OVERVIEW
The Japanese reversal charts described in this chapter are a relatively new addition to the realm of technical analysis. Their introduction to Western traders is primarily due to the efforts of trader and author Steven Nison.
RENKO CHART
The renko charting method is thought to have acquired its name from renga, the
Japanese word for bricks. Renko charts are similar to three-line break charts except
that in a renko chart, a line (or “brick” as they are called) is drawn in the direction of the prior move only if prices move by a minimum amount (i.e., the box size). The bricks are always equal in size. For example, in a 3-unit (“3-brick”) renko chart, a 12-point rally is displayed as four 3-unit-tall renko bricks.
Basic trend reversals are signaled with the emergence of a new white or black
brick. A new white brick indicates the beginning of a new uptrend. A new black brick
indicates the beginning of a new downtrend. Since the renko chart is a trend-follow-
ing technique, there are times when renko charts produce whipsaws, giving signals
near the end of short-lived trends. However, the expectation with a trend-following
technique is that it allows you to ride the major portion of significant trends.
Since a renko chart isolates the underlying price trend by filtering out the minor price changes, renko charts can also be very helpful when determining support and resistance levels.
Brick Size
Brick size is analogous to the point and figure box size and determines the minimum
price change to display. Renko charts do not have an equivalent to point and figure reversal amount since the default is always one brick. To filter out noise, simply increase the brick size.
Algorithm
To draw renko bricks, today’s close is compared with the high and low of the previous
brick (white or black):
•If the closing price rises above the top of the previous brick by at least the box size,
one or more white bricks are drawn in new columns. The height of the bricks is al-
ways equal to the box size.
•If the closing price falls below the bottom of the previous brick by at least the box
size, one or more black bricks are drawn in new columns. Again, the height of the
bricks is always equal to the box size.
•If prices move more than the box size, but not enough to create two bricks, only one
brick is drawn. For example, in a two-unit (“2-brick”) renko chart, if the prices
move from 100 to 103, only one white brick is drawn from 100 to 102. The rest of the
move, from 102 to 103, is not shown on the renko chart.
Programmatically, the same CalculateReversalColumns() function is called prior to
plotting the chart (this function appears in Chapter 12 on point and figure charts).
Note that the x-axis does not represent time in a linear fashion, since there is one x-axis unit per brick.
KAGI CHART
Kagi charts are believed to have been created around the time that the Japanese stock
market began trading in the 1870s. Kagi charts display a series of connecting vertical lines where the thickness (or color) and direction of the lines are dependent on the price action. The charts ignore the passage of time. If prices continue to move in the same direction, the vertical line is extended. However, if prices reverse by a minimum reversal amount, a new kagi line is then drawn in a new column. When prices penetrate a previous high or low, the thickness (or color) of the kagi line changes. Kagi charts were brought to the United States by Steven Nison in 1994 with the publication of his book Beyond Candlesticks.
OTHER REVERSAL CHARTS
Algorithm
The first closing price in a kagi chart is the starting price. To draw the first kagi line, the current close is compared to the starting price.
•If the current price is greater than or equal to the starting price, then a thick line is drawn from the starting price to the new closing price.
•If today’s price is less than to the starting price, then a thin line is drawn from the starting price to the new closing price.
To draw subsequent lines, compare the closing price to the tip (i.e., bottom or top)
of the previous kagi line:
•If the price continues in the same direction as the previous line, the line is extended in the same direction, no matter how small the move.
•If the price moves in the opposite direction by at least the reversal amount (this
may take several days), then a short horizontal line is drawn to the next column and
a new vertical line is drawn to the closing price.
•If the price moves in the opposite direction of the current column by less than the
reversal amount no lines are drawn.
•If a thin kagi line exceeds the prior high point on the chart, the line becomes thick.
Likewise, if a thick kagi line falls below the prior low point, the line becomes thin.
Kagi charts are designed to plot a single line until the price reverses by a predetermined amount, where another line is then begun. It is an attempt to smooth out the noise of daily trading activity so that the trend can be more clearly represented. The thickness of kagi lines is significant when prior highs and prior lows are exceeded.
