ELLIOTT WAVE

A flat correction differs from a zigzag in that the subwave sequence is 3-3-5, as shown in Figures 1 and 2. Since the first actionary wave,

Fibonacci studies: arcs, fans, retracements, and time

Overview: Leonardo Fibonacci was a mathematician who was born in Italy around the year 1170. It is believed that Mr. Fibonacci discovered..

Indicator

The Negative Volume Index (“NVI”) focuses on days where the volume decreases from the previous day. The premise being that the “smart money” takes positions on days when volume decreases

Basic Technicals

MACD technical analysis MACD technical analysis stands for moving average convergence/divergence analysis of stocks.

Fundamental Analysis

Doubling Stocks Review: Is this a scam? If you are looking for the truth about doubling stocks this is a necessity. One always thought there was something wrong with a doubling of stocks.

Wednesday, June 30, 2010

SWING INDEX

Overview
Developed by Welles Wilder, the Swing Index seeks to isolate the “real” price of a security by comparing the relationships between the current prices (i.e., open, high, low, and close) and the previous period’s prices.
Interpretation
The Swing Index is primarily used as a component of the Accumulation Swing Index.
Example
The following chart shows the British Pound and the Swing Index.
You can see that by itself, the Swing Index is an erratic plot. The value of this indicator develops when it is accumulated into the Accumulation Swing Index.
Calculation
Although it is beyond the scope of this book to completely define the Swing Index, the basic formula is shown below. Step-by-step instructions on calculating the Swing Index are provided in Wilder’s book, New Concepts In Technical Trading Systems.
Where,
The following table lists the limit moves for several commodities. You can get a list of limit moves from your broker.
Table
Commodity Limit Move
Coffee           $0.06
??                                                                                                     Gold             $75
Heatingoil   $0.04
Hogs$         $0.015
Soybeans    $0.3
T-Bound    $3
You may need to adjust the limit moves shown in the above table based on the position of the decimal in your data. For
example, if the price of corn is quoted as $2.45, the limit move would be $0.10. However, if the price of corn is quoted as $245.00, the limit move would be $10.00.
If the security does not have a limit move (e.g., a stock or some futures), use an extremely high value (e.g., $30,000).
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Monday, June 28, 2010

STANDARD DEVIATION

Overview
Standard Deviation is a statistical measure of volatility. Standard Deviation is typically used as a component of other
indicators, rather than as a stand-alone indicator. For example, Bollinger Bands are calculated by adding a security’s Standard Deviation to a moving average.

Interpretation
High Standard Deviation values occur when the data item being analyzed (e.g., prices or an indicator) is changing
dramatically. Similarly, low Standard Deviation values occur when prices are stable.Many analysts feel that major tops are accompanied with high volatility as investors struggle with both euphoria and fear. Major bottoms are expected to be calmer as investors have few expectations of profits.
Example
The following chart shows Proctor & Gamble and its 10-week Standard Deviation.The extremely low Standard Deviation values at points “A” and “B” preceded significant rallies at points 1 and “2.”
Standard Deviation is derived by calculating an n-period simple moving average of the data item (i.e., the closing price or an indicator), summing the squares of the difference between the data item and its moving average over each of the preceding n-time periods, dividing this sum by n, and then calculating the square root of this result.
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Thursday, June 24, 2010

