Advanced Technical Indicators
posted under
Philosophy of Technical Analysis
by ceecabolos
$$Technical Indicators $$
This appendix introduces several more advanced technical methods that can be used by themselves or with other technical studies. As with any technical approach, it is always recommended that investors do their own independent testing and research before actually investing.
DEMAND INDEX (DI)
Most technicians will agree that volume analysis is an important ingredient in determining a market's direction. The Demand Index (DI) is one of the early volume indicators that was developed in the 1970s by James Sibbett. The formula is quite complex (see end of this appendix). The Demand Index is the ratio of buying pres‑sure to selling pressure. When the buying pressure is greater than the selling pressure, the DI is above the zero line, which is positive. Greater selling pressure means the DI is below zero, which implies prices will move lower. Most traders also look for divergences between the DI and prices.
Figure A.1 is a weekly chart of T-Bond futures from early 1994 until late 1997. From April to November 1994, the DI was mostly below the zero line as bonds declined from 104 to the 96 area. While prices made lower lows (line A), the DI formed higher lows (line B). This is a classic positive, or bullish divergence, which suggested that bond prices were bottoming. The divergence was confirmed when the DI moved above the zero line at point 1. The DI reached its highest level for this rally in late May 1995 at point 2, and then dropped for the next six weeks before crossing below the zero line at point 3. It stayed negative for five weeks before it again turned positive. On the next rally the DI formed a significantly lower high in late November at point 4. While the DI was lower (line D), the bond contract was almost six points higher (line C). This negative or bearish divergence warned of a price peak.This indicator can also be used with stocks. The weekly chart of General Motors (Figure A.2) shows the DI plotted as a line rather than a histogram. This allows for trendlines to more easily be drawn on the indicator. I have personally found trend-line analysis of indicators to be quite valuable. Indicator trend-lines are often broken ahead of price trendlines. This was the case in late 1995 as the downtrend in the DI (line A) was broken a week before the corresponding price downtrend (line B). As this chart indicates, buying just one week earlier could have significantly improved the entry price. The DI also warned of a price high in mid-April 1996. While GM was making a new price high (line C), the DI had formed lower highs (line D). This warning signal came well ahead of the serious price decline in June and July.
HERRICK PAYOFF INDEX (HPI)
This indicator was developed by the late John Herrick as a way of analyzing commodity futures through changes in the open interest. As discussed in Chapter 7, changes in the open interest can give traders important clues as to whether a market trend is well supported or not.
The Herrick Payoff Index uses price, volume, and open interest to determine money flow into or out of a given commodity. This helps the trader spot divergences between the price action and the open interest. This is often quite important as buying or selling panics can often be identified through analysis of the open interest by the Herrick Payoff Index.
The most basic interpretation of the HPI is whether it is above or below the zero line. A positive value means that the HPI is projecting higher prices and that open interest is rising along with prices. Conversely, negative readings suggest that funds are flowing out of the commodity being analyzed.
One of the more volatile commodity markets is coffee, featured in Figure A.3. During March and April of 1997, the HPI had four crossings of the zero line with the last positive signal in early April (B) lasting until early June. The HPI dropped below zero in June, and even though prices were well below the highs, coffee dropped another 70 cents. Once again the HPI turned positive in late July very close to the lows. Over the next two months there were two short term signals and then another longer term sell signal. This is characteristic of the HPI when used on the daily data as it will cross above and below the zero line several times before a longer lasting buy or sell signal is given.The HPI, like the Demand Index, is most effective when used on the weekly data, as fewer false signals are evident. Divergence analysis can also be used to warn the trader of a change from positive to negative money flow. There are several good examples on the weekly T-Bond futures charts (Figure A.4) that covers approximately six years of trading. The HPI stayed positive from late 1992 until late 1993. The HPI peaked in early 1993 and, when bonds were almost 10 points higher (line A), the HPI was forming a lower high (line B). This negative divergence warned bond traders of the decline in prices that took place in 1994. The HPI violated the zero line in late October of 1993, but then turned slightly positive in early 1994 before plunging back below the zero line. The HPI reached its lowest
level in the first half of 1994 and bottomed well ahead of prices. As prices were making lower lows (line C), the HPI was forming higher lows and therefore a positive divergence (line D). The HPI moved back into positive territory in December 1994 as bonds were very close to their lows. A negative divergence was formed in late 1995 (line F), after bonds had rallied over 25 points from the late 1994 lows. The zero line was crossed several times in 1996 and early 1997 before the HPI moved firmly into positive territory. These two examples should illustrate why the HPI and its analysis of open interest can be helpful in analyzing a commodity market's direction.