Kagi charts use a modified form of the orthogonal line chart as a basis. When new
highs above the previous column occur, the line color becomes green. When new lows
below the previous column occur, the line color becomes red. Originally, the technique was to draw thick lines for new highs and thin lines for new lows, but the color alternation scheme accomplished the same end and has more visual appeal. (
Interpretation
Kagi charts illustrate the forces of supply and demand on a security:
•A series of thick (or green) lines shows that demand is exceeding supply (a rally).
•A series of thin (or red) lines shows that supply is exceeding demand (a decline).
•Alternating thick (or green) and thin (or red) lines show that the market is in a state of equilibrium (i.e., supply equals demand).
The most basic trading technique for kagi charts is to buy when the kagi line
changes from thin to thick (or red to green) and to sell when the kagi line changes from thick to thin (or green to red). A sequence of higher highs and higher lows on a kagi chart shows that the underlying forces are bullish, whereas, lower highs and lower lows indicate underlying weakness.
THREE-LINE BREAK CHART
Three-line break charts display a series of vertical boxes (lines) that are based on
changes in prices. As with kagi, point and figure, and renko charts, three-line break
charts ignore the passage of time. The three-line break charting method is so named because of the number of lines typically used. Three-line break charts were first brought to the United States by Steven Nison in 1994 with the publication of his book Beyond Candlesticks.
An advantage of three-line break charts is that there is no arbitrary fixed reversal
amount. It is the price action that gives the indication of a reversal. The disadvantage of three-line break charts is that the signals are generated after the new trend is well under way. However, many traders are willing to accept the late signals in exchange for calling major trends.
Number of Lines
You can adjust the sensitivity of the reversal criteria by changing the number of lines in the break. For example, short-term traders might use two-line breaks to get more reversals, whereas a longer-term investor might use four-line or even 10-line breaks to reduce the number of reversals. Of these choices, the three-line break is the most popular in Japan. Steven Nison recommends using three-line break charts in
conjunction with candlestick charts. He suggests using the three-line break chart to
determine the prevailing trend and then using candlestick patterns to time your indi-
vidual trades.
Algorithm
Line break charts are always based on closing prices. The general rules for calculating a line break chart are:
•If the price exceeds the previous line’s high price, a new white line is drawn.
•If the price falls below the previous line’s low price, a new black line is drawn.
•If the price neither rises above nor falls below the previous line, nothing is drawn.
Japanese Reversal Charts
In a three-line break chart, if rallies are strong enough to display three consecutive lines of the same color, then prices must reverse by the extreme price of the last three lines in order to create a new line:
•If a rally is powerful enough to form three consecutive white lines, then prices must fall below the lowest point of the last three white lines before a new black line is drawn.
•If a sell-off is powerful enough to form three consecutive black lines, then prices
must rise above the highest point of the last three black lines before a new white
line is drawn.
Interpretation
The following are some very basic trading rules for a three-line break chart:
•Buy when a white line emerges after three adjacent black lines (a white turnaround
line).
•Sell when a black line appears after three adjacent white lines (a black turnaround
line).
•Avoid trading in trendless markets where the lines alternate between black and
white.
Friday, November 2, 2007
Forex Trading System- Western reversal charts
OVERVIEW
All reversal charts share a common functionality: to filter out insignificant price movements below a user-selected range. The most popular is the point and figure (P&F)
chart. In this chapter and the following chapter, we explore the other variations within the reversal chart family so that traders may gain a modest acquaintance with alternative methods to P&F and diagonal swing charting.
GEOMETRIC CHART
The earliest reference to the geometric chart that we were able to locate is in the very informative book Point and Figure Method of Anticipating Stock Market Price Movements by Victor De Villiers and Owen Taylor (Traders Library, 1934).