RELATIVE STRENGTH INDEX

Overview
The Relative Strength Index (“RSI”) is a popular oscillator. It was first introduced by Welles Wilder in an article in Commodities (now known as Futures) Magazine in June, 1978. Step-by-step instructions on calculating and interpreting the RSI are also provided in Mr. Wilder’s book, New Concepts in Technical Trading Systems.The name “Relative Strength Index” is slightly misleading as the RSI does not compare the relative strength of two securities, but rather the internal strength of a single security. A more appropriate name might be “Internal Strength Index.” Relative strength charts that compare two market indices, which are often referred to as Comparative Relative Strength.
Interpretation
When Wilder introduced the RSI, he recommended using a 14-day RSI. Since then, the 9-day and 25-day RSIs have also gained popularity. Because you can vary the number of time periods in the RSI calculation, I suggest that you experiment to find the period that works best for you. (The fewer days used to calculate the RSI, the more volatile the indicator.)
The RSI is a price-following oscillator that ranges between 0 and 100. A popular method of analyzing the RSI is to look for a divergence in which the security is making a new high, but the RSI is failing to surpass its previous high. This divergence is an
indication of an impending reversal. When the RSI then turns down and falls below its most recent trough, it is said to have
completed a “failure swing.” The failure swing is considered a confirmation of the impending reversal.In Mr. Wilder’s book, he discusses five uses of the RSI in analyzing commodity charts. These methods can be applied to other security types as well.
Tops and Bottoms.
The RSI usually tops above 70 and bottoms below 30. It usually forms these tops and bottoms before the underlying price chart.
Chart Formations.
The RSI often forms chart patterns such as head and shoulders (page 215) or triangles (page 216) that may or may not be visible on the price chart.
Failure Swings.
(also known as support or resistance penetrations or breakouts). This is where the RSI surpasses a previous high (peak) or falls below a recent low (trough).
Support and Resistance.
The RSI shows, sometimes more clearly than price themselves, levels of support and resistance.
Divergences.
As discussed above, divergences occur when the price makes a new high (or low) that is not confirmed by a new high (or low) in the RSI. Prices usually correct and move in the direction of the RSI.
Example
A bullish divergence occurred during May and June as prices were falling while the RSI was rising. Prices subsequently corrected and trended upward.
Calculation
The RSI is a fairly simple formula, but is difficult to explain without pages of examples. Refer to Wilder’s book for additional calculation information. The basic formula is:
Where:
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Tuesday, June 22, 2010

NEGATIVE VOLUME INDEX

Overview
The Negative Volume Index (“NVI”) focuses on days where the volume decreases from the previous day. The premise being
that the “smart money” takes positions on days when volume decreases.
Interpretation
The interpretation of the NVI assumes that on days when volume increases, the crowd-following “uninformed” investors
are in the market. Conversely, on days with decreased volume, the “smart money” is quietly taking positions. Thus, the NVI
displays what the smart money is doing.
In Stock Market Logic, Norman Fosback points out that the odds of a bull market are 95 out of 100 when the NVI rises
above its one-year moving average. The odds of a bull market are roughly 50/50 when the NVI is below its one-year average.
Therefore, the NVI is most usefuly as a bull market indicator.
Example
The following chart shows Avon and its NVI. I drew “buy” arrows whenever the NVI crossed above its 1-year (255-trading day) moving average.

I drew “equal-signs” when the NVI fell below the moving average. You can see that the NVI did a great job of identifying profitable opportunities.
Calculation
If today’s volume is less than yesterday’s volume then:
If today’s volume is greater than or equal to yesterday’s volume then:

Because falling prices are usually associated with falling volume, the NVI usually trends downward.
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Thursday, June 17, 2010

OVERBOUGHT/OVERSOLD

Overview
The Overbought/Oversold (“OB/OS”) indicator is a market breadth indicator based on the smoothed difference between
advancing and declining issues.InterpretationThe OB/OS indicator shows when the stock market is overbought (and a correction is due) and when it is oversold (and a rally is due).
Readings above +200 are generally considered bearish and readings below -200 are generally considered bullish. When the OB/OS indicator falls below +200 a sell signal is generated. Similarly, a buy signal is generated when the OB/OS indicator
rises above -200.As with all OB/OS-type indicators, extreme readings may be a sign of a change in investor expectations and may not be followed by the expected correction. (Refer to the discussion on the Advance/Decline Ratio, and the McClellan Oscillator, for
additional comments on extremely overbought/oversold conditions.)
Example
The following chart shows the DJIA and the Overbought/Oversold indicator.

I drew “buy” and “sell” arrows when the indicator penetrated the +200/-200 levels. The OB/OS indicator works very well in
this type of trading-range market.
Calculation
The Overbought/Oversold indicator is a 10-period exponential moving average of the difference between the number of advancing and declining issues.

