London School of Business & Finance (HK) Ltd.

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Lecture 8
Technical vs Fundamental Analysis
Dr Peter Wheale
Technical Analysis
Technical analysts (some called “Chartists” because of a
reliance on graphs and charts, or trend analysts because
they use algorithms and models such as moving
averages to identify turning points and trends), use
graphs and diagrams as signs or signals of path of asset
prices extensively as the basis of investment decision
making rather than using fundamental analysis, which
focuses on economics factors such as expected return
and risk.
Assumptions of Technical Analysis
• Market forces determine values
• Supply and demand are driven by rational and irrational
behaviour
• Security prices move in trends that persist for long
periods of time
• Shifts in supply and demand can be observed in market
price behaviour
Fundamentalist Assumptions
• Economic factors determine asset prices
• Asset prices respond quickly to market information - is
cornerstone of fundamentalist approach
• Reason-based approach to asset valuation
• Efficient Market Hypothesis (EMH) – that all available
information (associated with both fundamentalist and
technical analysis) is impounded quickly in the current
price of securities -
EMH
• The EMH holds that:
(1) That stocks are always in equilibrium
(2) That it is impossible for an investor to consistently beat the market
Levels of market efficiency:
Weak-form efficiency – states that all information contained in past price
movements is fully reflected in current market prices. If this were true then
information about recent trends in stock prices would be of no use in
selecting stocks.
Semistrong-form efficiency:
the semistrong form of the EMH states that current market prices reflect all
publicly available information (not “insider” information).
Strong-form efficeincy:
the strong-form of efficiency states that current market prices reflect all
pertinent information, whether publicly available or privately held – even
insiders could not earn abnormal returns in the stock market.
Underlying Assumptions of
Technical Analysis
• Trading via technical analysis involve a number of
assumptions about markets
▫ The market value of any good or service is determined solely by
the interaction of supply and demand
▫ Supply and demand are governed by numerous factors, both
rational and irrational
Underlying Assumptions of
Technical Analysis
• Technical analysis assumptions:
▫ Disregarding minor fluctuations, the prices for
individual securities and the overall value of the
market tend to move in trends, which persist for
appreciable lengths of time
▫ Prevailing trends change in reaction to shifts in supply
and demand relationships and these shifts can be
detected in the action of the market
Advantages of Technical
Analysis
• Unlike fundamental analysis, technical analysis is not
heavily dependent on financial accounting statements
▫ Problems with accounting statements:
 Lack information needed by security analysts
 GAAP allows firms to select reporting procedures, resulting in difficulty
comparing statements between firms
 Many psychological and other non-quantifiable factors do not show up in
financial statements
Difference between the
approaches
• Fundamentalists consider that a security’s price is
determined by the supply and demand for the underlying
security based on its economic fundamentals, e.g.
expected risk-return relationship.
• Fundamentalists believe they can forecast value
changes by analysing earnings and other data in the
public domain.
• Technical analysts base assume that stock price
changes take a long time period to change.
Advantages of Technical
Analysis
• Fundamental analyst must process new information and
quickly determine a new intrinsic value, but technical analyst
merely has to recognize a movement to a new equilibrium
• Technicians trade when a move to a new equilibrium is
underway but a fundamental analyst finds undervalued
securities that may not adjust to “correct” prices as quickly
• It incorporates psychological as well as economic reasons
behind price changes
• It indicates buy and sell options (trading rules) – but does
explain reasoning behind the decisions
• Avoids the use of accounting data and accounting
conventions
Challenges to Technical
Analysis
• Challenges to basic assumptions
▫ Empirical tests of Efficient Market Hypothesis (EMH)
show that prices do not move in trends
• Challenges to technical trading rules
▫ Rules that worked in the past may not be repeated
▫ Patterns may become self-fulfilling prophecies
▫ A successful rule will gain followers and become less
successful
▫ Rules all require subjective judgement
Technical Trading Rules
and Indicators
• Stock cycles typically go through a peak and trough
• For instance, consider the following stock price graph
over time, and then consider how a technical analyst
would interpret the chart
• If the trading rules worked, the price movements would
become a self-fulfilling prophesy – once a breakout price
is reached, the buying pressure would cause a security’s
price to increase
• Trading rules fall into two main groups:
general market indicators
individual stock selection indicators (graphs and
moving averages)
Technicians two views
In analysing markets technical traders tend to take one of
two views:
(1) Follow the smart money view – following the market by
“jumping on the bandwagon” (on the basis that the
majority of investors are right about the market)
(2) The contrarian view – doing the opposite of what most
investors are doing (on the basis that most investors
are wrong)
Typical Stock Market Cycle
Stock
Price
Typical Stock Market Cycle
Stock
Price
Declining
Trend
Channel
Peak
Flat Trend Channel
Sell Point
Rising Trend Channel
Buy Point
Trough
Declining
Trend
Channel
Buy Point
Trough
Contrary-Opinion Rules
• Many analysts rely on rules developed from the premise
that the majority of investors are wrong as the market
approaches peaks and troughs
• Technicians try to determine whether investors are
strongly bullish or bearish and then trade in the opposite
direction
• These positions have various indicators
Contrary-Opinion Rules
• Mutual fund cash positions
▫ Buy when the mutual fund cash position is high, sell
when low
▫ Assumes that mutual fund managers are poor judges
of market turning points
• Credit balances in brokerage accounts
▫ Buy when credit balances increase, sell when credit
balances fall
• Investment advisory opinions
▫ Buy when advisory firms become more bearish
Mutual Funds – Cash Position
A fund’s cash position (i.e. ratio of fund’s cash/total
fund’s assets) is a function of investor expectations and
the institution’s view of market expectations.
