09.technical analysis
TRANSCRIPT
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Technical Analysis and Profit
Advantages
Dr. Rahul Singh
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Background
Main approaches to valuing stocks include Risk-return analysis
Fundamental analysis
Technical analysis
Some technicians use only technical analysiswhile others use both fundamental and technicalanalysis
Technicians (chartists) focus on charts of market
prices and transactions statistics Think that these statistics will reveal all
Technicians study patterns in security prices
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Theoretical Foundation
Edwards & Magee (1997) state the basic assumptions of technicalanalysis A securitys market value is based on supply and demand
Supply and demand are based on both rational and irrational factors
Security prices tend to move in persistent trends
Changes in trends occur due to shifts in supply and demand Shifts in supply and demand can be detected using charts of markettransactions
Some chart patterns tend to repeat themselves
Technicians believe past patterns will recur Therefore can be predicted
Technical analysts estimate prices Whereas fundamental analysts estimate value Technicians tend to ignore issues such as a firms riskiness and
earnings growth Instead focus on barometers of supply and demand
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Dow Theory
Originated by Charles Dow Founder of the Dow Jones Company and founder of Wall Street
Journal
Dow Theory presumes market moves in persistent bulland bear trends Often used for market as a whole, but used for individual
securities also
Types of movements defined by Dow theorists Primary trends (bull or bear market)
Secondary trends (corrections)
Market collapses or upward surges lasting a few weeks or months Tertiary moves (little daily fluctuations)
Meaningless random wiggles but should be studied to determine ifrelate to a primary trend
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Continued
Most Dow theorists do not think a new primary trend has been confirmed until pattern of
ascending or descending tops occur in both industrial and transportation averages.
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Testing the DOW Theory
Results indicate forecasts based on 4discernable patterns Recent downward trends in index are sell signals
index falls from recent peaks are sell signals
Recent upward trends in index are buy signals
Recoveries from recent declines in index are buysignals
When a buy or neutral signal was detected, ahypothetical portfolio is fully invested in index
When a sell signal was detected, a hypotheticalportfolio is fully invested in cash
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Support and Resistance Levels
Resistance level
Ceiling (peak) above which stockprice is not expected to go
Supply of security is expected toincrease
Support level
Floor (trough) below which stock priceis not expected to drop
Demand of security is expected toincrease
Suppose the following occurred
Moderate surge in trading volume at Point A Larger surge in trading volume at Point B
3 times greater than surge at Point A
May surmise that some bullish new information
caused buying pressure at Point B which overcame
the previous resistance at Point A
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Support is the price level at which demand is thought tobe strong enough to prevent the price from decliningfurther. Support levels are usually below the currentprice.
Resistance is the price level at which selling is thought tobe strong enough to prevent the price from rising further.
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Congestion Area Technicians are unable to offer reasons for price actions like this
Penetrating support line means sell Penetrating resistance line means buy
Studies examining trading range breakouts find that, after deducting
commissions, return was slightly larger than riskfree interest rate
Price fluctuates in
first congestion
area for a while.
Price rises through 50 resistancelevelold resistance level
becomes new support level.
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Relative Strength Index (RSI)
The RSI compares the magnitude of a stock's recent gainsto the magnitude of its recent losses and turns thatinformation into a number that ranges from 0 to 100
Stocks which score high on the relative strength
measure are considered good investments. Wilder recommended using 70 and 30 and overbought and
oversold levels respectively. Generally, if the RSI risesabove 30 it is considered bullish for the underlying stock.Conversely, if the RSI falls below 70, it is a bearish signal.
Some traders identify the long-term trend and then useextreme readings for entry points. If the long-term trend isbullish, then oversold readings could mark potential entrypoints.
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Formulae
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It is important to remember that the Average Gain and Average Loss are not
true averages! Instead of dividing by the number of gaining (losing) periods,
total gains (losses) are always divided by the specified number of time periods -
14 in this case.
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Moving Average Analysis
Moving averages are used to provide a smoothreference point for Individual securities
Market indices
Commodity prices Interest rates
Foreign exchange rates
Some use a 150-day (30 week) moving average
Changes each day Most recent day is added and oldest day is dropped
Following calculation is performed
M150DAPt= (1/150)(Valuet+ Valuet-1+ Valuet-149)
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Continued
Moving averages computed over short timeframes follow daily prices more closely More volatile than longer-term moving averages
Technicians analyze difference between daily
price and moving average If daily prices penetrate moving average line it is a
signal to take action If daily price moves down through a moving average, price
fails to rise for many months
Sell signal If daily prices are above moving average but difference is
narrowing Signals end of bull market may be near
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Continued
Moving average analysts recommend buying stock if Moving average line flattens and stock price moves up through moving
average line
Price of stock falls (temporarily) below moving average line that is rising
Stock price is above moving average line, falls, turns around and risesagain without penetrating moving average line
Moving average analysts recommend selling stock if Moving average line flattens and stock price drops down through
moving average line
Stock price temporarily rises above a declining moving average line
Stock price falls through moving average line and turns around only to
fall again without penetrating above moving average line
Strategy is more successful if moving average is calculated over alonger time frame
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Serial Correlation
Serial correlation measures the correlation betweenprice changes in consecutive time periods
Measure of how much price change in any perioddepends upon price change over prior time period.
0: imply that price changes in consecutive time periods areuncorrelated with each other
>0: evidence of price momentum in markets (buying afterperiods with positive returns and selling after periods withnegative returns )
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Continued Serial correlations in most markets is small,it is unlikely that
there is enough correlation to generate excess returns.
The serial correlation in short period returns is also affected byprice measurement issuesand the market micro-structurecharacteristics. Non-tradingin some of the components of the index can create a
carry-over effectfrom the prior time period, this can result in positiveserial correlationin the index returns.
The bid-ask spreadcreates a bias in the opposite direction, iftransactions prices are used to compute returns, since prices have aequal chance of ending up at the bid or the ask price. The bounce thatthis induces in prices will result in negative serial correlationsinreturns.
Bid-Ask Spread = Square root of (Serial Covariance in returns)
(where the serial covariance in returns measures the covariance betweenreturn changes in consecutive time periods)
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Filter Rule
In a filter rule, an investor buys an investmentif the price rises X% from a previous low andholds the investment until the price dropsX% from a previous high.
The magnitude of the change (X%) that triggersthe trades can vary from filter rule to filter rule.
with smaller changes resulting in moretransactions per period and higher transactionscosts.
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Illustration of Filter Rule
price changes are seriallycorrelated and that there is
price momentum
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January Effect
Returns in January are significantly higher thanreturns in any other month of the year.
The January effect is much more accentuated
for small firmsthan for larger firms.
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Week End Effect
Monday effect is really a weekend effectsince the bulk of the negativereturns is manifested in the Friday close to Monday open returns.The returns from intraday returns on Monday are not the culprits increating the negative returns.
Monday effect is worse for small stocksthan for larger stocks.
Monday effect is no worse following three-day weekendsthan two-day weekends.
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New of the Today's
Artificial Intelligence: Software systems thatattempt to replicate aspects of humanintelligence.
Expert System: Computerized decision-making
technique that embodies knowledge gleanedfrom experts.
Neural Network: Tries to mimic human brainprocessesand learns from mistakesit makes.
Chaos Theory: Holds that seemingly randomevent s actually have patternsthat computerscan detect.