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Wednesday, June 9, 2010

OPTION ANALYSIS

Overview
The most widely used option pricing model is the Black-Scholes option valuation model which was developed by Fisher Black and Myron Scholes in 1973.The Black-Scholes model helps determine the fair market value of an option based on the security’s price and volatility, time until expiration, and the current market interest rate. The following assumptions were made by Black and Scholes when the model was developed:
1.  Markets are “frictionless.” In other words, there are no transaction costs or taxes; all market participants may borrow and lend at the “riskless” rate of interest; there are no penalties for short selling; and all securities are infinitely divisible (i.e., fractional shares can be purchased).
2.  Stock prices are lognormally distributed (i.e., they follow a bell curve). This means that a stock can double in price as easily as it can drop to half its price.
3.  Stocks do not pay dividends or make any distributions. (The model is often modified to allow for dividend adjustments.)
4.  The option can only be exercised on the expiration date.
The components of the option model are security price, volatility, option life, market interest rate, and dividend (if any).I suggest you refer to the book Option Volatility and Pricing Strategies, by Sheldon Natenberg for more information on calculations and strategies using the Black-Scholes model.
Interpretation
Put/Call Price
The Put/Call Price is the main output of the Black-Scholes model. It shows how much an option should sell for based on
the various components that make up the model (e.g., volatility, option life, security price, etc). It helps answer the
question, “Is the option overpriced or underpriced?”The usefulness of the Put/Call Price is basically two-fold:
1.  It helps you locate mispriced options. The option purchaser can use the model to find options that areunderpriced. The option writer can use the model to find options that are overpriced.
2.  It helps you form a riskless hedge to earn arbitrage profits. For example, you could buy undervalued calls and then short the underlying stock. This creates a riskless hedge because regardless of whether the security’s price goes up or down, the two positions will exactly offset each other. You would then wait for the option to return to its fair market value to earn arbitrage profits.
Delta (below) is used to determine the number of shares to purchase in order to form a riskless hedge.
Delta
Delta shows the amount that the option’s price will change if the underlying security’s price changes by $1.00.For example, if XYZ is selling for $25.00/share, a call option on XYZ is selling for $2.00 and the Delta is 75%, then the option’s price should increase $0.75 (to $2.75) if the price of XYZ increases to $26.00/share. In other words, the option should go up $0.75 for each $1.00 that XYZ goes up.If an option is deep in-the-money, then it will have a high Delta, because almost all of the gain/loss in the security will be
reflected in the option price. Conversely, deep out-of-the-money options will have a low Delta, because very little of the gain/loss in the security is reflected in the option price.If you don’t have a computer, the rough rule-of-thumb for calculating Delta is: 75% for an option $5.00 in the money, 50% for an option at the money, and %25 for an option $5.00 out of the money.
As an in-the-money option nears expiration, the Delta will approach 100% because the amount of time remaining for the
option to move out-of-the-money is small.Delta is also used to determine the correct number of shares to buy/short to form a “riskless hedge.” For example, suppose the Delta on a put option is 66%. A riskless hedge would result from owning a ratio of two-thirds (66%) a position in stock (i.e., 66 shares) to every one long position in a put option contract. If the stock price goes up one point, then the stock position will increase $66.00. This $66.00 increase should be exactly offset by a $66.00 decrease in the value of the put option contract.As discussed on earlier, forming a riskless hedge gives the investor the potential of earning arbitrage profits, by profiting from the undervalued option’s return to its fair market value (i.e., the price at which the option is neither overpriced nor underpriced). Theoretically, the market will eventually value underpriced options at their fair market value. However, it should be noted that high transaction costs may undermine this theory.
Gamma
Gamma shows the anticipated change in Delta, given a one point increase in the underlying security. Thus, it shows how responsive Delta is to a change in the underlying security’s price. For example, a Gamma of four indicates that the Delta will increase four points (e.g., from 50% to 54%) for each one point increase in the underlying security’s price.Gamma indicates the amount of risk involved with an option position. A large Gamma indicates higher risk, because the value of the option can change more quickly. However, a
trader may desire higher risk depending on the strategy employed.
Option Life
Option Life shows the number of days until expiration. Generally speaking, the longer the time until expiration, the more valuable the option.A graph of Option Life appears as a stepped line from the upper-left to the lower-right side of the screen. The reason the line is stepped is because of weekends and holidays.
For example, on Friday there may be 146 days to expiration and on the following Monday only 143 days remaining.
Theta
Theta shows the change in the option’s price (in points) due to the effect of time alone. The longer the time until expiration, the
less effect that time has on the price of the option. However, as the option nears expiration, the effect can be great, particularly
on out-of-the-money options. Theta is also referred to as “time decay.”
For example, a Theta value of -0.0025 means that the option lost 1/4 of one cent due to the passage of time alone.
The effect of time on the option price is almost always positive. The more time until expiration the better chance the option has
of being in-the-money at expiration. The only exception to this positive relationship is deep in-the-money put options with an
expiration date far into the future.All other things being equal, options with low Thetas are more preferable (for purchase) than are those with high Thetas.
Vega
Vega shows the change in the option price due to an assumed 1% increase in the underlying security’s volatility. Vega shows
the dollar amount of gain that should be expected if the volatility goes up one point (all else being equal).
The effect of volatility on the option price is always positive. The greater the volatility of the underlying security, the better
chance the option has of being in-the-money at expiration. Therefore, options with higher volatilities will cost more than
those with lower volatilities.Since Vega measures the sensitivity of an option to a change in volatility, options with higher Vegas are more preferable (for purchase) than those with low Vegas.
Volatility
Volatility is a measurement that shows the degree of fluctuation that a security experiences over a given time frame.
Wide price movements over a short time frame are characteristic of high volatility stocks.Volatility is the only input parameter of the Black-Scholes model (e.g., security price, volatility, option life, market interest rate) that is calculated, yet the accuracy of the model is highly dependent on a good Volatility figure. The best measurement of volatility is the one that captures future price movements.
But if we knew what future price movements would be, we would care less about the Black-Scholes model–we’d be trading! However, reality forces us to estimate volatility. There are two ways to estimate volatility for use with the Black-Scholes model: Historical Volatility and Implied Volatility.Historical Volatility measures the actual volatility of the security’s prices using a standard deviation based formula. It shows how volatile prices have been over the last x-time periods. The advantage of histocial volatility is that can be
calculated using only historical security prices. When you calculate the Black-Scholes put/call price using historial
volatililty, most options appear overpriced.
A more widely used measure of option volatility is called Implied Volatility. Implied Volatility is the amount of volatility
that the option market is assuming (i.e., implying) for the option. To calculate implied volatility, the actual option price,
security price, strike price, and the option expiration date are plugged into the Black-Scholes formula. The formula then
solves for the implied volatility.Options of high volatility stocks are worth more (i.e., carry higher premiums) than those with low volatility, because of the greater chance the option has of moving in-the-money by expiration. Option purchasers normally prefer options with high volatilities and option writers normally prefer options with low volatilities (all else being equal).
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Monday, June 7, 2010

