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The Keltner Channel was developed by Chester W. Keltner for the purpose of determining market momentum. This type of technical indicator is considered an envelope indicator and is in many respects similar to the Bollinger Bands. A Keltner Channel has three measurement bands; where the one in the middle represents the ten-day high, low and closing prices moving average for a particular asset.

We arrive at the high and low bands by solving the ten-day moving average of the difference between the high and low closing prices. We then should add to subtract this value from the middle band.

Theoretically though, asset prices should found somewhere in between the high and low bands 96% of the time. The remainder, which is only about 5%, can serve as a strong indicator that prices are gaining momentum in either direction.

Interpretation of the Keltner Channel though can be pretty straightforward: buy when the price is greater than the high band and sell when the price falls beneath the low band.

If a trader follows this advice, he would be expecting the price trend to continue for some time in a particular direction. By following this advice, a trader would be counting on the trend in price continuing for some time in the given direction. However, another method of interpreting the Keltner Channel advises the very opposite: buy when the price falls out of the Channel, and sell when the price surges over the channel. This interpretation would be dependent on an asset’s high momentum, which means that the asset is either overbought or oversold. These are situations which would render the price at the mercy of rapid turnarounds.

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In technical analysis, Ichimoku Kinko Hyo is utilized as an equilibrium chart. The chart was created by a Japanese named Goichi Hosada. The name of the chart roughly translates to “equilibrium at a glance,” aptly describing its function as it provides information regarding the equilibrium behavior of a particular asset by taking only a single glance at the chart. Although the chart did not become popular in the West until the 1990s, it has been in use in Japan since 1968.

There are five lines in Ichimoku Kinko Hyo, namely:

• Tenkan-sen - this averages the highest high and lowest low and is calculation is arrived at in a fairly short time period, i.e. 7 to 9.
• Kijun-sen - this utilizes a similar equation; however this is calculated over 22 periods;
• Chikou Span plots the current closing price a full twenty-two periods behind.
• Senkou Span A averages Tenkan-sen and Kijun-sen, and a 26 periods plot ahead.
• Senkou Span B takes the highest high and lowest low and averages them over the last 44 periods. This is plotted ahead by 22 periods. The space between Senkou Spans A and B is known as the Kumo.

Traders utilize Ichimoku Kinko Hyo to get different signals for market behavior, judging by the interaction of the chart’s lines with the Kumo. By reason of the chart’s comprehensiveness, traders rely on it, being a powerful technical analysis tool.

However, as a forex trader, be warned that its use in forex has some drawbacks, since the market never closes - no close prices therefore are generated - and renders the Chikou span difficult to plot under the situation. You need therefore to exercise good judgment in deciding from which time periods the chart should be created as well as which price should be chosen as close price for the market.

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One the most fundamental technical analysis tools is the moving average. There are a couple of most popular kinds of moving average: the simple moving average; and the exponential moving average. We can solve for the SMA by averaging market prices within a certain time period. We can take as an example, the 20-day moving average that would, during the first 20 market days, average the levels of prices.

On the next day, the SMA would now have the 21st day of the market, excluding the first day. All SMA values are drawn on a chart, and can be a pretty good indicator of the overall price behavior. The more the SMA take periods into account, the less market fluctuations behavior will be reflected by the SMA, hence the smoother will be the data.

Another type of moving average, the exponential moving average or EMA is more complicated. However, it can be calculated by taking the difference between the current price and the former EMA. This value then is multiplied by a set percentage. This set percentage is usually dependent on the number of periods that were considered. The number that results is added to the earlier value of the EMA. Unlike the SMA, the EMA will not remove previous price levels, and will continue to be included when calculating, and for that reason is considered a bit more responsive at reflecting the price’s minor fluctuations.

All in all Moving averages can be an effective tool in getting the big picture regarding a particular asset’s price behavior. They can also be utilized as variables for a number of fairly complicated technical analysis tools and charts.