This chart in theory displays the same information as a standard P&F chart except
that the columns of Xs and Os have been converted to vertical lines with interconnecting horizontal lines at the reversal points. Some traders may say the advantage of the geometric chart is that it has a cleaner, simpler visual presentation of the data, while an advantage of the standard P&F chart is that its component elements (Xs and Os) are readily countable. We emphasize that traders should use the method with which they feel most comfortable. In Figures 32.1 through 32.3 are examples of the geometric charts using different box sizes and reversal amounts.
TREND OUTLINE CHART
The trend outline chart can also be attributed to De Villiers and Taylor in the same book cited earlier. One diagonal line in the trend outline chart represents two straight lines in the geometric chart (one vertical and an adjacent horizontal line). Examples of the trend outline chart are provided in Figures 32.4, 32.5, and 32.6.
Readers will note the similarities between the trend outline chart and the swing
chart described in Part 3. The difference is that each subsequent vertex (either a peak or a valley) is equally spaced along the x-axis in the trend outline chart while peaks and valleys in a swing chart represent the actual time elapsed in the corresponding OHLC bar chart.
PIVOT CHART
The pivot chart (shown in Figure 32.7) is unique among reversal charts in that it requires no user-supplied parameters. This chart uses the interval high and low only, so that converting OHLC data to its equivalent closes-only time series is not necessary.
The underlying premise of the pivot chart is that once a trend is in motion then the
pivot algorithm favors the continuation of that trend. A reversal in direction is possible only when a continuation increment does not occur. For example, assume an upward trend has been established. The following rules apply:
•If the current high is greater than the previous high regardless of magnitude, then
the trend continues.
•If the current high is equal to the previous high, nothing is plotted.
•If the current high is less than the previous high, then the trend reverses and the
current low is plotted.
•The converse is true when the original trend is downward.
Technically there is a method by which the trader can increase or decrease the sen-
sitivity of the pivot reversal mechanism: change the time interval of the underlying data.
As the time interval increases (say from 1-minute-interval data to 10-minute-interval
data), the sensitivity decreases in terms of minimum fluctuation units. This phenome-
non occurs because the percentage of overlapping range between adjacent bars de-
creases as the time interval grows.
It may appear at first sight that a pivot chart is equivalent to a swing chart of the
same OHLC data using a single minimum price fluctuation as the box size and a reversal
amount of one unit. However, they do differ since the pivot chart shows a stronger bias toward showing continuation of an existing trend.
OBSERVATION
As long as creative technical analysts pursue the quest to display raw and processed data in innovative and revealing methods, no matter how bizarre or esoteric, charting theory will never become stagnant.
All reversal charts share a common functionality: to filter out insignificant price movements below a user-selected range. The most popular is the point and figure (P&F)
chart. In this chapter and the following chapter, we explore the other variations within the reversal chart family so that traders may gain a modest acquaintance with alternative methods to P&F and diagonal swing charting.
GEOMETRIC CHART
The earliest reference to the geometric chart that we were able to locate is in the very informative book Point and Figure Method of Anticipating Stock Market Price Movements by Victor De Villiers and Owen Taylor (Traders Library, 1934).
This chart in theory displays the same information as a standard P&F chart except
that the columns of Xs and Os have been converted to vertical lines with interconnecting horizontal lines at the reversal points. Some traders may say the advantage of the geometric chart is that it has a cleaner, simpler visual presentation of the data, while an advantage of the standard P&F chart is that its component elements (Xs and Os) are readily countable. We emphasize that traders should use the method with which they feel most comfortable. In Figures 32.1 through 32.3 are examples of the geometric charts using different box sizes and reversal amounts.
TREND OUTLINE CHART
The trend outline chart can also be attributed to De Villiers and Taylor in the same book cited earlier. One diagonal line in the trend outline chart represents two straight lines in the geometric chart (one vertical and an adjacent horizontal line). Examples of the trend outline chart are provided in Figures 32.4, 32.5, and 32.6.
Readers will note the similarities between the trend outline chart and the swing
chart described in Part 3. The difference is that each subsequent vertex (either a peak or a valley) is equally spaced along the x-axis in the trend outline chart while peaks and valleys in a swing chart represent the actual time elapsed in the corresponding OHLC bar chart.