On Balance Volume

Overview
On Balance Volume (“OBV”) is a momentum indicator that relates volume to price change.On Balance Volume was developed by Joe Granville and originally presented in his book New Strategy of Daily Stock Market Timing for Maximum Profits.
Interpretation
On Balance Volume is a running total of volume. It shows if volume is flowing into or out of a security. When the security
closes higher than the previous close, all of the day’s volume is considered up-volume. When the security closes lower than
the previous close, all of the day’s volume is considered down-volume.
A full explanation of OBV is beyond the scope of this book. If you would like further information on OBV analysis, I recommend that you read Granville’s book, New Strategy of Daily Stock Market Timing for Maximum Profits.
The basic assumption, regarding OBV analysis, is that OBV changes precede price changes. The theory is that smart
money can be seen flowing into the security by a rising OBV. When the public then moves into the security, both the security
and the OBV will surge ahead.
If the security’s price movement precedes OBV movement, a “non-confirmation” has occurred. Non-confirma-tions can occur
at bull market tops (when the security rises without, or before, the OBV) or at bear market bottoms (when the security falls
without, or before, the OBV).The OBV is in a rising trend when each new peak is higher than the previous peak and each new trough is higher than the previous trough. Likewise, the OBV is in a falling trend when each successive peak is lower than the previous peak and each successive trough is lower than the previous trough. When the OBV is moving sideways and is not making successive highs and lows, it is in a doubtful trend. \[See Figure 1]
Once a trend is established, it remains in force until it is broken. There are two ways in which the OBV trend can be broken. The first occurs when the trend changes from a rising
trend to a falling trend, or from a falling trend to a rising trend.The second way the OBV trend can be broken is if the trend
changes to a doubtful trend and remains doubtful for more than three days. Thus, if the security changes from a rising trend to a doubtful trend and remains doubtful for only two days before
changing back to a rising trend, the OBV is consid-ered to have always been in a rising trend.
When the OBV changes to a rising or falling trend, a “breakout” has occurred. Since OBV breakouts normally precede price
breakouts, investors should buy long on OBV upside breakouts. Likewise, investors should sell short when the OBV
makes a downside breakout. Positions should be held until the trend changes (as explain-ed in the preceding paragraph).
This method of analyzing On Balance Volume is designed for trading short-term cycles. According to Granville, investors
must act quickly and decisively if they wish to profit from short-term OBV analysis.
Example
The following chart shows Pepsi and the On Balance Volume indicator. I have labeled the OBV Up, Down, and Doubtful
trends.

