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Equity Report Reference

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

Seasonality refers to particular time frames when stocks/sectors/indices are subjected to and influenced by recurring tendencies that produce patterns that are apparent in the investment valuation.   Tendencies can range from weather events (temperature in winter vs. summer, nurse physician probability of inclement conditions, more about etc.) to calendar events (quarterly reporting expectations, find announcements, etc.).   The key is that the tendency is recurring and provides a sustainable probability of performing in a manner consistent to previous results.

Identified below are the periods of seasonal strength for each market segment, as identified by Brooke Thackray.   Each bar will indicate a buy and sell date based upon the optimal holding period for each market sector/index.

 

 

A seasonality study preferably uses at least 10 years of data. Most of our studies use 10-20 years of data, however, data may not always be available for periods greater than 10 years in length.   Studies using less than ten years of data can be used, but they tend to be less reliable. Results of shorter term studies have a higher chance of being skewed by a single data point.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

Seasonality refers to particular time frames when stocks/sectors/indices are subjected to and influenced by recurring tendencies that produce patterns that are apparent in the investment valuation.   Tendencies can range from weather events (temperature in winter vs. summer, vitamin probability of inclement conditions, try etc.) to calendar events (quarterly reporting expectations, announcements, etc.).   The key is that the tendency is recurring and provides a sustainable probability of performing in a manner consistent to previous results.

Identified below are the periods of seasonal strength for each market segment, as identified by Brooke Thackray.   Each bar will indicate a buy and sell date based upon the optimal holding period for each market sector/index.

 

 

A seasonality study preferably uses at least 10 years of data. Most of our studies use 10-20 years of data, however, data may not always be available for periods greater than 10 years in length.   Studies using less than ten years of data can be used, but they tend to be less reliable. Results of shorter term studies have a higher chance of being skewed by a single data point.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

By definition, discount seasonal investing includes:

  • A start date for an investment
  • An end date
  • Either price strength or weakness between the start and end dates for the chosen equity, pathopsychology sector, index or commodity.

A seasonality study preferably uses at least 10 years of data. Most of our studies use 10-20 years of data, however, data may not always be available for periods greater than 10 years in length. Studies using less than ten years of data can be used, but they tend to be less reliable. Results of shorter term studies have a higher chance of being skewed by a single data point.

Results using at least ten years of data tend to be stable for long periods of time, particularly when annual recurring fundamental reasons causing seasonality are unchanged. However, “statistical” slippage can occur. For example, the U.S. high tech sector has a period of seasonal strength from the end of September to a time between the end of December and the end January. On average, the sector peaks between start of the annual Las Vegas consumer electronics show in the second week in January and start of fourth quarter earnings reports near the end of January. Optimal time to own high tech securities for a seasonal trade based on month end statistical data over a 10 year period frequently flips back and forth from the end of December to the end of January. Seasonality studies on equity indices, sectors and commodities need to be re-examined once a year to see if slippage has occurred.

Time length for intermediate periods of seasonal strength or weakness ranges from five weeks to seven months. In addition, special short term periods often related to holidays have been identified. Examples include strength just before and after U.S. Thanksgiving and strength from just before Christmas until just after the New Year. Also, longer term “cyclical” periods lasting several years have been identified. Most notable is the four year economic or “presidential” cycle. Data for longer term cyclical periods frequently can be overlaid with annual data to refine seasonal entry and exit points.

Most periods of seasonal strength are NOT followed by a periods of seasonal weakness. In most cases, periods of seasonal strength are followed by a period of random performance. Markets moving from a period of seasonal strength to a period of seasonal weakness are rare.

Measuring Seasonality

Seasonality is measured in three ways:

  • Average return during the chosen period expressed as a percent
  • Reliability expressed by the number of profitable periods out of at least the past ten periods.
  • Performance relative to a major equity index such as the S&P 500 Index or the TSX Composite Index.

A seasonal investment by definition is profitable more than 50% of the time. If frequency of profitable trades is 50% and frequency of unprofitable trades is 50%, results are random. Confidence in a seasonal trade increases with the frequency of profitable trades. A confidence level for a seasonal trade exceeding is 70% is preferred. A confidence level of 80% frequently is available. A confidence level of 90% is relatively rare. A confidence level of 100% is extremely rare.

Primary Factors Influencing Seasonality

Seasonality happens because of a series of annual recurring events. The job of a seasonality analyst is to examine if the annual events are likely to recur prior to a period of seasonal strength. If annual recurring events are less likely to occur, the seasonality analyst will avoid recommending a seasonal trade.

The classic example is a series of recurring events that trigger the annual period of seasonal strength in the equity market. The S&P 500 Composite Index has an historic period of seasonal strength from the end of October to the beginning of May. The strategy is known as the “Buy when it snows, sell when it goes.”   Equity markets historically start to move higher near the end of October when the first snowfalls frequently appear. Equity markets tend to reach a seasonal peak around April when last of the snow melts away.  Equity markets in developed nations have a similar seasonal pattern.

Combining Seasonality with Technical and Fundamental Analysis

Using seasonality as a “stand alone” tool to make investment decisions is NOT recommended. Seasonality is a useful analytical tool, but only when used in conjunction with fundamental and technical analysis. Trades based on seasonality alone are profitable in say seven or eight times out of 10, but are unprofitable in two or three times out of ten.

The same can be said for strategies based on technical analysis. Reliable technical patterns such as head-and-shoulders patterns are accurate approximately 75% of the time. However, they are not accurate 25% of the time.

Trades based on fundamental analysis alone also are not recommended. Fundamental analyst picks may be profitable most of the time. However, results from a stock picking contest during 2006 run by a major Canadian newspaper showed that even the best fundamental analysts are far from perfect. The contest requested each participant to choose one stock to buy at the beginning of 2006 and to hold until the end of the year. Participants included a college student, a financial journalist and seven of Canada’s top fundamental analysts. You guessed it! The winner and only person to choose a stock that appreciated in 2006 was the college student.

Chances of a choosing a profitable seasonal trade are greatly enhanced if all three methods of analysis are combined. Of equal importance, chances of losing capital are greatly reduced.

Seasonality analysis is the bridge between fundamental and technical analysis:

  • Fundamental analysis tells us what to buy and sell
  • Technical analysis tells us when to buy and sell.
  • Seasonality analysis tells us what and when to buy and sell.

Identifying Seasonal Trades

Several methods are available to identify periods of seasonal strength:

  • Comments on seasonality made by fundamental analysts can be confirmed by completing a seasonality report based on data for 10 years or more. Fundamental analysts are notorious for commenting on seasonal trends based on 2-5 year data. Ten year studies will confirm or not confirm their comments. A few fundamental analysts on the Street are well aware of long term seasonal trends and base the timing of their recommendations at least partially on seasonality. They usually are analysts who have been in the financial service industry for 10 years or more.
  • Recurring spikes can be examined on monthly price charts using 10 or more years of data. Recurring spikes at the same time each year either on the upside or downside can suggest the possibility of a seasonal trend.
  • Companies and sectors can be examined when they have at least one quarter per year when revenues, earnings, cash flow and/or Earnings Before Interest, Depreciation and Amortization (EBITDA) are seasonally strong. Examples include retail merchandising and consumer electronic companies in the fourth quarter or airline companies in the summer. Seasonal strength in their share price normally begins just prior to their period of seasonal financial strength and ends just prior to the end of their seasonal period of financial strength.
  • Data for 10 years or more can be screened to identify equities and sectors showing periods of above average strength relative to their benchmark index. Preferred benchmarks are the S&P 500 Index for U.S. equities and sectors and the TSX Composite Index for Canadian equities and sectors.

Seasonality Myths

One of the greatest myths on the Street is that North American equity markets usually experience a “summer rally”. Traders frequently start talking in May about the possibility of a rally in the stock market in the June to August period. Talk by traders normally escalates during a period when North American equity markets are experiencing a short term correction. The message is “Don’t worry, be happy. The market will come back”. A long term study of the market confirms that a rally lasting three weeks or more inevitably happens during the three month summer period. However, traders fail to mention that the three week rally period has no consistency. Timing of the appearance of the three week rally is random and can appear at any time during the three month period. Of greater importance, traders fail to mention that virtually all three month periods during the year record at least one period of recovery lasting three weeks or more regardless of season.

Another myth is the expression “Sell in May and go away”. The myth originated from an actual period of seasonal strength in the base metal sector. Base metal prices as well as base metal equity prices tended to peak early in May and bottom near the end of September. The main reason was the annual operating shut down by base metal smelters in Europe in July and August for Europe’s extended holiday season. Demand by smelters for base metal concentrates slowed in May and recovered in September. Currently, base metal prices continue to show this seasonal pattern, but the pattern has been muted over the years. Market share of base metal smelter capacity in Europe has declined while market share in the Far East and South America has increased. Over the past decade, the “Sell in May and go away” phrase became adopted by the media, but with a slightly different twist. The phrase was transformed into expectation for weakness by broadly based North American equity indices such as the S&P 500 Index and the TSX Composite Index from the end of May to the end of September. The myth is not supported by fact. The S&P 500 Index and the TSX Composite Index has gained in five of the past ten periods from the end of May to the end of September. Unlike the period of seasonal strength by North American equity markets from the end of September to the end of April, performance in the May to September period is random. This period does not have a sufficient number of annual recurring events to influence equity markets.