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The disparity index is a measure of the percentage position of the current closing price of a particular asset in relation to the moving average of that asset. Traders oftentimes attribute this measurement to Steve Nison who wrote the book “Beyond Candlesticks.”

The disparity index can have either a positive or a negative value. When the value is positive, this means that the price of the asset price is surging rapidly, whereas a negative value means that the price is declining rapidly. A value of zero indicates that the asset’s price at the moment is exactly in line with its moving average.

The disparity index when it crosses the zero line indicates a very rapid change in the trend of the asset in question. It is therefore a reliable early-warning indicator of the increasing momentum of the asset.

Considering that overbought and oversold assets are very susceptible to rapid reversals of prices, the disparity index is an excellent indicator as to when following the trend of a given asset might prove a dangerous proposition.

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The directional movement index (or DMI) is a technical analysis tool developed by J. Welles Wilder for the purpose of finding the general direction of a particular asset’s prices. DMI is made up of a couple of lines, the positive direction (+DI) line and the negative direction (-DI) line.

To solve for the DMI, one must calculate first the difference between the current high and the former high (HiDiff), this should also include the difference between the former low and the present low (LowDiff). Next we should compare HiDiff and LowDiff.

If HiDiff’s value is greater, a variable +DMI is set to HiDiff while that of -DMI is set to 0. If LowDiff is larger, -DMI is set to LowDiff and +DMI, to 0. If the two are of equal values, or if no trend can be seen in either highs or lows, the values of both variables are simply assigned a 0.

Next we will utilize a calculation method known as the Welles Summation. This is calculation is done on both +DMI and -DMI. This will produce two values represented by +DI and -DI, both ranging from 0 to 100. These two points then make up the directional movement index.

The DMI can be utilized in strongly trending markets to find out the strength of the buy and sell signals. The DMI will produce a strong buy signal when +DI surges above -DI at any point. Conversely, it generates a strong sell signal when +DI falls beneath -DI at any point. This indicator becomes less useful however In non-trending markets.

The DMI is the basis for the average directional index (ADX).

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As the name of this measure indicates, the Detrended Price Oscillator, is a tool for technical analysis that is geared to give information about the price of a certain asset without taking into consideration existing price trends. The rationale behind this principle is that detrended prices can be utilized by traders to give them knowledge about the buy and sell pressure exerted in a particular market on the bases of short-term fluctuations in the asset’s price, without taking considering larger upswings or downswings in the asset’s price.

The Detrended Price Oscillator is solved by declaring a time period indicative of a trend in price. Divide this period by two and add one to arrive at a number n. Next, you need to take the price of asset’s moving average n days before the said period, and subtract this from the closing price of that asset for the period. This calculation will result in the period’s DPO. This method of calculation will ensure that although a DPO chart will include short-term price trends, those with longer-terms are excluded.

One of the basic assumptions of the DPO is that long-term price trends are made up of short-term price trends, and that you can only understand long term trends by studying short-term trends.

By this reasoning, severe peaks and troughs in the DPO that really stand out tend to mean that there will likely be reversals in the overall trend of the price of an asset, and traders therefore should position themselves appropriately if they were to benefit from these reversals in either direction.

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In the technical analysis arena, we can make use of the DeMarker indicator for indentifying high-risk buying or selling areas within a particular market.

A couple of variants of the Demarker Indicator exist, one has a value ranging from -100 to 100, while the other’s value ranges from 0 to 1. The basic principle governing the Indicator is the equal in either case. If the high price for a particular period is more than the high during that of the previous period, the DeMax variable for that period is the difference between the highs; on the other hand, the DeMin variable for the period works in the same manner for the low prices. The Demarker Indicator is calculated as the moving average of DeMax divided by the total of the moving averages of DeMax and DeMin. The higher therefore the value of DeMax in relation to DeMin, the greater will be the value of the Demarker Indicator.