If this reflects investors’ expectations, contrary-opinion
technicians will use this cash ratio as the buy and sell
indicator in the market.
Schweser suggest if the ratio >13% buy, and if the ratio
<5% sell.
Similarly with investor-brokerage accounts – if credit
balances are going down – the contrarian technician will
sell and visa versa.
Opinions of Investment
Advisory Services
IAS = bearish opinions/total opinions
If the ratio is > 60%, it implies the market is bearish, so
contrarians would buy, and if the ratio <20% it implies
investment advisors are bullish, so contrarians would sell.
For example, this would imply that contrarians would buy
Greek securities at the present time (March, 2010) because
advisors are bearish on Greek stocks and sovereign debt.
Contrary-Opinion Rules
• OTC versus NYSE volume
▫ If OTC volume increases relative to NYSE volume, sell
since speculation increases at peaks
• Chicago Board Options Exchange (CBOE) put/call ratio
▫ Buy when option purchasers are bearish (when the
put/call ratio increases)
• Futures traders bullish on stock index futures
▫ Sell when speculators are bullish
Follow the Smart Money
• While contrary-opinion rules assume that most investors
are not smart, these indicators seek to follow the path of
sophisticated, and assumed smart, investors
• The Barron’s Confidence Index
▫ Measures the yield spread between high-grade bonds
and a large cross section of bonds
▫ Declining (increasing) yield spreads increase
(decrease) this index, and are a bullish (bearish)
indicator
Follow the Smart Money
• T-Bill - Eurodollar yield spread
▫ Decreases in this spread indicates greater confidence, and is a
bullish indicator
• Debit balances in brokerage accounts
▫ Such balances represent buying on margin, which is assumed to
be done by largely sophisticated investors
▫ Increases are a bullish signal
Other Market Indicators
These indicators are meant to gauge overall market
sentiment
• Breadth of market
▫ Advance-decline (number of advancing minus the
number of declining issues)
• Short interest
▫ Cumulative number of shares sold short in uncovered
positions
▫ Actually a bullish indicator, as it indicates potential
demand
Other Market Indicators
• Stocks above their 200-day moving average
▫ Technicians use moving averages to compute general
trends, and evaluate current stock prices relative to
those trends
• Block uptick-downtick ratio
▫ Gauges institutional investor sentiment by looking at
the proportion of block trades that resulted in an uptick
(buy) or a downtick (sell)
Put-Call ratio = puts/calls
if the PCR>0.50 the market is bearish – buy
if the PCR<0.35 the market is bullish - sell
Stock Price and Volume
Techniques
•
•
The Dow theory
1. Major trends are like tides in the ocean
2. Intermediate trends resemble waves
3. Short-run movements are like ripples
▫ Key is to identify the nature of a current price
movement
Importance of volume
▫ Ratio of upside-downside volume
▫ Price movements are not very important unless they
are “confirmed” by volume
Stock Price and Volume
Techniques
•
Support and resistance levels
▫ Support level: the level that a price is unlikely to
decline below; when price reaches the support
level, demand surges for the stock
▫ Resistance level: the level that a price is unlikely to
rise above; when price reaches the resistance level,
we observe selling or “profit taking”
▫ Movements below (bearish) and above (bullish) this
range provide indicators
Stock Price and Volume
Techniques
•
Moving average lines
▫
▫
Moving average prices are calculated and track for several
different time periods
When the shorter-term moving average line is consistently
above the longer-term line, it is considered a bullish signal
Stock Price and Volume Techniques
• Relative-strength (RS) ratios
▫ For individual stocks and industry groups
▫ Measure relative price changes across different stocks
or industries
• Other Indicators
▫ Bar charting
▫ Multiple indicator charts
▫ Point-and-figure charts
• Idea is to get an overall feel from numerous technical
indicators
Technical Analysis of Foreign
Markets
• Some foreign market data is more limited than U.S.
market data
▫ Greater reliance on stock and volume data
• Merrill Lynch publishes various indicators for several
countries
• Technical analysis of foreign exchange rates
▫ Traders look for trends in exchange rates that could
give rise to profit opportunities
Technical Analysis of Bond Markets
• Many of the same indicators and trading rules can be
applied to bond markets
• Generally not possible to get bond market volume data
Technical illustrations
• Technical analysis is the attempt to forecast stock prices
on the basis of market-derived data.