Another myth is that the month of October is a weak and dangerous month for North American equity markets. The myth is based on the fact that substantial downdrafts in North American prices have occurred in the month of October. October 1929 and October 1987 are seared into the minds of traders. However, data during the past ten years suggests that fears of weakness in October no longer are founded. The S&P 500 Index has advanced in five of the past 10 periods and the TSX Composite Index has gained in seven of the past 10 periods. On the contrary! October frequently is the month of the year when important seasonal lows frequently are reached.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

Why use technical analysis in conjunction with seasonal investing? Seasonality analysis is a useful tool when looking at a general time to enter and exit equity markets and sectors. However, and seasonality analysis is not precise. It only gives an approximate time when trades can be made. Equity markets and sectors rarely reach important lows and highs on the dates identified by seasonality studies. The solution is to use technical analysis to optimize seasonal entry and exit points. Normally, check technical analysis will provide optimal entry and exit points within one month (plus or minus) of an identified period of seasonal strength. Net result: investment performance usually is enhanced significantly.

Using Short Term Momentum Indicators To Optimize Seasonal Entry and Exit Points

Several well known momentum indicators are preferred for optimizing seasonal entry and exit points. They can be used separately or jointly. Choice of indicators is determined by experience and comfort of the investor. Short term momentum indicators based on daily data are preferred when seeking entry and exit points for seasonal strategies. Indicators using weekly data are useful as a supplement to indictors using daily data, but, by definition tend to be less precise for entry and exit.

Three momentum indicators are preferred:

  • Moving Average Convergence Divergence (MACD)
  • Relative Strength Index (RSI)
  • Stochastics

All use moving averages in one form or another when calculated. By definition, all will provide entry and exit signals shortly after a short term low or high has been reached.

MACD is the best known and most widely used momentum indicator. Entry and exit points are determined by a cross over of two moving averages. A buy signal is given when the indicator is oversold (i.e. below -1.0) and a positive cross over occurs. Please refer to the enclosed chart for demonstration of a buy signal. Conversely, a sell signal occurs when the indicator is overbought (i.e. above 1.0) and a negative cross over occurs.

MACD buy and sell signals are more relevant when divergence between the indicator and price of the security occurs on an intermediate basis. The enclosed chart gives a trend line showing divergence between the MACD indicator and the price of crude oil.

MACD is the slowest and latest of the three momentum indicators. RSI and Stochastics are faster, but are more prone to false signals.

RSI is slightly faster. When the indicator declines to 30% or lower, the security is oversold. The investor looks for a recovery above 30% for a recovery entry point. Conversely, when the indicator is above 70%, the security is overbought. The investor looks for weakness below 70% for confirmation of an exit point.

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Chart courtesy of StockCharts.com www.stockcharts.com

Stochastics is the fastest momentum indicator. A drop below 20% indicates that the security is oversold in the short term. A recovery above 20% indicates a short term entry point. Conversely, a move above 80% indicates that the security is overbought in the short term. Weakness below 80% indicates a short term exit point.

Bullish Percent Index

Bullish Percent Index is a useful indicator when used in conjunction with short term momentum indicators. Its strength is its unique method of calculation. Data for Bullish Percent Index does not include moving averages applied by other indicators.

The root of the Bullish Percent Index is Point and Figure charts showing the trend of a security. A chart with a “bullish” trend has a current column of “x”s moving higher than the previous column of “x”s. Following is an example:

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IBM is one stock out of 500 stocks in the S&P 500 Index that is considered to have an uptrend or “bullish” trend based on point and figure analysis. StockCharts.com adds up the total number of stocks in the 500 that have an uptrend and publishes the data as a Bullish Percent Index for the S&P 500 Index. Bullish Percent Index for the S&P 500 is updated daily and published at www.stockcharts.com at $BPSPX.

Bullish Percent Indices are available for well known broadly based equity indices and U.S. sectors including the S&P 500 Index, The S&P 100 Index, the Dow Jones Industrial Average, the NASDAQ Composite Index, the NYSE Index, the NASDAQ 100 Index, the Dow Jones Transportation Average, the Dow Jones Utilities Average, the TSX Composite Index and the ten S&P sector indices.

Bullish Percent Index works best for an index with a large number of holdings. For example, it works better for the 500 S&P 500 Index stocks than for the 30 Dow Jones Industrial Average stocks. The Bullish Percent Index based on a small number of securities tends to be more volatile (i.e. choppy) and prone to false signals.

A 15 day moving average has been proven through experience to be a reliable “cross over” measure to confirm a change in trend on Bullish Percent Index charts.

Like any indicator, Bullish Percent Index is not perfect. However, when used in conjunction with momentum indicator and seasonality, it eliminates much of the “noise” that occurs during an intermediate cycle. It also can be used in conjunction with momentum indicators only (i.e. excluding seasonal influences) to identify additional intermediate trading opportunities. Following is a Bullish Percent Index on the TSX Composite Index showing entry and exit points that combine Seasonality, MACD and the Bullish Percent Index. Arrows indicate entry and exit points using seasonality (i.e. Buy when it snows, sell when it goes” from the end of September to the end of April). Zeros represent other entry and exit points based on MACD and Bullish Percent Index only:

clip_image004[7]

Charts courtesy of StockCharts.com www.stockcharts.com

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Chart courtesy of StockCharts.com www.stockcharts.com

 

Other Useful Technical Indicators

Trend Lines

Trend lines are useful for confirming the direction that a chart is moving. They can provide early warning signs when direction is changing. However, they should not be used a “stand alone” buy or sell technical signal.

By definition, a trend line needs three or more points to connect. For an uptrend, the three or more points are located below indicated prices. For a downtrend, the three points are more are located above indicated prices. Confirmed support and resistance levels often are useful for establishing trend lines. Following are examples.

clip_image012[7]

Chart courtesy of StockCharts.com www.stockcharts.com

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Chart courtesy of StockCharts.com www.stockcharts.com

Moving Averages

Moving averages can be considered as another form of trend line. They indicate a chart’s direction, but with more flexibility.

The moving average most frequently used for longer term direction is the 200 day or 40 week moving average. Both averages are virtually the same. The 200 day moving average frequently acts as a support or resistance level.

The 200 day moving average also is an attractive indictor for measuring risk and potential return. Assuming charts eventually revert to a neutral level determined by the 200 day moving average, the percent gain above or below the 200 day moving average can indicate amount of risk/potential return.

The second moving average frequently used for medium term direction is the 50 day moving average. A break above the 50 day moving average is an “alert” signal to explore a possible buying opportunity. Conversely, a break below the 50 day moving average is an alert signal to explore a possible selling opportunity.

Target Prices

Target prices are interesting, but not very useful. They frequently are provided by technical analysts as a guideline for potential return from an investment, fully realizing that targets should not be used as “hard numbers” for completing a transaction.

Targets are calculated in two ways:

  • A point gain (or loss) recorded in a previous trading range that is translated into a potential point gain (or loss) when support or resistance levels for the current trading range is broken.
  • The percentage gain (or loss) recorded in a previous trading range that is translated into the potential percentage gain (or loss) when support or resistance levels for the current trading range is broken.

Here is an example using an upside breakout above an established trading range:

The Philadelphia Semiconductor Index broke above confirmed resistance at 380.13. Previous trading range was 380.13 to 332.11.

· Upside technical target price based on the point gain method is 380.13-332.11= 48.02 + 380.13= 428.15

· Upside technical target based on the percentage gain method is 380.13/332.11×380.13= 435.09

The later method is preferred.

clip_image014[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Here is an example showing a downside breakdown below an established trading range:

Whole Foods broke below confirmed support at $29.81. Previous trading range was $29.81 and $36.03.

  • Downside risk based on the point loss method is $36.03-$29.81= $6.22. Downside technical target is $29.81-$6.22= $23.59
  • Downside technical target price based on the percentage loss method is $29.81/$36.03x$29.81= $24.66

clip_image015[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Pattern Recognition

Lots of strange names: Head and Shoulders, double tops, double bottoms, rising wedges, saucers, rounding tops, V formations and spikes! All are major reversal patterns. Other names include triangles, diamonds, flags, pennants, wedges and rectangles. All are continuation patterns.

All of these terms are jargon used by technical analysts. All of these patterns are based on three factors:

  • Support
  • Resistance
  • Trend

Naming the patterns is an interesting exercise (particularly when talking with another technical analyst), but is not really necessary when determining an entry or exit point on a chart.