STARC BANDS AND KELTNER CHANNELS
As discussed in Chapter 9, banding techniques have been used for many years. Two types that I prefer are based on the Average True Range. Despite this common factor, these two types of bands are used in very different ways. Average True Range is the average of true price ranges over x periods. True Range is the greatest distance from today's high to low, yesterday's close to today's high, or yesterday's close to today's low. See Welles Wilder's New Concepts in Technical Trading Systems.
Manning Stoller, a well known expert in the commodity business, developed the Stoller Average Range Channels or starc bands. In his formula the 15 period Average True Range is doubled and added to or subtracted from a 6 period moving average (MA). The upper band is starc+; the lower is starc-. Movement outside of these bands is uncommon and indicates an extreme situation. In this manner they can be used as trading filters. When prices are near or above the starc+ band, it is a high risk time to buy and a low risk time to sell. Conversely, if prices are at or below the starc- band, then it is a high risk selling zone and a more favorable point to buy.
The weekly continuation chart of gold futures (Figure A.5) is plotted with both the starc+ and starc- bands. In Feb. 1997 at point 1, gold prices slightly overshot the starc- band. Though the price action was weak, the starc bands indicated that this was not a good time to sell. By waiting, a better selling opportunity was likely to occur. Just three weeks later gold was $22 higher and at the starc+ band (point 2). Point 2 was a low risk selling opportunity. In July (point 3), gold prices dropped well below the starc-band, but instead of declining further, prices moved sideways for the next 12 weeks. Gold prices then started to move lower from November to December 1997 and touched the starc- band three times (points 4). In all instances prices did stabilize or move higher for 1-2 weeks. These bands work well in all time frames even as short as 5 to 10 minute bar charts. Starc bands can help the trader avoid chasing the market, which almost always results in a poor entry price.
The Kellner channels were originally developed by Chester Keltner in his 1960 book How to Make Money in Commodities. Linda Raschke, a very successful commodity trader, has reintroduced them to technicians. In her modification, the bands are also based on the average true range (ATR), but the ATR is calculated over 10 periods. This ATR value is then doubled and added to a 20 period exponential moving average for the plus band and subtracted from it for the minus band.
The recommended use of the Keltner channels is much different from the starc bands. When prices close above the plus band, a positive signal is given as it indicates a breakout in upward volatility. Conversely, when prices close below the lower band, it is negative and indicates prices will move lower. In many respects, this is just a graphical representation of a four week channel breakout system discussed in Chapter 9.Figure A-6 is a daily chart of March 1998 copper futures. Prices closed below the minus band in late October 1997 at point 1. This indicated that prices should begin a new downtrend and copper prices dropped 16 cents in the next two months There were many other closes below the minus band during this period. Until prices close above the plus band, the negative signal will stay in effect. The second chart is March 1998 coffee prices (Figure A.7) and illustrates a positive signal at point 1. After two consecutive closes above the plus band, prices then declined to the 20 period EMA. In a rising market the 20 period EMA should act as support. Several days after the EMA was touched (point 2), coffee prices began a dramatic 30 cent rise in just a few weeks.
Both of these techniques offer an alternative approach to either percentage envelopes or standard deviation bands (like Bollinger Bands). Neither is presented as a stand-alone trading system but should be considered as additional tools of the trade.
FORMULA FOR DEMAND INDEX
The Demand Index (DI) calculates two values, Buying Pressure (BP) and Selling Pressure (SP), and then takes a ratio of the two. DI is BP/SP. There are some slight variations in the formula. Here's one version:
If prices rise:
BP = V or Volume
SP = V/P where P is the % change in price
If prices decline:
BP = V/P where P is the % change in price SP = V or Volume
Because P is a decimal (less than 1), P is modified by multiplying it by the constant K.
P = P(K)
K = (3 x C)/VA
Where C is the closing price and VA (Volatility Average) is the 10 day average of a two day price range (highest high — lowest low).