On the 0 to 1 scale of the Demarker Indicator, any value greater than .7 means that the price is likely to going to plunge, while a value that is anywhere lower than .3 means that the price will soon surge. Values between .3 and .7 mean that periods for entering a given asset market would be rendered relatively low-risk.

The usefulness therefore of the Demarker Indicator lies in determining when to enter a market, or when to buy or sell an asset in order to take advantage of probable price trends.

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The Commodity Channel Index is a tool for measuring the point at which cyclical price reversals for a particular asset can be expected. Among the primary assumptions behind the CCI is that price trends will tend to reverse at regular intervals within a particular asset. This will allow investors to take the correct action when the CCI indicates that one of those cyclical reversals is bound to occur.

The CCI is first calculated by averaging the high, low and closing prices into a measure coined as the True Price, or TP. A 20-period moving average of the TP will then become the Simple Moving Average of the True Price, or SMATP. A standard deviation of the difference between SMATP and TP over twenty periods will also be taken. The difference then between TP and SMATP will then be divided by the product of this standard deviation and 0.15, which is a constant value, in order to produce the CCI.

By utilizing the constant the .015 constant value will make sure that that most of CCI values will be within 100 and -100. In case the CCI’s absolute value will be greater than 100, Lambert’s theory indicates that the market is nearing one of its cyclical reversals, and that traders should take an action that is appropriate. The CCI will also help determine overbought and oversold levels, which are any levels where the absolute value is more than 100. If the CCI goes beyond the -100 to 100 boundary range and then returns, what is generated here can either be a buy or sell signal, depending on whether the CCI was less than -100 (oversold) or greater than 100 (overbought).

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Developed by Marc Chaikin, the Chaikin Oscillator’s purpose was to compare an asset’s volume and price levels. The Oscillator is useful in determining whether an asset is overbought or oversold and as well as in indicating upcoming reversals.

To solve for a Chaikin Oscillator chart, the first thing a trader should do is create an Accumulation/Distribution Line or A/D line for a particular asset. The A/D line is taken from an index called the close location value, or CLV, the purpose of which is to compare high, low as well as close prices.

If the close price is greater than the midpoint of the high-low range, the CLV will have a positive value; on the other hand we will have a negative value for the CLV if the close price is less than the midpoint.

A cumulative total of the CLV multiplied by the volume of the asset will result in an A/D Line, which will be high when both volume and closing prices are high and low when volume and closing prices are low, as pressure is exerted in either direction on the asset.

The Chaikin Oscillator is a ten-period moving average of the price of a particular asset minus a three-day moving average of the recently-generated value of the A/D line.

When the value of the oscillator is high, the A/D line will be relatively low compared to the price of the asset. This indicates that the pressure to sell is increasing and that a price reversal is about to happen. Conversely if the opposite occurs, there will be an increase in the buying pressure and a price increase will be unavoidable.

By utilizing the Oscillator, traders can determine the appropriate time to sell or buy and thus take advantage of the imminent reversal.

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As a techical indicator, the Camarilla Equation is popular as a day trading tool. The principle behind this equation is the concept that market trends will have a tendency of reverting to a mean overtime.

The Camarilla equation takes four arguments of variables from the previous trading day. These variables are the market opening, market closing, high and low.

The equation generates eight price levels based on these aforementioned variables. The lowest four are called the “support” levels and are labeled L1 to L4. The highest four are termed “resistance” levels with labels H1 to H4. These levels indicate the points at which a reverse toward the mean is likely to take place on a particular trading day.

Of all the levels the equation generates, levels L3 and H3 are the most important. At L3, the is a strong market support that suggests that there will be a reversal towards a price increase. H3 indicats a strong market resistance meaning there will be a reversal to lower prices.

On the other hand, L4 and H4 are called “breakout” levels. This means that if market prices reach beyond these levels, indicating that this breakout trend will be sustained for a considerable period of time.

Due to the fact that the Camarilla Equation is a guarded knowledge, there are several different versions, by reason of its “secret” nature, of this equation, which further differ in accuracy as well as complexity.