Percent Retracements

When owning a trending investment, what size of a correction is reasonable before concerns about a change in trend are raised? Up-trending charts usually experience brief periods of weakness over time. Seasonal investors frequently will calculate their “tolerance” level where they will take protective measures when the investment weakens. Their tolerance level frequently is called “the box”. The seasonal investor will maintain the position unless the security drops out of the box. The box is established by calculating a retracement level based on the investment’s previous trading range. A retracement box is calculated on a percentage basis and usually is a range between 33% and 66%. (Investors focusing on a Fibinacci retracement will use 37.5% and 62.5%).

Here is an example. General Dynamics has been trending higher for an extended period of time. The trader wants to protect himself. He decides he will maintain the position during a short period of weakness as long as the stock remains above his “tolerance” level. The stock’s recent trading range has been between $69 and $81. Retracement “Box” for the stock is between $73 and $77. If the trader has a tight tolerance he may decide to place a stop loss order near the top of the box at $77. Another trader with a higher risk tolerance may be willing to place a stop loss order at the bottom of the box.at $73. Both traders are out of the trade if the stock moves below $73.

clip_image016[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Volume

Volume is a useful tool when stocks are breaking confirmed support and resistance levels. A spike in volume on break outs and break downs usually confirms their significance. Chances of follow through in the short term are higher. Break outs and breakdowns on volume, when significant news is released, are particularly relevant.

Cardinal Health is a good example. The company broke above a base building pattern on higher than average volume after reporting better than expected quarterly results.

clip_image017[7]

Chart courtesy of StockCharts.com www.stockcharts.com

On Balance Volume As A Price Predictor

On Balance Volume is an interesting indicator that frequently is useful for identifying stocks that are under accumulation for a possible take out. The method for calculating On Balance Volume is relatively simple. Volume is added when price of the stock moves higher and volume is subtracted when price of the stock moves lower. The reason for the phenomenon is a tendency for acquirers of large stock positions to “sit in the weeds” with a “bid” just below the market and to take out the “ask” price only when a sizeable block of stock is offered. Net result: the On Balance Volume indicator moves higher during a time when price of the stock remains relatively flat.

The On Balance Volume indicator is particularly useful when the indicator has moved to a new high just prior to a test of a key resistance level. The implication is that the acquirer may be ready to take the stock to the next higher price plateau.

The indicator is less useful today than it was 20 years ago. Equity activity related to listed options transactions has skewed the data for actively traded stocks and ETFs.

Denison Mines is an example of a stock with a positive On Balance Volume profile. Rumors of an eventual takeover of the company persist. On Balance Volume data indicates that the stock is under steady accumulation by a large buyer.

clip_image018[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Elliott Wave Theory

Interesting, but not high on the seasonal investor’s radar screen”! Most people find Elliott Wave analysis difficult to grasp and somewhat intimidating. The principles behind the theory are relatively simple. They focus on patterns, ratios and time. However, interpreting Elliott frequently is more of an art than a science. If you put four Elliotticians in a room with one chart, chances are that at least three interpretations will be offered. To be fair, some Elliotticians have shown considerable skill over the years. The best example is Bob Prechter, the ultimate guru of Elliott Wave. More information is available through Bob’s company, Elliott Wave International.

The Four Year Cycle

The four year stock market cycle usually is called the Four Year Presidential Cycle or the Four Year Economic Cycle. Historically, the four year cyclical low for the U.S. stock market has occurred within three months prior to the U.S. midterm election held during the second year after a president has been elected. On average, U.S. equity market advance thereafter for the next 22 months. The best period for performance by the S&P 500 Index during the four year cycle has been the nine month period following the four year low.

The series of recurring events trigger the four year low in the U.S. Presidential cycle:

  • The President uses his “political capital” to complete difficult items on his agenda during the first year of his mandate. His standings in the “popularity” polls diminish.
  • The opposition party in Congress starts to raise concerns about the President’s actions early in the second year of his mandate. Plans to gain more seats in Congress during the mid term elections are prepared.
  • Political rhetoric builds during late spring and summer. Congress is spending more time debating each other than considering legislation.
  • Rhetoric raises concerns about economic activity.
  • Growth in the U.S. economy starts to slow. Corporate revenues and profit margins come under pressure into the second and third quarters.
  • The mid-term election is held on the first Tuesday in November
  • The political agenda shifts, the president looks for ways to improve the economy prior to the end of his four year term, economic growth accelerates, corporate revenues and earnings improve and stock prices go higher.

Less well known is the tendency by all major developed nations to complete a four year economic cycle that corresponds to the U.S. Presidential Cycle. Four year economic cycles and their corresponding four stock market cycles also occur in Canada, the United Kingdom, developed European countries and Japan.

The four year stock market cycle has been exceptionally reliable for many decades. The U.S. stock market has recorded a four year low on 26 of the past 29 occasions since 1890. The only three occasions when the four year low was not identified just prior to the U.S. mid-term election were 1936, 1986 and 2006. On each occasion, the U.S. equity market continued to move higher without a correction of 5% or more. The miss in 1936 was followed by a substantial correction in 1937. The miss in 1986 was followed by a substantial correction in October 1987. The miss in 2006 was followed by a significant correction in late 2007/ early 2008.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

By definition, cialis 40mg seasonal investing includes:

  • A start date for an investment
  • An end date
  • Either price strength or weakness between the start and end dates for the chosen equity, sector, index or commodity.

A seasonality study preferably uses at least 10 years of data. Most of our studies use 10-20 years of data, however, data may not always be available for periods greater than 10 years in length. Studies using less than ten years of data can be used, but they tend to be less reliable. Results of shorter term studies have a higher chance of being skewed by a single data point.

Results using at least ten years of data tend to be stable for long periods of time, particularly when annual recurring fundamental reasons causing seasonality are unchanged. However, “statistical” slippage can occur. For example, the U.S. high tech sector has a period of seasonal strength from the end of September to a time between the end of December and the end January. On average, the sector peaks between start of the annual Las Vegas consumer electronics show in the second week in January and start of fourth quarter earnings reports near the end of January. Optimal time to own high tech securities for a seasonal trade based on month end statistical data over a 10 year period frequently flips back and forth from the end of December to the end of January. Seasonality studies on equity indices, sectors and commodities need to be re-examined once a year to see if slippage has occurred.

Time length for intermediate periods of seasonal strength or weakness ranges from five weeks to seven months. In addition, special short term periods often related to holidays have been identified. Examples include strength just before and after U.S. Thanksgiving and strength from just before Christmas until just after the New Year. Also, longer term “cyclical” periods lasting several years have been identified. Most notable is the four year economic or “presidential” cycle. Data for longer term cyclical periods frequently can be overlaid with annual data to refine seasonal entry and exit points.

Most periods of seasonal strength are NOT followed by a periods of seasonal weakness. In most cases, periods of seasonal strength are followed by a period of random performance. Markets moving from a period of seasonal strength to a period of seasonal weakness are rare.

Measuring Seasonality

Seasonality is measured in three ways:

  • Average return during the chosen period expressed as a percent
  • Reliability expressed by the number of profitable periods out of at least the past ten periods.
  • Performance relative to a major equity index such as the S&P 500 Index or the TSX Composite Index.

A seasonal investment by definition is profitable more than 50% of the time. If frequency of profitable trades is 50% and frequency of unprofitable trades is 50%, results are random. Confidence in a seasonal trade increases with the frequency of profitable trades. A confidence level for a seasonal trade exceeding is 70% is preferred. A confidence level of 80% frequently is available. A confidence level of 90% is relatively rare. A confidence level of 100% is extremely rare.

Primary Factors Influencing Seasonality

Seasonality happens because of a series of annual recurring events. The job of a seasonality analyst is to examine if the annual events are likely to recur prior to a period of seasonal strength. If annual recurring events are less likely to occur, the seasonality analyst will avoid recommending a seasonal trade.

The classic example is a series of recurring events that trigger the annual period of seasonal strength in the equity market. The S&P 500 Composite Index has an historic period of seasonal strength from the end of October to the beginning of May. The strategy is known as the “Buy when it snows, sell when it goes.”   Equity markets historically start to move higher near the end of October when the first snowfalls frequently appear. Equity markets tend to reach a seasonal peak around April when last of the snow melts away.  Equity markets in developed nations have a similar seasonal pattern.

Combining Seasonality with Technical and Fundamental Analysis

Using seasonality as a “stand alone” tool to make investment decisions is NOT recommended. Seasonality is a useful analytical tool, but only when used in conjunction with fundamental and technical analysis. Trades based on seasonality alone are profitable in say seven or eight times out of 10, but are unprofitable in two or three times out of ten.

The same can be said for strategies based on technical analysis. Reliable technical patterns such as head-and-shoulders patterns are accurate approximately 75% of the time. However, they are not accurate 25% of the time.

