength”
(NOT the same as Wilder’s RSI or the IBD ranking) or
“ratio charts”, but since there is so much confusion, I
call it relative momentum.
We compare the stock against a benchmark index, a
broad stock index. Is the stock large cap, mid cap or
small cap? Is it a constituent of any of the major stock
indexes such as the S&P 500 Index, the NASDAQ 100
Index or the Russell 2000 Index?
RMI Histogram and PaintBar Studies
The RMI Histogram compares price action of a stock (or sector) against
an appropriate benchmark index while the RMI PaintBar colors
price bars according to the status of the histogram values.
The position of the green and red histogram bars relative to the grey
threshold line is very important. A number of combinations and
permutations can occur. Price bars are colored based on
information contained in the histogram according to these rules:
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Green = RELATIVE OUTPERFORMANCE = Histogram > 0 AND
Histogram > Threshold Line
Red = RELATIVE UNDERPERFORMANCE = Histogram < 0 AND
Histogram < Threshold Line
Yellow = POTENTIAL CHANGE OF TREND = all other combinations
Example: GLD vs. S&P 500 Index
Example: GLD vs. NASDAQ 100 Index
Example: GOOG vs. S&P 500 Index
Example: RIMM vs. S&P 500 Index
Example: WYNN vs. S&P 500 Index
Example: BRK.B vs. S&P 500 Index
Step 5: Is There a Technical Trade
Setup?
Is there a valid reason for entering this trade?
Is there a technical trade setup on this chart?
Identify trades by the process of elimination, from
smallest to largest patterns.
In the era of quantitative analysis, pattern-based
technical analysis remains 100% valid because
chart patterns are like foot prints. We track these
like a predator tracks his prey.
We draw swing lines with Smarter.Swings, connect
the dots and objectively identify the pattern.
List of Discretionary Trade Setups
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The Pause (1 bar)
The Wunderbar (1 bar)
The Fast Flag (1 swing, 2-4 bars)
The Pennant (2 swings)
The Classic Flag (2 swings)
The Holy Grail (Linda Raschke 20EMA/ADX combo)
The ABC Correction (3 swings)
The Wedge (3 swings or more on decreasing volatility)
The Reversal Patterns (Spike, Test)
The Breakout (“Last Resort”)
http://invivoanalytics.com/2008/03/09/glossary-of-trade-setups/
Example: INSP Moving Averages
Example: INSP Volatility and Range
Example: INSP Relative to S&P 500
Example: INSP Swing Chart
Look at the structure of the swings connected by the swing lines. Is there a
pattern of higher swing highs and higher swing lows? That is an uptrend.
Is there a pattern of lower swing highs and lower swing lows? That is a
downtrend. Is there no pattern? It’s probably choppy.
Step 6: Position Size and Execution
Are all your eggs in one basket?
Be sure to calculate appropriate position size to
limit risk to capital.
http://invivoanalytics.com/2008/09/06/thoughtson-position-sizing/
Traders should consider using call or put spreads to
further reduce risk. Bull call spreads and bear put
spreads can be selected using the dots generated
by Smarter.Stops.
http://invivoanalytics.com/2009/05/14/podcastfor-tuesday-option-spreads/
The Only Game in Town
-- Jack Treynor, Treynor On Institutional Investing
Example: INSP
VR (grey line) is the Volatility Ratio
http://invivoanalytics.com/2010/03/0
7/please-note-8/
Position Sizer (yellow line) is a more
accurate indication of size relative to a
risk free benchmark.
http://invivoanalytics.com/2010/06/2
1/position-sizer-for-stocks/
Step 7: Where is the Stop Loss?
Perhaps more than any other game, active
management resembles Five Card Stud: In
the long run, the "cards" research deals the
portfolio manager may matter less than his
judgement about when to raise and when to
fold.
--Jack Treynor, Treynor On Institutional Investing
Example: INSP
Smarter.Stops are engineered to
reflect observed volatility and range,
providing with a real edge over other
so-called volatility-based indicators or
bands.
•BUY RULE: A *close* above a blue dot
is buy signal.
•SELL RULE: A *close* below a pink
dot is a sell signal.
Stops must accurately reflect volatility
and range. Stops must never, ever be
based on what the trader can afford to
lose. They must be placed where they
ought to be and we reduce our trading
size as required to manage risk to
capital. This is our definitive edge.
How Much Diversification?
Diversifiable vs. Non-diversifiable risk (Facts and Fallacies of Financial Engineering, Kim, 2010)
Conclusion and Implications
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Common indicators have a weak theoretical basis but we must be
aware of superstitions because people act on these signals.
Informed traders capitalize on mistakes.
We must be aware of market sentiment because stocks can look
good from far, but are far from good.
Volatile periods identified on the daily chart cluster together.
We objectively measure volatility, price strength and weakness.
Chart patterns are valid, perhaps especially in this day and age.
Draw swing lines objectively to trace out patterns. No setup, no
trade.
Position size must be calculated conservatively. Do not put all
eggs in one basket. Do not load all the baskets onto one truck.
Use a stop loss. He who fights and runs away, lives to fight another
day.