Lecture 8 Technical vs Fundamental Analysis Dr Peter Wheale.

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Presentation transcript:

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 Trough Buy Point Rising Trend Channel Flat Trend Channel Sell Point Peak Declining Trend Channel Trough Buy Point

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 Resistance Breakout

Simple Moving Averages 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.

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.

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 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.

Rounded Tops & Bottoms Rounding formations are characterized by a slow reversal of trend.

Rounded Bottom Chart Example

Broadening Formations These formations are like reverse triangles. These formations usually signal a reversal of the trend.

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 Double bottom Gap, should get filled Nov to Mar Trading range Descending triangles

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.” ( )

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 12- day 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 Oversold Overbought

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 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 long- term 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 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 8- wave 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)

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 , 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.”