Trades based on fundamental analysis alone also are not recommended. Fundamental analyst picks may be profitable most of the time. However, results from a stock picking contest during 2006 run by a major Canadian newspaper showed that even the best fundamental analysts are far from perfect. The contest requested each participant to choose one stock to buy at the beginning of 2006 and to hold until the end of the year. Participants included a college student, a financial journalist and seven of Canada’s top fundamental analysts. You guessed it! The winner and only person to choose a stock that appreciated in 2006 was the college student.

Chances of a choosing a profitable seasonal trade are greatly enhanced if all three methods of analysis are combined. Of equal importance, chances of losing capital are greatly reduced.

Seasonality analysis is the bridge between fundamental and technical analysis:

  • Fundamental analysis tells us what to buy and sell
  • Technical analysis tells us when to buy and sell.
  • Seasonality analysis tells us what and when to buy and sell.

Identifying Seasonal Trades

Several methods are available to identify periods of seasonal strength:

  • Comments on seasonality made by fundamental analysts can be confirmed by completing a seasonality report based on data for 10 years or more. Fundamental analysts are notorious for commenting on seasonal trends based on 2-5 year data. Ten year studies will confirm or not confirm their comments. A few fundamental analysts on the Street are well aware of long term seasonal trends and base the timing of their recommendations at least partially on seasonality. They usually are analysts who have been in the financial service industry for 10 years or more.
  • Recurring spikes can be examined on monthly price charts using 10 or more years of data. Recurring spikes at the same time each year either on the upside or downside can suggest the possibility of a seasonal trend.
  • Companies and sectors can be examined when they have at least one quarter per year when revenues, earnings, cash flow and/or Earnings Before Interest, Depreciation and Amortization (EBITDA) are seasonally strong. Examples include retail merchandising and consumer electronic companies in the fourth quarter or airline companies in the summer. Seasonal strength in their share price normally begins just prior to their period of seasonal financial strength and ends just prior to the end of their seasonal period of financial strength.
  • Data for 10 years or more can be screened to identify equities and sectors showing periods of above average strength relative to their benchmark index. Preferred benchmarks are the S&P 500 Index for U.S. equities and sectors and the TSX Composite Index for Canadian equities and sectors.

Seasonality Myths

One of the greatest myths on the Street is that North American equity markets usually experience a “summer rally”. Traders frequently start talking in May about the possibility of a rally in the stock market in the June to August period. Talk by traders normally escalates during a period when North American equity markets are experiencing a short term correction. The message is “Don’t worry, be happy. The market will come back”. A long term study of the market confirms that a rally lasting three weeks or more inevitably happens during the three month summer period. However, traders fail to mention that the three week rally period has no consistency. Timing of the appearance of the three week rally is random and can appear at any time during the three month period. Of greater importance, traders fail to mention that virtually all three month periods during the year record at least one period of recovery lasting three weeks or more regardless of season.

Another myth is the expression “Sell in May and go away”. The myth originated from an actual period of seasonal strength in the base metal sector. Base metal prices as well as base metal equity prices tended to peak early in May and bottom near the end of September. The main reason was the annual operating shut down by base metal smelters in Europe in July and August for Europe’s extended holiday season. Demand by smelters for base metal concentrates slowed in May and recovered in September. Currently, base metal prices continue to show this seasonal pattern, but the pattern has been muted over the years. Market share of base metal smelter capacity in Europe has declined while market share in the Far East and South America has increased. Over the past decade, the “Sell in May and go away” phrase became adopted by the media, but with a slightly different twist. The phrase was transformed into expectation for weakness by broadly based North American equity indices such as the S&P 500 Index and the TSX Composite Index from the end of May to the end of September. The myth is not supported by fact. The S&P 500 Index and the TSX Composite Index has gained in five of the past ten periods from the end of May to the end of September. Unlike the period of seasonal strength by North American equity markets from the end of September to the end of April, performance in the May to September period is random. This period does not have a sufficient number of annual recurring events to influence equity markets.

Another myth is that the month of October is a weak and dangerous month for North American equity markets. The myth is based on the fact that substantial downdrafts in North American prices have occurred in the month of October. October 1929 and October 1987 are seared into the minds of traders. However, data during the past ten years suggests that fears of weakness in October no longer are founded. The S&P 500 Index has advanced in five of the past 10 periods and the TSX Composite Index has gained in seven of the past 10 periods. On the contrary! October frequently is the month of the year when important seasonal lows frequently are reached.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

Seasonality refers to particular time frames when stocks/sectors/indices are subjected to and influenced by recurring tendencies that produce patterns that are apparent in the investment valuation.   Tendencies can range from weather events (temperature in winter vs. summer, sickness probability of inclement conditions, apoplectic etc.) to calendar events (quarterly reporting expectations, announcements, etc.).   The key is that the tendency is recurring and provides a sustainable probability of performing in a manner consistent to previous results.

Identified below are the periods of seasonal strength for each market segment, as identified by Brooke Thackray.   Each bar will indicate a buy and sell date based upon the optimal holding period for each market sector/index.

 

 

A seasonality study preferably uses at least 10 years of data. Most of our studies use 10-20 years of data, however, data may not always be available for periods greater than 10 years in length.   Studies using less than ten years of data can be used, but they tend to be less reliable. Results of shorter term studies have a higher chance of being skewed by a single data point.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

Why use technical analysis in conjunction with seasonal investing? Seasonality analysis is a useful tool when looking at a general time to enter and exit equity markets and sectors. However, stuff seasonality analysis is not precise. It only gives an approximate time when trades can be made. Equity markets and sectors rarely reach important lows and highs on the dates identified by seasonality studies. The solution is to use technical analysis to optimize seasonal entry and exit points. Normally, order technical analysis will provide optimal entry and exit points within one month (plus or minus) of an identified period of seasonal strength. Net result: investment performance usually is enhanced significantly.

Using Short Term Momentum Indicators To Optimize Seasonal Entry and Exit Points

Several well known momentum indicators are preferred for optimizing seasonal entry and exit points. They can be used separately or jointly. Choice of indicators is determined by experience and comfort of the investor. Short term momentum indicators based on daily data are preferred when seeking entry and exit points for seasonal strategies. Indicators using weekly data are useful as a supplement to indictors using daily data, medstore but, by definition tend to be less precise for entry and exit.

Three momentum indicators are preferred:

  • Moving Average Convergence Divergence (MACD)
  • Relative Strength Index (RSI)
  • Stochastics

All use moving averages in one form or another when calculated. By definition, all will provide entry and exit signals shortly after a short term low or high has been reached.

MACD is the best known and most widely used momentum indicator. Entry and exit points are determined by a cross over of two moving averages. A buy signal is given when the indicator is oversold (i.e. below -1.0) and a positive cross over occurs. Please refer to the enclosed chart for demonstration of a buy signal. Conversely, a sell signal occurs when the indicator is overbought (i.e. above 1.0) and a negative cross over occurs.

MACD buy and sell signals are more relevant when divergence between the indicator and price of the security occurs on an intermediate basis. The enclosed chart gives a trend line showing divergence between the MACD indicator and the price of crude oil.

MACD is the slowest and latest of the three momentum indicators. RSI and Stochastics are faster, but are more prone to false signals.

RSI is slightly faster. When the indicator declines to 30% or lower, the security is oversold. The investor looks for a recovery above 30% for a recovery entry point. Conversely, when the indicator is above 70%, the security is overbought. The investor looks for weakness below 70% for confirmation of an exit point.

clip_image001[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Stochastics is the fastest momentum indicator. A drop below 20% indicates that the security is oversold in the short term. A recovery above 20% indicates a short term entry point. Conversely, a move above 80% indicates that the security is overbought in the short term. Weakness below 80% indicates a short term exit point.

Bullish Percent Index

Bullish Percent Index is a useful indicator when used in conjunction with short term momentum indicators. Its strength is its unique method of calculation. Data for Bullish Percent Index does not include moving averages applied by other indicators.

The root of the Bullish Percent Index is Point and Figure charts showing the trend of a security. A chart with a “bullish” trend has a current column of “x”s moving higher than the previous column of “x”s. Following is an example:

clip_image003[7]

IBM is one stock out of 500 stocks in the S&P 500 Index that is considered to have an uptrend or “bullish” trend based on point and figure analysis. StockCharts.com adds up the total number of stocks in the 500 that have an uptrend and publishes the data as a Bullish Percent Index for the S&P 500 Index. Bullish Percent Index for the S&P 500 is updated daily and published at www.stockcharts.com at $BPSPX.

Bullish Percent Indices are available for well known broadly based equity indices and U.S. sectors including the S&P 500 Index, The S&P 100 Index, the Dow Jones Industrial Average, the NASDAQ Composite Index, the NYSE Index, the NASDAQ 100 Index, the Dow Jones Transportation Average, the Dow Jones Utilities Average, the TSX Composite Index and the ten S&P sector indices.