• Technicians (also known as quantitative analysts or
chartists) usually look at price, volume and psychological
indicators over time.
• They are looking for trends and patterns in the data that
indicate future price movements.
Basic Technical Tools
•
•
•
•
•
Trend Lines
Moving Averages
Price Patterns
Indicators
Cycles
Trend Lines
• There are three basic
kinds of trends:
▫ An Up trend where prices
are generally increasing.
▫ A Down trend where
prices are generally
decreasing.
▫ A Trading Range.
Support & Resistance
• Support and resistance lines
indicate likely ends of
trends.
• Resistance results from the
inability to surpass prior
highs.
• Support results from the
inability to break below to
prior lows.
• What was support becomes
resistance, and vice-versa.
Support
Breakout
Resistance
Simple Moving Averages
MSFT Daily Prices with 10-day MA
9/23/93 to 9/21/94
60
55
50
Price
• A moving average is simply
the average price (usually
the closing price) over the
last N periods.
• They are used to smooth out
fluctuations of less than N
periods.
• This chart shows MSFT with
a 10-day moving average.
Note how the moving
average shows much less
volatility than the daily stock
price.
45
40
35
30
1
21
41
61
81
101
121
Date
141
161
181
201
221
241
Price Patterns
• Technicians look for many patterns in the historical time
series of prices.
• These patterns are reputed to provide information
regarding the size and timing of subsequent price
moves.
• But don’t forget that the EMH says these patterns are
illusions, and have no real meaning. In fact, they can be
seen in a randomly generated price series.
Head and Shoulders
• This formation is
characterized by two
small peaks on either
side of a larger peak.
• This is a reversal
pattern, meaning that it
signifies a change in the
trend.
H&S Top
Head
Right Shoulder
Left Shoulder
Neckline
H&S Bottom
Neckline
Left Shoulder
Right Shoulder
Head
Head & Shoulders Example
Sell Signal
Minimum Target Price
Based on measurement rule
Double Tops and Bottoms
• These formations are
similar to the H&S
formations, but there is
no head.
• These are reversal
patterns with the same
measuring implications
as the H&S.
Double Top
Target
Target
Double Bottom
Double Bottom Example
Triangles
• Triangles are
continuation
formations.
• Three flavors:
▫ Ascending
▫ Descending
▫ Symmetrical
• Typically, triangles
should break out about
half to three-quarters of
the way through the
formation.
Ascending
Symmetrical
Symmetrical
Descending
Rounded Tops & Bottoms
• Rounding formations
are characterized by a
slow reversal of trend.
Rounding
Bottom
Rounding Top
Rounded Bottom Chart
Example
Broadening Formations
• These formations are
like reverse triangles.
• These formations
usually signal a reversal
of the trend.
Broadening Bottoms
Broadening Tops
DJIA Oct 2000 to Oct 2001 Example
What could you have known,
and when could you have known it?
DJIA Oct 2000 to Oct 2001 Example
Nov to Mar
Trading range
Descending
triangles
Double bottom
Gap, should get
filled
Technical Indicators
• There are, literally, hundreds of technical indicators used
to generate buy and sell signals.
• We will look at just a few that I use:
▫
▫
▫
▫
Moving Average Convergence/Divergence (MACD)
Relative Strength Index (RSI)
On Balance Volume
Bollinger Bands
• For information on other indicators see my Investments
Class Links page under the heading “Technical Analysis
Links.”
(http://clem.mscd.edu/~mayest/FIN3600/FIN3600_Links.htm)
MACD
• MACD was developed by Gerald Appel as a way to keep
track of a moving average crossover system.
• Appel defined MACD as the difference between a 12day and 26-day moving average. A 9-day moving
average of this difference is used to generate signals.
• When this signal line goes from negative to positive, a
buy signal is generated.
• When the signal line goes from positive to negative, a
sell signal is generated.
• MACD is best used in choppy (trendless) markets, and is
subject to whipsaws (in and out rapidly with little or no
profit).
MACD Example Chart
Relative Strength Index (RSI)
• RSI was developed by Welles Wilder as an oscillator to
gauge overbought/oversold levels.
• RSI is a rescaled measure of the ratio of average price
changes on up days to average price changes on down
days.