A falling trend, as you will recall, is defined by lower peaks and lower troughs. Conversely, a rising trend is defined by higher peaks and higher troughs.
Calculation
On Balance Volume is calculated by adding the day’s volume to a cumulative total when the security’s price closes up, and
subtracting the day’s volume when the security’s price closes down.If today’s close is greater than yesterday’s close then:
If today’s close is greater than yesterday’s close then:
If today’s close is less than yesterday’s close then:
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Odd Lot Balance Index

Overview
The Odd Lot Balance Index (“OLBI”) is a market sentiment indicator that shows the ratio of odd lot sales to purchases (an
“odd lot” is a stock transaction of less than 100 shares). The assumption is that the “odd lotters,” the market’s smallest
traders, don’t know what they are doing.(Unfortunately, the trading of 99 share lots in an effort to skirt the “up-tick” rule, which requires that specialists take short positions only when prices move upward, has rendered odd lot
indicators less reliable.)
Interpretation
When the Odd Lot Balance Index is high, odd lotters are selling more than they are buying and are therefore bearish on the
market. To trade contrarily to the odd lotters, you should buy when they are selling (as indicated by a high OLBI) and sell
when the odd lotters are bullish and buying (as indicated by a low OLBI).You can smooth day-to-day fluctuations of the Odd Lot Balance Index by plotting a 10-day moving average of the Index.
Example
The following chart shows the S&P 500 and a 10-day moving average of the Odd Lot Balance Index.
I drew a vertical line when the odd lotters were excessively pessimistic–which turned out to be a good time to buy.
Calculation

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Saturday, June 5, 2010

MOVING AVERAGES


Overview
A Moving Average is an indicator that shows the average value of a security’s price over a period of time. When calculating a
moving average, a mathematical analysis of the security’s average value over a predetermined time period is made. As
the security’s price changes, its average price moves up or down.There are five popular types of moving averages: simple (also
referred to as arithmetic), exponential, triangular, variable, and weighted. Moving averages can be calculated on any data
series including a security’s open, high, low, close, volume, or another indicator. A moving average of another moving
average is also common.The only significant difference between the various types of moving averages is the weight assigned to the most recent data. Simple moving averages apply equal weight to the prices. Exponential and weighted averages apply more weight
to recent prices. Triangular averages apply more weight to prices in the middle of the time period. And variable moving
averages change the weighting based on the volatility of prices.
Interpretation
The most popular method of interpreting a moving average is to compare the relationship between a moving average of the
security’s price with the security’s price itself. A buy signal is generated when the security’s price rises above its moving average and a sell signal is generated when the security’s price falls below its moving average.The following chart shows the Dow Jones Industrial Average (“DJIA”) from 1970 through 1993.
This type of moving average trading system is not intended to get you in at the exact bottom nor out at the exact top. Rather,
it is designed to keep you in line with the security’s price trend by buying shortly after the security’s price bottoms and selling
shortly after it tops.
The critical element in a moving average is the number of time periods used in calculating the average. When using hindsight,
you can always find a moving average that would have been profitable (using a computer, I found that the optimum number
of months in the preceding chart would have been 43). The key is to find a moving average that will be consistently profitable.
The most popular moving average is the 39-week (or 200-day) moving average. This moving average has an excellent track
record in timing the major (long-term) market cycles.
The length of a moving average should fit the market cycle you wish to follow. For example if you determine that a security has
a 40-day peak to peak cycle, the ideal moving average length would be 21 days calculated using the following formula:

—————————————————–
Trend                                           Moving Average
—————————————————–
Very Short Term                    5-13 days
Short Term                               14-25 days
Minor Intermediate              26-49 days
Intermediate                            50-100 days
Long Term                                  100-200 days
——————————————————
You can convert a daily moving average quantity into a weekly moving average quantity by dividing the number of days by 5
(e.g., a 200-day moving average is almost identical to a 40-week moving average). To convert a daily moving average
quantity into a monthly quantity, divide the number of days by 21 (e.g., a 200-day moving average is very similar to a 9-
month moving average, because there are approximately 21 trading days in a month).Moving averages can also be calculated and plotted on indicators. The interpretation of an indicator’s moving average is similar to the interpretation of a security’s moving average:
when the indicator rises above its moving average, it signifies a continued upward movement by the indicator; when the
indicator falls below its moving average, it signifies a continued downward movement by the indicator.
Indicators which are especially well-suited for use with moving average penetration systems include the MACD, Price ROC,
Momentum, and Stochastics.Some indicators, such as short-term Stochastics, fluctuate so erratically that it is difficult to tell what their trend really is. By erasing the indicator and then plotting a moving average of the indica-tor, you can see the general trend of the indicator rather than its day-to-day fluctuations.
Whipsaws can be reduced, at the expense of slightly later signals, by plotting a short-term moving average (e.g., 2-10
day) of oscillating indicators such as the 12-day ROC, Stochas-tics, or the RSI. For example, rather than selling when the
Stochastic Oscillator falls below 80, you might sell only when a 5-period moving average of the Stochastic Oscillator falls
below 80.
Example
The following chart shows Lincoln National and its 39-week exponential moving average.
Although the moving average does not pinpoint the tops and bottoms perfectly, it does provide a good indication of the
direction prices are trending.
Calculation
The following sections explain how to calculate moving averages of a security’s price using the various calculation
techniques.
Simple
A simple, or arithmetic, moving average is calculated by adding the closing price of the security for a number of time periods
(e.g., 12 days) and then dividing this total by the number of time periods. The result is the average price of the security
over the time period. Simple moving averages give equal weight to each daily price.
For example, to calculate a 21-day moving average of IBM: First, you would add IBM’s closing prices for the most recent
21 days. Next, you would divide that sum by 21; this would give you the average price of IBM over the preceding 21 days.
You would plot this average price on the chart. You would perform the same calculation tomorrow: add up the previous
21 days’ closing prices, divide by 21, and plot the resulting figure on the chart.
Where:

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Wednesday, June 2, 2010

GANN ANGLES

Overview
W. D. Gann (1878-1955) designed several unique techniques for studying price charts. Central to Gann’s techniques was
geometric angles in conjunction with time and price. Gann believed that specific geometric patterns and angles had
unique characteristics that could be used to predict price action.
All of Gann’s techniques require that equal time and price intervals be used on the charts, so that a rise/run of 1 x 1 will
always equal a 45 degree angle.
Interpretation
Gann believed that the ideal balance between time and price exists when prices rise or fall at a 45 degree angle relative to
the time axis. This is also called a 1 x 1 angle (i.e., prices rise one price unit for each time unit).
Gann Angles are drawn between a significant bottom and top (or vice versa) at various angles. Deemed the most important
by Gann, the 1 x 1 trendline signifies a bull market if prices are above the trendline or a bear market if below. Gann felt that a
1 x 1 trendline provides major support during an up-trend and when the trendline is broken, it signifies a major reversal in the
trend. Gann identified nine significant angles, with the 1 x 1 being the most important:
1 x 8 – 82.5 degrees
1 x 4 – 75 degrees
1 x 3 – 71.25 degrees
1 x 2 – 63.75 degrees
1 x 1 – 45 degrees
2 x 1 – 26.25 degrees
3 x 1 – 18.75 degrees
4 x 1 – 15 degrees
8 x 1 – 7.5 degrees
Note that in order for the rise/run values (e.g., 1 x 1, 1 x 8, etc) to match the actual angles (in degrees), the x- and y-axes must
have equally spaced intervals. This means that one unit on the x-axis (i.e., hour, day, week, month, etc) must be the same
distance as one unit on the y-axis. The easiest way to calibrate the chart is make sure that a 1 x 1 angle produces a 45 degree
angle.
Gann observed that each of the angles can provide support and resistance depending on the trend. For example, during an
up-trend the 1 x 1 angle tends to provide major support. A major reversal is signaled when prices fall below the 1 x 1
angled trendline. According to Gann, prices should then be expected to fall to the next trendline (i.e., the 2 x 1 angle). In
other words, as one angle is penetrated, expect prices to move and consolidate at the next angle.
Gann developed several techniques for studying market action. These include Gann Angles, Gann Fans, Gann Grids and
Cardinal Squares.
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