PIVOT CHART
The pivot chart (shown in Figure 32.7) is unique among reversal charts in that it requires no user-supplied parameters. This chart uses the interval high and low only, so that converting OHLC data to its equivalent closes-only time series is not necessary.
The underlying premise of the pivot chart is that once a trend is in motion then the
pivot algorithm favors the continuation of that trend. A reversal in direction is possible only when a continuation increment does not occur. For example, assume an upward trend has been established. The following rules apply:
•If the current high is greater than the previous high regardless of magnitude, then
the trend continues.
•If the current high is equal to the previous high, nothing is plotted.
•If the current high is less than the previous high, then the trend reverses and the
current low is plotted.
•The converse is true when the original trend is downward.
Technically there is a method by which the trader can increase or decrease the sen-
sitivity of the pivot reversal mechanism: change the time interval of the underlying data.
As the time interval increases (say from 1-minute-interval data to 10-minute-interval
data), the sensitivity decreases in terms of minimum fluctuation units. This phenome-
non occurs because the percentage of overlapping range between adjacent bars de-
creases as the time interval grows.
It may appear at first sight that a pivot chart is equivalent to a swing chart of the
same OHLC data using a single minimum price fluctuation as the box size and a reversal
amount of one unit. However, they do differ since the pivot chart shows a stronger bias toward showing continuation of an existing trend.
OBSERVATION
As long as creative technical analysts pursue the quest to display raw and processed data in innovative and revealing methods, no matter how bizarre or esoteric, charting theory will never become stagnant.
Forex Trading System- Swing Summary
OVERVIEW
We have introduced quite a lot of new and technical information in the preceding chapters. Our goal in this chapter is to unify the salient estimating routines into a viable tool that traders may incorporate into their existing trading systems.
SELECTING SWING PARAMETERS
In his very informative book, Point and Figure: Commodity and Stock Trading Tech-
niques (Traders Press, 1997), author and trader Kermit C. Zieg Jr. suggests the use of a constant reversal amount, which he sets at three boxes. He prefers to vary the box size according to the underlying security. Table 31.1 is our recommendation based loosely on Mr. Zieg’s idea.
An alternative method of setting swing reversal parameters is the converse of Zieg’s
suggestion; that is, set the box size to the constant minimum price fluctuation (one pip in currency markets), then vary the reversal amounts according to the influence of the parity rates of the individual currency pairs. We recommend that the transaction cost (the bid/ask spread) multiplied by 3 be used to initialize the swing reversal algorithm.
The second column in Table 31.2 is the average transaction cost of several major cur-
rency dealers. However, if Zieg’s method is preferred, then set the box size to the transaction cost, and a constant three-box reversal amount can be used. Essentially, we recommend that currency traders experiment with different combinations based on their different trading objectives.
COMPOSITE AVERAGE ESTIMATES
The idea here is very simple and direct: to generate multiple discrete estimates using the different methods described in earlier chapters and combine them to create one average forecast. In all instances we use one pip as the box size and three-, five-, and nine-box reversal amounts. We also use a three-wave cycle where the heights of the last three waves in the swing data are 15, –12, and 9 (see Figure 31.1):
A = 1.0002
B = 1.0017
C = 1.0005
D = 1.0014
Linear Regression Method
In this section, we apply an ordinary least squares (OLS) linear regression to the same three waves with heights 15, –12 and 9. Technically, the regression method requires only the final two waves and our model becomes:
Wave 4 = (A Wave 2) + (B Wave 3) + C
The estimate for the three-box reversal amount is:
Wave 4 = 0.7119(12) + 0.0871(–9) + 0.0110
Wave 4 = 8.5428 – 0.7839 + 0.0110
Wave 4 = 7.7699
A five-box reversal amount produces:
Wave 4 = 0.0140(12) – 1.1137(–9) + 0.0047
Wave 4 = 0.1680 + 7.8863 + 0.0047
Wave 4 = 8.0590
The estimated height using a nine-box reversal amount is:
Wave 4 = 0.2167(12) – 0.8128 (–9) + 4.1850
Wave 4 = 2.6004 + 7.3152 + 4.1850
Wave 4 = 14.1006
Convert pips to discrete prices and subtract from last vertex D:
1.0014 – 0.00078 = 1.00062
1.0014 – 0.00081 = 1.00059
1.0014 – 0.00141 = 0.99999
CAVEAT
The various mathematic and statistical approaches illustrated in this book are, to our knowledge, new and therefore experimental. The rationale behind averaging multiple discrete forecasts (nine in the example in this chapter) is very logical, though, and should theoretically enhance the validity of the desired output. Nonetheless, the authors would like to emphasize that a thorough testing period and ample paper trading are advisable before traders incorporate any one method into their existing trading systems.