• The most important thing to understand about RSI is that
a level above 70 indicates a stock is overbought, and a
level below 30 indicates that it is oversold (it can range
from 0 to 100).
• Also, realize that stocks can remain overbought or
oversold for long periods of time, so RSI alone isn’t
always a great timing tool.
RSI Example Chart
Overbought
Oversold
On Balance Volume
• On Balance Volume was developed by Joseph Granville,
one of the most famous technicians of the 1960’s and
1970’s.
• OBV is calculated by adding volume on up days, and
subtracting volume on down days. A running total is
kept.
• Granville believed that “volume leads price.”
• To use OBV, you generally look for OBV to show a
change in trend (a divergence from the price trend).
• If the stock is in an uptrend, but OBV turns down, that is
a signal that the price trend may soon reverse.
OBV Example Chart
Divergence, OBV failed
OBV confirms
trend change
but doesn’t
lead
Bollinger Bands
• Bollinger bands were created by John Bollinger (former FNN
technical analyst, and regular guest on CNBC).
• Bollinger Bands are based on a moving average of the closing price.
• They are two standard deviations above and below the moving
average.
• A buy signal is given when the stock price closes below the lower
band, and a sell signal is given when the stock price closes above
the upper band.
• When the bands contract, that is a signal that a big move is coming,
but it is impossible to say if it will be up or down.
• In my experience, the buy signals are far more reliable than the sell
signals.
Bollinger Bands Example Chart
Sell signal
Buy signals
Sometimes, the buy
signals just keep coming and
you can go broke!
Dow Theory
• This theory was first stated by Charles Dow in a series of
columns in the WSJ between 1900 and 1902.
• Dow (and later Hamilton and Rhea) believed that market
trends forecast trends in the economy.
• A change in the trend of the DJIA must be confirmed by
a trend change in the DJTA in order to generate a valid
signal.
Dow Theory Trends (1)
• Primary Trend
▫ Called “the tide” by Dow, this is the trend that defines the longterm direction (up to several years). Others have called this a
“secular” bull or bear market.
• Secondary Trend
▫ Called “the waves” by Dow, this is shorter-term departures from
the primary trend (weeks to months)
• Day to day fluctuations
▫ Not significant in Dow Theory
Dow Theory Trends (2)
Does Dow Theory Work?
• According to Martin Pring, if you had invested $44 in
1897 and followed all buy and sell signals, by 1981 you
would have accumulated about $18,000.
• If you had simply invested $44 and held that portfolio, by
1981 you would have accumulated about $960.
Elliot Wave Principle (1)
• R.N. Elliot formulated this idea in a series of articles in
Financial World in 1939.
• Elliot believed that the market has a rhythmic regularity
that can be used to predict future prices.
• The Elliot Wave Principle is based on a repeating 8wave cycle, and each cycle is made up of similar
shorter-term cycles (“Big fleas have little fleas upon their
backs to bite 'em - little fleas have smaller fleas and so
on ad infinitem”).
• Elliot Wave adherents also make extensive use of the
Fibonacci series.
The Elliot Wave Principle (2)
5
B
A
C
3
4
1
2
Fibonacci Numbers
• Fibonacci numbers are a series where each succeeding number is
the sum of the two preceding numbers.
• The first two Fibonacci numbers are defined to be 1, and then the
series continues as follows: 1, 1, 2, 3, 5, 8, 13, 21…
• As the numbers get larger, the ratio of adjacent numbers
approaches the Golden Mean: 1.618:1.
• This ratio is found extensively in nature, and has been used in
architecture since the ancient Greeks (who believed that a rectangle
whose sides had the ratio of 1.618:1 was the most aesthetically
pleasing).
• Technical analysts use this ratio and its inverse, 0.618, extensively
to provide projections of price moves.
Does Elliot Wave Work?
• Who knows? One of the biggest problems with Elliot
Wave is that no two practitioners seem to agree on the
wave count, and therefore on the prediction of what’s to
come.
• Robert Prechter (the most famous EW practitioner)
made several astoundingly correct predictions in the
1980’s, but hasn’t been so prescient since (he no longer
gets much press attention).
• For example, in 1985 he predicted that the market would
peak in 1987 (correct), but he thought it would peak at
3686 (± 100 points).
• The DJIA actually peaked on 25 August 1987 at
2722.42, more than 960 points lower.
Too Many Others To List
• As noted, there are literally hundreds of indicators and thousands of
trading systems.
• A whole semester could easily be spent on just a handful of these.
• To close, just note that there is nothing so crazy that somebody
doesn’t use it to trade.
• For example, many people use astrology, geometry (Gann angles),
neural networks, chaos theory, etc.
• There’s no doubt that each of these (and others) would have made
you lots of money at one time or another. The real question is can
they do it consistently?
• As the carneys used to say, “You pays your money, and you takes
your chances.”
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