Bullish Percent Index works best for an index with a large number of holdings. For example, it works better for the 500 S&P 500 Index stocks than for the 30 Dow Jones Industrial Average stocks. The Bullish Percent Index based on a small number of securities tends to be more volatile (i.e. choppy) and prone to false signals.

A 15 day moving average has been proven through experience to be a reliable “cross over” measure to confirm a change in trend on Bullish Percent Index charts.

Like any indicator, Bullish Percent Index is not perfect. However, when used in conjunction with momentum indicator and seasonality, it eliminates much of the “noise” that occurs during an intermediate cycle. It also can be used in conjunction with momentum indicators only (i.e. excluding seasonal influences) to identify additional intermediate trading opportunities. Following is a Bullish Percent Index on the TSX Composite Index showing entry and exit points that combine Seasonality, MACD and the Bullish Percent Index. Arrows indicate entry and exit points using seasonality (i.e. Buy when it snows, sell when it goes” from the end of September to the end of April). Zeros represent other entry and exit points based on MACD and Bullish Percent Index only:

clip_image004[7]

Charts courtesy of StockCharts.com www.stockcharts.com

clip_image005[7]

Chart courtesy of StockCharts.com www.stockcharts.com

 

Other Useful Technical Indicators

Trend Lines

Trend lines are useful for confirming the direction that a chart is moving. They can provide early warning signs when direction is changing. However, they should not be used a “stand alone” buy or sell technical signal.

By definition, a trend line needs three or more points to connect. For an uptrend, the three or more points are located below indicated prices. For a downtrend, the three points are more are located above indicated prices. Confirmed support and resistance levels often are useful for establishing trend lines. Following are examples.

clip_image012[7]

Chart courtesy of StockCharts.com www.stockcharts.com

clip_image013[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Moving Averages

Moving averages can be considered as another form of trend line. They indicate a chart’s direction, but with more flexibility.

The moving average most frequently used for longer term direction is the 200 day or 40 week moving average. Both averages are virtually the same. The 200 day moving average frequently acts as a support or resistance level.

The 200 day moving average also is an attractive indictor for measuring risk and potential return. Assuming charts eventually revert to a neutral level determined by the 200 day moving average, the percent gain above or below the 200 day moving average can indicate amount of risk/potential return.

The second moving average frequently used for medium term direction is the 50 day moving average. A break above the 50 day moving average is an “alert” signal to explore a possible buying opportunity. Conversely, a break below the 50 day moving average is an alert signal to explore a possible selling opportunity.

Target Prices

Target prices are interesting, but not very useful. They frequently are provided by technical analysts as a guideline for potential return from an investment, fully realizing that targets should not be used as “hard numbers” for completing a transaction.

Targets are calculated in two ways:

  • A point gain (or loss) recorded in a previous trading range that is translated into a potential point gain (or loss) when support or resistance levels for the current trading range is broken.
  • The percentage gain (or loss) recorded in a previous trading range that is translated into the potential percentage gain (or loss) when support or resistance levels for the current trading range is broken.

Here is an example using an upside breakout above an established trading range:

The Philadelphia Semiconductor Index broke above confirmed resistance at 380.13. Previous trading range was 380.13 to 332.11.

· Upside technical target price based on the point gain method is 380.13-332.11= 48.02 + 380.13= 428.15

· Upside technical target based on the percentage gain method is 380.13/332.11×380.13= 435.09

The later method is preferred.

clip_image014[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Here is an example showing a downside breakdown below an established trading range:

Whole Foods broke below confirmed support at $29.81. Previous trading range was $29.81 and $36.03.

  • Downside risk based on the point loss method is $36.03-$29.81= $6.22. Downside technical target is $29.81-$6.22= $23.59
  • Downside technical target price based on the percentage loss method is $29.81/$36.03x$29.81= $24.66

clip_image015[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Pattern Recognition

Lots of strange names: Head and Shoulders, double tops, double bottoms, rising wedges, saucers, rounding tops, V formations and spikes! All are major reversal patterns. Other names include triangles, diamonds, flags, pennants, wedges and rectangles. All are continuation patterns.

All of these terms are jargon used by technical analysts. All of these patterns are based on three factors:

  • Support
  • Resistance
  • Trend

Naming the patterns is an interesting exercise (particularly when talking with another technical analyst), but is not really necessary when determining an entry or exit point on a chart.

Percent Retracements

When owning a trending investment, what size of a correction is reasonable before concerns about a change in trend are raised? Up-trending charts usually experience brief periods of weakness over time. Seasonal investors frequently will calculate their “tolerance” level where they will take protective measures when the investment weakens. Their tolerance level frequently is called “the box”. The seasonal investor will maintain the position unless the security drops out of the box. The box is established by calculating a retracement level based on the investment’s previous trading range. A retracement box is calculated on a percentage basis and usually is a range between 33% and 66%. (Investors focusing on a Fibinacci retracement will use 37.5% and 62.5%).

Here is an example. General Dynamics has been trending higher for an extended period of time. The trader wants to protect himself. He decides he will maintain the position during a short period of weakness as long as the stock remains above his “tolerance” level. The stock’s recent trading range has been between $69 and $81. Retracement “Box” for the stock is between $73 and $77. If the trader has a tight tolerance he may decide to place a stop loss order near the top of the box at $77. Another trader with a higher risk tolerance may be willing to place a stop loss order at the bottom of the box.at $73. Both traders are out of the trade if the stock moves below $73.

clip_image016[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Volume

Volume is a useful tool when stocks are breaking confirmed support and resistance levels. A spike in volume on break outs and break downs usually confirms their significance. Chances of follow through in the short term are higher. Break outs and breakdowns on volume, when significant news is released, are particularly relevant.

Cardinal Health is a good example. The company broke above a base building pattern on higher than average volume after reporting better than expected quarterly results.

clip_image017[7]

Chart courtesy of StockCharts.com www.stockcharts.com

On Balance Volume As A Price Predictor

On Balance Volume is an interesting indicator that frequently is useful for identifying stocks that are under accumulation for a possible take out. The method for calculating On Balance Volume is relatively simple. Volume is added when price of the stock moves higher and volume is subtracted when price of the stock moves lower. The reason for the phenomenon is a tendency for acquirers of large stock positions to “sit in the weeds” with a “bid” just below the market and to take out the “ask” price only when a sizeable block of stock is offered. Net result: the On Balance Volume indicator moves higher during a time when price of the stock remains relatively flat.

The On Balance Volume indicator is particularly useful when the indicator has moved to a new high just prior to a test of a key resistance level. The implication is that the acquirer may be ready to take the stock to the next higher price plateau.

The indicator is less useful today than it was 20 years ago. Equity activity related to listed options transactions has skewed the data for actively traded stocks and ETFs.

Denison Mines is an example of a stock with a positive On Balance Volume profile. Rumors of an eventual takeover of the company persist. On Balance Volume data indicates that the stock is under steady accumulation by a large buyer.

clip_image018[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Elliott Wave Theory

Interesting, but not high on the seasonal investor’s radar screen”! Most people find Elliott Wave analysis difficult to grasp and somewhat intimidating. The principles behind the theory are relatively simple. They focus on patterns, ratios and time. However, interpreting Elliott frequently is more of an art than a science. If you put four Elliotticians in a room with one chart, chances are that at least three interpretations will be offered. To be fair, some Elliotticians have shown considerable skill over the years. The best example is Bob Prechter, the ultimate guru of Elliott Wave. More information is available through Bob’s company, Elliott Wave International.

The Four Year Cycle

The four year stock market cycle usually is called the Four Year Presidential Cycle or the Four Year Economic Cycle. Historically, the four year cyclical low for the U.S. stock market has occurred within three months prior to the U.S. midterm election held during the second year after a president has been elected. On average, U.S. equity market advance thereafter for the next 22 months. The best period for performance by the S&P 500 Index during the four year cycle has been the nine month period following the four year low.

The series of recurring events trigger the four year low in the U.S. Presidential cycle:

  • The President uses his “political capital” to complete difficult items on his agenda during the first year of his mandate. His standings in the “popularity” polls diminish.
  • The opposition party in Congress starts to raise concerns about the President’s actions early in the second year of his mandate. Plans to gain more seats in Congress during the mid term elections are prepared.
  • Political rhetoric builds during late spring and summer. Congress is spending more time debating each other than considering legislation.
  • Rhetoric raises concerns about economic activity.
  • Growth in the U.S. economy starts to slow. Corporate revenues and profit margins come under pressure into the second and third quarters.
  • The mid-term election is held on the first Tuesday in November
  • The political agenda shifts, the president looks for ways to improve the economy prior to the end of his four year term, economic growth accelerates, corporate revenues and earnings improve and stock prices go higher.