We have introduced quite a lot of new and technical information in the preceding chapters. Our goal in this chapter is to unify the salient estimating routines into a viable tool that traders may incorporate into their existing trading systems.
SELECTING SWING PARAMETERS
In his very informative book, Point and Figure: Commodity and Stock Trading Tech-
niques (Traders Press, 1997), author and trader Kermit C. Zieg Jr. suggests the use of a constant reversal amount, which he sets at three boxes. He prefers to vary the box size according to the underlying security. Table 31.1 is our recommendation based loosely on Mr. Zieg’s idea.
An alternative method of setting swing reversal parameters is the converse of Zieg’s
suggestion; that is, set the box size to the constant minimum price fluctuation (one pip in currency markets), then vary the reversal amounts according to the influence of the parity rates of the individual currency pairs. We recommend that the transaction cost (the bid/ask spread) multiplied by 3 be used to initialize the swing reversal algorithm.
The second column in Table 31.2 is the average transaction cost of several major cur-
rency dealers. However, if Zieg’s method is preferred, then set the box size to the transaction cost, and a constant three-box reversal amount can be used. Essentially, we recommend that currency traders experiment with different combinations based on their different trading objectives.
COMPOSITE AVERAGE ESTIMATES
The idea here is very simple and direct: to generate multiple discrete estimates using the different methods described in earlier chapters and combine them to create one average forecast. In all instances we use one pip as the box size and three-, five-, and nine-box reversal amounts. We also use a three-wave cycle where the heights of the last three waves in the swing data are 15, –12, and 9 (see Figure 31.1):
A = 1.0002
B = 1.0017
C = 1.0005
D = 1.0014
Linear Regression Method
In this section, we apply an ordinary least squares (OLS) linear regression to the same three waves with heights 15, –12 and 9. Technically, the regression method requires only the final two waves and our model becomes:
Wave 4 = (A Wave 2) + (B Wave 3) + C
The estimate for the three-box reversal amount is:
Wave 4 = 0.7119(12) + 0.0871(–9) + 0.0110
Wave 4 = 8.5428 – 0.7839 + 0.0110
Wave 4 = 7.7699
A five-box reversal amount produces:
Wave 4 = 0.0140(12) – 1.1137(–9) + 0.0047
Wave 4 = 0.1680 + 7.8863 + 0.0047
Wave 4 = 8.0590
The estimated height using a nine-box reversal amount is:
Wave 4 = 0.2167(12) – 0.8128 (–9) + 4.1850
Wave 4 = 2.6004 + 7.3152 + 4.1850
Wave 4 = 14.1006
Convert pips to discrete prices and subtract from last vertex D:
1.0014 – 0.00078 = 1.00062
1.0014 – 0.00081 = 1.00059
1.0014 – 0.00141 = 0.99999
CAVEAT
The various mathematic and statistical approaches illustrated in this book are, to our knowledge, new and therefore experimental. The rationale behind averaging multiple discrete forecasts (nine in the example in this chapter) is very logical, though, and should theoretically enhance the validity of the desired output. Nonetheless, the authors would like to emphasize that a thorough testing period and ample paper trading are advisable before traders incorporate any one method into their existing trading systems.
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