If BP > SP then DI = SP/BPThe Demand Index is included on the MetaStock charting menu
This appendix introduces several more advanced technical methods that can be used by themselves or with other technical studies. As with any technical approach, it is always recommended that investors do their own independent testing and research before actually investing.
DEMAND INDEX (DI)
Most technicians will agree that volume analysis is an important ingredient in determining a market's direction. The Demand Index (DI) is one of the early volume indicators that was developed in the 1970s by James Sibbett. The formula is quite complex (see end of this appendix). The Demand Index is the ratio of buying pres‑sure to selling pressure. When the buying pressure is greater than the selling pressure, the DI is above the zero line, which is positive. Greater selling pressure means the DI is below zero, which implies prices will move lower. Most traders also look for divergences between the DI and prices.
Figure A.1 is a weekly chart of T-Bond futures from early 1994 until late 1997. From April to November 1994, the DI was mostly below the zero line as bonds declined from 104 to the 96 area. While prices made lower lows (line A), the DI formed higher lows (line B). This is a classic positive, or bullish divergence, which suggested that bond prices were bottoming. The divergence was confirmed when the DI moved above the zero line at point 1. The DI reached its highest level for this rally in late May 1995 at point 2, and then dropped for the next six weeks before crossing below the zero line at point 3. It stayed negative for five weeks before it again turned positive. On the next rally the DI formed a significantly lower high in late November at point 4. While the DI was lower (line D), the bond contract was almost six points higher (line C). This negative or bearish divergence warned of a price peak.This indicator can also be used with stocks. The weekly chart of General Motors (Figure A.2) shows the DI plotted as a line rather than a histogram. This allows for trendlines to more easily be drawn on the indicator. I have personally found trend-line analysis of indicators to be quite valuable. Indicator trend-lines are often broken ahead of price trendlines. This was the case in late 1995 as the downtrend in the DI (line A) was broken a week before the corresponding price downtrend (line B). As this chart indicates, buying just one week earlier could have significantly improved the entry price. The DI also warned of a price high in mid-April 1996. While GM was making a new price high (line C), the DI had formed lower highs (line D). This warning signal came well ahead of the serious price decline in June and July.
HERRICK PAYOFF INDEX (HPI)
This indicator was developed by the late John Herrick as a way of analyzing commodity futures through changes in the open interest. As discussed in Chapter 7, changes in the open interest can give traders important clues as to whether a market trend is well supported or not.
The Herrick Payoff Index uses price, volume, and open interest to determine money flow into or out of a given commodity. This helps the trader spot divergences between the price action and the open interest. This is often quite important as buying or selling panics can often be identified through analysis of the open interest by the Herrick Payoff Index.
The most basic interpretation of the HPI is whether it is above or below the zero line. A positive value means that the HPI is projecting higher prices and that open interest is rising along with prices. Conversely, negative readings suggest that funds are flowing out of the commodity being analyzed.
One of the more volatile commodity markets is coffee, featured in Figure A.3. During March and April of 1997, the HPI had four crossings of the zero line with the last positive signal in early April (B) lasting until early June. The HPI dropped below zero in June, and even though prices were well below the highs, coffee dropped another 70 cents. Once again the HPI turned positive in late July very close to the lows. Over the next two months there were two short term signals and then another longer term sell signal. This is characteristic of the HPI when used on the daily data as it will cross above and below the zero line several times before a longer lasting buy or sell signal is given.The HPI, like the Demand Index, is most effective when used on the weekly data, as fewer false signals are evident. Divergence analysis can also be used to warn the trader of a change from positive to negative money flow. There are several good examples on the weekly T-Bond futures charts (Figure A.4) that covers approximately six years of trading. The HPI stayed positive from late 1992 until late 1993. The HPI peaked in early 1993 and, when bonds were almost 10 points higher (line A), the HPI was forming a lower high (line B). This negative divergence warned bond traders of the decline in prices that took place in 1994. The HPI violated the zero line in late October of 1993, but then turned slightly positive in early 1994 before plunging back below the zero line. The HPI reached its lowest
level in the first half of 1994 and bottomed well ahead of prices. As prices were making lower lows (line C), the HPI was forming higher lows and therefore a positive divergence (line D). The HPI moved back into positive territory in December 1994 as bonds were very close to their lows. A negative divergence was formed in late 1995 (line F), after bonds had rallied over 25 points from the late 1994 lows. The zero line was crossed several times in 1996 and early 1997 before the HPI moved firmly into positive territory. These two examples should illustrate why the HPI and its analysis of open interest can be helpful in analyzing a commodity market's direction.