Less well known is the tendency by all major developed nations to complete a four year economic cycle that corresponds to the U.S. Presidential Cycle. Four year economic cycles and their corresponding four stock market cycles also occur in Canada, the United Kingdom, developed European countries and Japan.

The four year stock market cycle has been exceptionally reliable for many decades. The U.S. stock market has recorded a four year low on 26 of the past 29 occasions since 1890. The only three occasions when the four year low was not identified just prior to the U.S. mid-term election were 1936, 1986 and 2006. On each occasion, the U.S. equity market continued to move higher without a correction of 5% or more. The miss in 1936 was followed by a substantial correction in 1937. The miss in 1986 was followed by a substantial correction in October 1987. The miss in 2006 was followed by a significant correction in late 2007/ early 2008.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

Seasonality refers to particular time frames when stocks/sectors/indices are subjected to and influenced by recurring tendencies that produce patterns that are apparent in the investment valuation.   Tendencies can range from weather events (temperature in winter vs. summer, here probability of inclement conditions, etc.) to calendar events (quarterly reporting expectations, announcements, etc.).   The key is that the tendency is recurring and provides a sustainable probability of performing in a manner consistent to previous results.

Identified below are the periods of seasonal strength for each market segment, as identified by Brooke Thackray.   Each bar will indicate a buy and sell date based upon the optimal holding period for each market sector/index.

 

 

A seasonality study preferably uses at least 10 years of data. Most of our studies use 10-20 years of data, however, data may not always be available for periods greater than 10 years in length.   Studies using less than ten years of data can be used, but they tend to be less reliable. Results of shorter term studies have a higher chance of being skewed by a single data point.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

Why use technical analysis in conjunction with seasonal investing? Seasonality analysis is a useful tool when looking at a general time to enter and exit equity markets and sectors. However, viagra 40mg seasonality analysis is not precise. It only gives an approximate time when trades can be made. Equity markets and sectors rarely reach important lows and highs on the dates identified by seasonality studies. The solution is to use technical analysis to optimize seasonal entry and exit points. Normally, technical analysis will provide optimal entry and exit points within one month (plus or minus) of an identified period of seasonal strength. Net result: investment performance usually is enhanced significantly.

Using Short Term Momentum Indicators To Optimize Seasonal Entry and Exit Points

Several well known momentum indicators are preferred for optimizing seasonal entry and exit points. They can be used separately or jointly. Choice of indicators is determined by experience and comfort of the investor. Short term momentum indicators based on daily data are preferred when seeking entry and exit points for seasonal strategies. Indicators using weekly data are useful as a supplement to indictors using daily data, but, by definition tend to be less precise for entry and exit.

Three momentum indicators are preferred:

  • Moving Average Convergence Divergence (MACD)
  • Relative Strength Index (RSI)
  • Stochastics

All use moving averages in one form or another when calculated. By definition, all will provide entry and exit signals shortly after a short term low or high has been reached.

MACD is the best known and most widely used momentum indicator. Entry and exit points are determined by a cross over of two moving averages. A buy signal is given when the indicator is oversold (i.e. below -1.0) and a positive cross over occurs. Please refer to the enclosed chart for demonstration of a buy signal. Conversely, a sell signal occurs when the indicator is overbought (i.e. above 1.0) and a negative cross over occurs.

MACD buy and sell signals are more relevant when divergence between the indicator and price of the security occurs on an intermediate basis. The enclosed chart gives a trend line showing divergence between the MACD indicator and the price of crude oil.

MACD is the slowest and latest of the three momentum indicators. RSI and Stochastics are faster, but are more prone to false signals.

RSI is slightly faster. When the indicator declines to 30% or lower, the security is oversold. The investor looks for a recovery above 30% for a recovery entry point. Conversely, when the indicator is above 70%, the security is overbought. The investor looks for weakness below 70% for confirmation of an exit point.

clip_image001[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Stochastics is the fastest momentum indicator. A drop below 20% indicates that the security is oversold in the short term. A recovery above 20% indicates a short term entry point. Conversely, a move above 80% indicates that the security is overbought in the short term. Weakness below 80% indicates a short term exit point.

Bullish Percent Index

Bullish Percent Index is a useful indicator when used in conjunction with short term momentum indicators. Its strength is its unique method of calculation. Data for Bullish Percent Index does not include moving averages applied by other indicators.

The root of the Bullish Percent Index is Point and Figure charts showing the trend of a security. A chart with a “bullish” trend has a current column of “x”s moving higher than the previous column of “x”s. Following is an example:

clip_image003[7]

IBM is one stock out of 500 stocks in the S&P 500 Index that is considered to have an uptrend or “bullish” trend based on point and figure analysis. StockCharts.com adds up the total number of stocks in the 500 that have an uptrend and publishes the data as a Bullish Percent Index for the S&P 500 Index. Bullish Percent Index for the S&P 500 is updated daily and published at www.stockcharts.com at $BPSPX.

Bullish Percent Indices are available for well known broadly based equity indices and U.S. sectors including the S&P 500 Index, The S&P 100 Index, the Dow Jones Industrial Average, the NASDAQ Composite Index, the NYSE Index, the NASDAQ 100 Index, the Dow Jones Transportation Average, the Dow Jones Utilities Average, the TSX Composite Index and the ten S&P sector indices.

Bullish Percent Index works best for an index with a large number of holdings. For example, it works better for the 500 S&P 500 Index stocks than for the 30 Dow Jones Industrial Average stocks. The Bullish Percent Index based on a small number of securities tends to be more volatile (i.e. choppy) and prone to false signals.

A 15 day moving average has been proven through experience to be a reliable “cross over” measure to confirm a change in trend on Bullish Percent Index charts.

Like any indicator, Bullish Percent Index is not perfect. However, when used in conjunction with momentum indicator and seasonality, it eliminates much of the “noise” that occurs during an intermediate cycle. It also can be used in conjunction with momentum indicators only (i.e. excluding seasonal influences) to identify additional intermediate trading opportunities. Following is a Bullish Percent Index on the TSX Composite Index showing entry and exit points that combine Seasonality, MACD and the Bullish Percent Index. Arrows indicate entry and exit points using seasonality (i.e. Buy when it snows, sell when it goes” from the end of September to the end of April). Zeros represent other entry and exit points based on MACD and Bullish Percent Index only:

clip_image004[7]

Charts courtesy of StockCharts.com www.stockcharts.com

clip_image005[7]

Chart courtesy of StockCharts.com www.stockcharts.com

 

Other Useful Technical Indicators

Trend Lines

Trend lines are useful for confirming the direction that a chart is moving. They can provide early warning signs when direction is changing. However, they should not be used a “stand alone” buy or sell technical signal.

By definition, a trend line needs three or more points to connect. For an uptrend, the three or more points are located below indicated prices. For a downtrend, the three points are more are located above indicated prices. Confirmed support and resistance levels often are useful for establishing trend lines. Following are examples.

clip_image012[7]

Chart courtesy of StockCharts.com www.stockcharts.com

clip_image013[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Moving Averages

Moving averages can be considered as another form of trend line. They indicate a chart’s direction, but with more flexibility.

The moving average most frequently used for longer term direction is the 200 day or 40 week moving average. Both averages are virtually the same. The 200 day moving average frequently acts as a support or resistance level.

The 200 day moving average also is an attractive indictor for measuring risk and potential return. Assuming charts eventually revert to a neutral level determined by the 200 day moving average, the percent gain above or below the 200 day moving average can indicate amount of risk/potential return.

The second moving average frequently used for medium term direction is the 50 day moving average. A break above the 50 day moving average is an “alert” signal to explore a possible buying opportunity. Conversely, a break below the 50 day moving average is an alert signal to explore a possible selling opportunity.

Target Prices

Target prices are interesting, but not very useful. They frequently are provided by technical analysts as a guideline for potential return from an investment, fully realizing that targets should not be used as “hard numbers” for completing a transaction.

Targets are calculated in two ways:

  • A point gain (or loss) recorded in a previous trading range that is translated into a potential point gain (or loss) when support or resistance levels for the current trading range is broken.
  • The percentage gain (or loss) recorded in a previous trading range that is translated into the potential percentage gain (or loss) when support or resistance levels for the current trading range is broken.

Here is an example using an upside breakout above an established trading range:

The Philadelphia Semiconductor Index broke above confirmed resistance at 380.13. Previous trading range was 380.13 to 332.11.

· Upside technical target price based on the point gain method is 380.13-332.11= 48.02 + 380.13= 428.15

· Upside technical target based on the percentage gain method is 380.13/332.11×380.13= 435.09

The later method is preferred.

clip_image014[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Here is an example showing a downside breakdown below an established trading range:

Whole Foods broke below confirmed support at $29.81. Previous trading range was $29.81 and $36.03.

  • Downside risk based on the point loss method is $36.03-$29.81= $6.22. Downside technical target is $29.81-$6.22= $23.59
  • Downside technical target price based on the percentage loss method is $29.81/$36.03x$29.81= $24.66

clip_image015[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Pattern Recognition

Lots of strange names: Head and Shoulders, double tops, double bottoms, rising wedges, saucers, rounding tops, V formations and spikes! All are major reversal patterns. Other names include triangles, diamonds, flags, pennants, wedges and rectangles. All are continuation patterns.

All of these terms are jargon used by technical analysts. All of these patterns are based on three factors:

  • Support
  • Resistance
  • Trend

Naming the patterns is an interesting exercise (particularly when talking with another technical analyst), but is not really necessary when determining an entry or exit point on a chart.

Percent Retracements

When owning a trending investment, what size of a correction is reasonable before concerns about a change in trend are raised? Up-trending charts usually experience brief periods of weakness over time. Seasonal investors frequently will calculate their “tolerance” level where they will take protective measures when the investment weakens. Their tolerance level frequently is called “the box”. The seasonal investor will maintain the position unless the security drops out of the box. The box is established by calculating a retracement level based on the investment’s previous trading range. A retracement box is calculated on a percentage basis and usually is a range between 33% and 66%. (Investors focusing on a Fibinacci retracement will use 37.5% and 62.5%).

Here is an example. General Dynamics has been trending higher for an extended period of time. The trader wants to protect himself. He decides he will maintain the position during a short period of weakness as long as the stock remains above his “tolerance” level. The stock’s recent trading range has been between $69 and $81. Retracement “Box” for the stock is between $73 and $77. If the trader has a tight tolerance he may decide to place a stop loss order near the top of the box at $77. Another trader with a higher risk tolerance may be willing to place a stop loss order at the bottom of the box.at $73. Both traders are out of the trade if the stock moves below $73.

clip_image016[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Volume

Volume is a useful tool when stocks are breaking confirmed support and resistance levels. A spike in volume on break outs and break downs usually confirms their significance. Chances of follow through in the short term are higher. Break outs and breakdowns on volume, when significant news is released, are particularly relevant.

Cardinal Health is a good example. The company broke above a base building pattern on higher than average volume after reporting better than expected quarterly results.

clip_image017[7]

Chart courtesy of StockCharts.com www.stockcharts.com

On Balance Volume As A Price Predictor

On Balance Volume is an interesting indicator that frequently is useful for identifying stocks that are under accumulation for a possible take out. The method for calculating On Balance Volume is relatively simple. Volume is added when price of the stock moves higher and volume is subtracted when price of the stock moves lower. The reason for the phenomenon is a tendency for acquirers of large stock positions to “sit in the weeds” with a “bid” just below the market and to take out the “ask” price only when a sizeable block of stock is offered. Net result: the On Balance Volume indicator moves higher during a time when price of the stock remains relatively flat.

The On Balance Volume indicator is particularly useful when the indicator has moved to a new high just prior to a test of a key resistance level. The implication is that the acquirer may be ready to take the stock to the next higher price plateau.

The indicator is less useful today than it was 20 years ago. Equity activity related to listed options transactions has skewed the data for actively traded stocks and ETFs.

Denison Mines is an example of a stock with a positive On Balance Volume profile. Rumors of an eventual takeover of the company persist. On Balance Volume data indicates that the stock is under steady accumulation by a large buyer.

clip_image018[7]

Chart courtesy of StockCharts.com www.stockcharts.com

Elliott Wave Theory

Interesting, but not high on the seasonal investor’s radar screen”! Most people find Elliott Wave analysis difficult to grasp and somewhat intimidating. The principles behind the theory are relatively simple. They focus on patterns, ratios and time. However, interpreting Elliott frequently is more of an art than a science. If you put four Elliotticians in a room with one chart, chances are that at least three interpretations will be offered. To be fair, some Elliotticians have shown considerable skill over the years. The best example is Bob Prechter, the ultimate guru of Elliott Wave. More information is available through Bob’s company, Elliott Wave International.

The Four Year Cycle

The four year stock market cycle usually is called the Four Year Presidential Cycle or the Four Year Economic Cycle. Historically, the four year cyclical low for the U.S. stock market has occurred within three months prior to the U.S. midterm election held during the second year after a president has been elected. On average, U.S. equity market advance thereafter for the next 22 months. The best period for performance by the S&P 500 Index during the four year cycle has been the nine month period following the four year low.

The series of recurring events trigger the four year low in the U.S. Presidential cycle:

  • The President uses his “political capital” to complete difficult items on his agenda during the first year of his mandate. His standings in the “popularity” polls diminish.
  • The opposition party in Congress starts to raise concerns about the President’s actions early in the second year of his mandate. Plans to gain more seats in Congress during the mid term elections are prepared.
  • Political rhetoric builds during late spring and summer. Congress is spending more time debating each other than considering legislation.
  • Rhetoric raises concerns about economic activity.
  • Growth in the U.S. economy starts to slow. Corporate revenues and profit margins come under pressure into the second and third quarters.
  • The mid-term election is held on the first Tuesday in November
  • The political agenda shifts, the president looks for ways to improve the economy prior to the end of his four year term, economic growth accelerates, corporate revenues and earnings improve and stock prices go higher.

Less well known is the tendency by all major developed nations to complete a four year economic cycle that corresponds to the U.S. Presidential Cycle. Four year economic cycles and their corresponding four stock market cycles also occur in Canada, the United Kingdom, developed European countries and Japan.

The four year stock market cycle has been exceptionally reliable for many decades. The U.S. stock market has recorded a four year low on 26 of the past 29 occasions since 1890. The only three occasions when the four year low was not identified just prior to the U.S. mid-term election were 1936, 1986 and 2006. On each occasion, the U.S. equity market continued to move higher without a correction of 5% or more. The miss in 1936 was followed by a substantial correction in 1937. The miss in 1986 was followed by a substantial correction in October 1987. The miss in 2006 was followed by a significant correction in late 2007/ early 2008.

 

Seasonality  |  Seasonal Investing  |  Combining Seasonal Investing With Technical Analysis

 

By definition, healthful seasonal investing includes:

  • A start date for an investment
  • An end date
  • Either price strength or weakness between the start and end dates for the chosen equity, sector, index or commodity.

A seasonality study preferably uses at least 10 years of data. Most of our studies use 10-20 years of data, however, data may not always be available for periods greater than 10 years in length. Studies using less than ten years of data can be used, but they tend to be less reliable. Results of shorter term studies have a higher chance of being skewed by a single data point.

Results using at least ten years of data tend to be stable for long periods of time, particularly when annual recurring fundamental reasons causing seasonality are unchanged. However, “statistical” slippage can occur. For example, the U.S. high tech sector has a period of seasonal strength from the end of September to a time between the end of December and the end January. On average, the sector peaks between start of the annual Las Vegas consumer electronics show in the second week in January and start of fourth quarter earnings reports near the end of January. Optimal time to own high tech securities for a seasonal trade based on month end statistical data over a 10 year period frequently flips back and forth from the end of December to the end of January. Seasonality studies on equity indices, sectors and commodities need to be re-examined once a year to see if slippage has occurred.

Time length for intermediate periods of seasonal strength or weakness ranges from five weeks to seven months. In addition, special short term periods often related to holidays have been identified. Examples include strength just before and after U.S. Thanksgiving and strength from just before Christmas until just after the New Year. Also, longer term “cyclical” periods lasting several years have been identified. Most notable is the four year economic or “presidential” cycle. Data for longer term cyclical periods frequently can be overlaid with annual data to refine seasonal entry and exit points.

Most periods of seasonal strength are NOT followed by a periods of seasonal weakness. In most cases, periods of seasonal strength are followed by a period of random performance. Markets moving from a period of seasonal strength to a period of seasonal weakness are rare.

Measuring Seasonality

Seasonality is measured in three ways:

  • Average return during the chosen period expressed as a percent
  • Reliability expressed by the number of profitable periods out of at least the past ten periods.
  • Performance relative to a major equity index such as the S&P 500 Index or the TSX Composite Index.

A seasonal investment by definition is profitable more than 50% of the time. If frequency of profitable trades is 50% and frequency of unprofitable trades is 50%, results are random. Confidence in a seasonal trade increases with the frequency of profitable trades. A confidence level for a seasonal trade exceeding is 70% is preferred. A confidence level of 80% frequently is available. A confidence level of 90% is relatively rare. A confidence level of 100% is extremely rare.

Primary Factors Influencing Seasonality

Seasonality happens because of a series of annual recurring events. The job of a seasonality analyst is to examine if the annual events are likely to recur prior to a period of seasonal strength. If annual recurring events are less likely to occur, the seasonality analyst will avoid recommending a seasonal trade.

The classic example is a series of recurring events that trigger the annual period of seasonal strength in the equity market. The S&P 500 Composite Index has an historic period of seasonal strength from the end of October to the beginning of May. The strategy is known as the “Buy when it snows, sell when it goes.”   Equity markets historically start to move higher near the end of October when the first snowfalls frequently appear. Equity markets tend to reach a seasonal peak around April when last of the snow melts away.  Equity markets in developed nations have a similar seasonal pattern.