STARC BANDS AND KELTNER CHANNELS
As discussed in Chapter 9, banding techniques have been used for many years. Two types that I prefer are based on the Average True Range. Despite this common factor, these two types of bands are used in very different ways. Average True Range is the average of true price ranges over x periods. True Range is the greatest distance from today's high to low, yesterday's close to today's high, or yesterday's close to today's low. See Welles Wilder's New Concepts in Technical Trading Systems.
Manning Stoller, a well known expert in the commodity business, developed the Stoller Average Range Channels or starc bands. In his formula the 15 period Average True Range is doubled and added to or subtracted from a 6 period moving average (MA). The upper band is starc+; the lower is starc-. Movement outside of these bands is uncommon and indicates an extreme situation. In this manner they can be used as trading filters. When prices are near or above the starc+ band, it is a high risk time to buy and a low risk time to sell. Conversely, if prices are at or below the starc- band, then it is a high risk selling zone and a more favorable point to buy.
The weekly continuation chart of gold futures (Figure A.5) is plotted with both the starc+ and starc- bands. In Feb. 1997 at point 1, gold prices slightly overshot the starc- band. Though the price action was weak, the starc bands indicated that this was not a good time to sell. By waiting, a better selling opportunity was likely to occur. Just three weeks later gold was $22 higher and at the starc+ band (point 2). Point 2 was a low risk selling opportunity. In July (point 3), gold prices dropped well below the starc-band, but instead of declining further, prices moved sideways for the next 12 weeks. Gold prices then started to move lower from November to December 1997 and touched the starc- band three times (points 4). In all instances prices did stabilize or move higher for 1-2 weeks. These bands work well in all time frames even as short as 5 to 10 minute bar charts. Starc bands can help the trader avoid chasing the market, which almost always results in a poor entry price.
The Kellner channels were originally developed by Chester Keltner in his 1960 book How to Make Money in Commodities. Linda Raschke, a very successful commodity trader, has reintroduced them to technicians. In her modification, the bands are also based on the average true range (ATR), but the ATR is calculated over 10 periods. This ATR value is then doubled and added to a 20 period exponential moving average for the plus band and subtracted from it for the minus band.
The recommended use of the Keltner channels is much different from the starc bands. When prices close above the plus band, a positive signal is given as it indicates a breakout in upward volatility. Conversely, when prices close below the lower band, it is negative and indicates prices will move lower. In many respects, this is just a graphical representation of a four week channel breakout system discussed in Chapter 9.Figure A-6 is a daily chart of March 1998 copper futures. Prices closed below the minus band in late October 1997 at point 1. This indicated that prices should begin a new downtrend and copper prices dropped 16 cents in the next two months There were many other closes below the minus band during this period. Until prices close above the plus band, the negative signal will stay in effect. The second chart is March 1998 coffee prices (Figure A.7) and illustrates a positive signal at point 1. After two consecutive closes above the plus band, prices then declined to the 20 period EMA. In a rising market the 20 period EMA should act as support. Several days after the EMA was touched (point 2), coffee prices began a dramatic 30 cent rise in just a few weeks.
Both of these techniques offer an alternative approach to either percentage envelopes or standard deviation bands (like Bollinger Bands). Neither is presented as a stand-alone trading system but should be considered as additional tools of the trade.
FORMULA FOR DEMAND INDEX
The Demand Index (DI) calculates two values, Buying Pressure (BP) and Selling Pressure (SP), and then takes a ratio of the two. DI is BP/SP. There are some slight variations in the formula. Here's one version:
If prices rise:
BP = V or Volume
SP = V/P where P is the % change in price
If prices decline:
BP = V/P where P is the % change in price SP = V or Volume
Because P is a decimal (less than 1), P is modified by multiplying it by the constant K.
P = P(K)
K = (3 x C)/VA
Where C is the closing price and VA (Volatility Average) is the 10 day average of a two day price range (highest high — lowest low).
If BP > SP then DI = SP/BPThe Demand Index is included on the MetaStock charting menu
Comment Form under post in blogger/blogspot