Combining Seasonality with Technical and Fundamental Analysis

Using seasonality as a “stand alone” tool to make investment decisions is NOT recommended. Seasonality is a useful analytical tool, but only when used in conjunction with fundamental and technical analysis. Trades based on seasonality alone are profitable in say seven or eight times out of 10, but are unprofitable in two or three times out of ten.

The same can be said for strategies based on technical analysis. Reliable technical patterns such as head-and-shoulders patterns are accurate approximately 75% of the time. However, they are not accurate 25% of the time.

Trades based on fundamental analysis alone also are not recommended. Fundamental analyst picks may be profitable most of the time. However, results from a stock picking contest during 2006 run by a major Canadian newspaper showed that even the best fundamental analysts are far from perfect. The contest requested each participant to choose one stock to buy at the beginning of 2006 and to hold until the end of the year. Participants included a college student, a financial journalist and seven of Canada’s top fundamental analysts. You guessed it! The winner and only person to choose a stock that appreciated in 2006 was the college student.

Chances of a choosing a profitable seasonal trade are greatly enhanced if all three methods of analysis are combined. Of equal importance, chances of losing capital are greatly reduced.

Seasonality analysis is the bridge between fundamental and technical analysis:

  • Fundamental analysis tells us what to buy and sell
  • Technical analysis tells us when to buy and sell.
  • Seasonality analysis tells us what and when to buy and sell.

Identifying Seasonal Trades

Several methods are available to identify periods of seasonal strength:

  • Comments on seasonality made by fundamental analysts can be confirmed by completing a seasonality report based on data for 10 years or more. Fundamental analysts are notorious for commenting on seasonal trends based on 2-5 year data. Ten year studies will confirm or not confirm their comments. A few fundamental analysts on the Street are well aware of long term seasonal trends and base the timing of their recommendations at least partially on seasonality. They usually are analysts who have been in the financial service industry for 10 years or more.
  • Recurring spikes can be examined on monthly price charts using 10 or more years of data. Recurring spikes at the same time each year either on the upside or downside can suggest the possibility of a seasonal trend.
  • Companies and sectors can be examined when they have at least one quarter per year when revenues, earnings, cash flow and/or Earnings Before Interest, Depreciation and Amortization (EBITDA) are seasonally strong. Examples include retail merchandising and consumer electronic companies in the fourth quarter or airline companies in the summer. Seasonal strength in their share price normally begins just prior to their period of seasonal financial strength and ends just prior to the end of their seasonal period of financial strength.
  • Data for 10 years or more can be screened to identify equities and sectors showing periods of above average strength relative to their benchmark index. Preferred benchmarks are the S&P 500 Index for U.S. equities and sectors and the TSX Composite Index for Canadian equities and sectors.

Seasonality Myths

One of the greatest myths on the Street is that North American equity markets usually experience a “summer rally”. Traders frequently start talking in May about the possibility of a rally in the stock market in the June to August period. Talk by traders normally escalates during a period when North American equity markets are experiencing a short term correction. The message is “Don’t worry, be happy. The market will come back”. A long term study of the market confirms that a rally lasting three weeks or more inevitably happens during the three month summer period. However, traders fail to mention that the three week rally period has no consistency. Timing of the appearance of the three week rally is random and can appear at any time during the three month period. Of greater importance, traders fail to mention that virtually all three month periods during the year record at least one period of recovery lasting three weeks or more regardless of season.

Another myth is the expression “Sell in May and go away”. The myth originated from an actual period of seasonal strength in the base metal sector. Base metal prices as well as base metal equity prices tended to peak early in May and bottom near the end of September. The main reason was the annual operating shut down by base metal smelters in Europe in July and August for Europe’s extended holiday season. Demand by smelters for base metal concentrates slowed in May and recovered in September. Currently, base metal prices continue to show this seasonal pattern, but the pattern has been muted over the years. Market share of base metal smelter capacity in Europe has declined while market share in the Far East and South America has increased. Over the past decade, the “Sell in May and go away” phrase became adopted by the media, but with a slightly different twist. The phrase was transformed into expectation for weakness by broadly based North American equity indices such as the S&P 500 Index and the TSX Composite Index from the end of May to the end of September. The myth is not supported by fact. The S&P 500 Index and the TSX Composite Index has gained in five of the past ten periods from the end of May to the end of September. Unlike the period of seasonal strength by North American equity markets from the end of September to the end of April, performance in the May to September period is random. This period does not have a sufficient number of annual recurring events to influence equity markets.

Another myth is that the month of October is a weak and dangerous month for North American equity markets. The myth is based on the fact that substantial downdrafts in North American prices have occurred in the month of October. October 1929 and October 1987 are seared into the minds of traders. However, data during the past ten years suggests that fears of weakness in October no longer are founded. The S&P 500 Index has advanced in five of the past 10 periods and the TSX Composite Index has gained in seven of the past 10 periods. On the contrary! October frequently is the month of the year when important seasonal lows frequently are reached.

The equity reports published on EquityClock.com are designed to provide an overall perspective of technical, stomatology seasonal, infertility fundamental and situational influences on particular stocks trading on the open market.

Below are some details and explanations of some of the items that you will find in the equity reports.

Commentary

  • Contains comments form the author that may be relevant at the time the report is created

Seasonal Chart

  • Analysis pegged at a specified date that details graphically the seasonal tendencies that occur throughout the calendar year using data from the past 20 years (if available).  Many charts are pegged at the most recent market close, providing a real-time perspective of the tendencies affecting a stock assuming you had invested today.

Seasonality Analysis

  • A breakdown of the of the compounded returns having invested during the period discovered as producing the best return, the best return under the greatest number of profitable periods, and the buy and hold return. Analysis is done over a 10 year range to complement the 20 year chart.

Support/Resistance figures

  • The price levels in which pullback is expected in a manner such that the price is unable to exceed

Support and Resistance Analysis

  • Examines the current price in relation to previously identified support and resistance levels. If the price exceeds the support or resistance levels identified, the start of a new trend is a clear possibility.

MACD Analysis

  • A momentum indicator that shows the relation between a 12 and 26 day moving averages.  If price movements cause the shorter, faster moving average to divert away from the longer, slower moving average, it is expected that a pullback will occur to eliminate the divergence. If the MACD is positive (above 0), the short-term price action has exceeded the long term averages, and a price decline might be expected to bring the two averages in-line. And vice versa if MACD is negative.

MACD vs. Signal

  • A “trigger” to buy or sell based on the momentum of a security utilizing a 9-day signal line that is shorter and faster than its MACD counterpart. If the signal line crosses the MACD line, this implies that the short term price action is breaking away from longer term price trends. A signal line below MACD suggests buying opportunities, and vice versa if above.

RSI Analysis

  • A momentum indicator that attempts to explain the relation of up days compared to down days as a number ranging from 0 to 100. An RSI greater than 70 is considered to be overbought, while an RSI less than 30 is considered to be oversold. If a stock is overbought or oversold, a correction may be expected.

Stochastic (Fast) Analysis

  • A momentum indicator that details the relation of the most recent closing price to highs and lows over a given period. The result is a number ranging from 0 to 100 that reveals a stock as being oversold if less than 20 and overbought if greater than 80.

50 Day vs. 200 Day Moving Average Analysis

  • A comparative indicator that details the relation of the most recent trend, 50 day moving average, with that of the longer 200 day average.  A 50 day stock MA above its 200 day is indication that the investment is trending upwards, and vice versa if below.

Year over Year Trend

  • A performance indicator based upon the investment return over the past year.

Critical Level Analysis

  • A Tech Talk created trading range that establishes a high and low value in which the investment trades within given the current trend. Unlike the support and resistance levels, a stock may surpass the critical high or low.  The values provide indication of a likely pullback upon crossing these calculated levels.  If the price of a stock were to exceed a critical high, based upon a regression analysis, past history has revealed that sellers will exceed buyers at this level causing the price to fall soon thereafter. And vice versa if the stock were to fall below the critical low.

MFI Analysis

  • A momentum indicator similar to RSI that incorporates trading volumes to compare in-flows and out-flows of an investment over a given period of time.

Candlestick Analysis

  • An analytical technique that examines price charts containing high, low, open and close values in a “candlestick”-like format that allow investors, particularly day traders, the ability to examine the extent to which buyers and sellers are moving the price.

Situational Analysis

  • Analysis of the impact that certain events may have on the price of a stock. If the market buys on the rumor and sells on the news, a situational analysis will reveal the expected impacts, based on past history, to the price of the stock and the way the market reacts to the news as it is released.

Further Analysis

  • Consensus Recommendation – The opinion of  investment performance going forward from other analysts in the market.

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