Kaufman adaptive moving average

Kaufman adaptive moving averageKaufman Adaptive Moving Average | Trading Strategy (Setup & Filter)

I. Trading Strategy

Developer: Perry Kaufman (Kaufman Adaptive Moving Average KAMA). Source: Kaufman, P. J. (1995). Smarter Trading. Improving Performance in Changing Markets. New York: McGraw-Hill, Inc. Concept: Trading strategy based on an adaptive noise filter. Research Goal: Performance verification of the setup and filter. Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: The Adaptive Moving Average (AMA) turns up. Short Trades: The Adaptive Moving Average turns down. Note: The AMA trendline appears to stop when markets have no direction. When markets trend, the AMA trendline catches up. Trade Entry: Long Trades: A buy at the close is placed after a bullish setup. Short Trades: A sell at the close is placed after a bearish setup. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 32 years since 1980. Testing Platform: MATLAB®.

II. Sensitivity Test

ER_Length = [2, 100], Step = 2;

Kaufman Adaptive Moving Average | Trading Strategy (Setup)

I. Trading Strategy

Developer: Perry Kaufman (Kaufman Adaptive Moving Average KAMA). Source: Kaufman, P. J. (1995). Smarter Trading. Improving Performance in Changing Markets. New York: McGraw-Hill, Inc. Concept: Trading strategy based on an adaptive noise filter. Research Goal: Performance verification of the setup. Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: The Adaptive Moving Average (AMA) turns up. Short Trades: The Adaptive Moving Average turns down. Note: The AMA trendline appears to stop when markets have no direction. When markets trend, the AMA trendline catches up. Trade Entry: Long Trades: A buy at the close is placed after a bullish setup. Short Trades: A sell at the close is placed after a bearish setup. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 32 years since 1980. Testing Platform: MATLAB®.

II. Sensitivity Test

ER_Length = [2, 100], Step = 2;

FastMA_Length = [2, 28], Step = 1;

Combined donchian channels

Combined donchian channelsCombined Donchian Channels | Trading Strategy (Entry & Exit)

I. Trading Strategy

Developer: Richard D. Donchian. Concept: Trading strategy based on Donchian Channels. Research Goal: Performance verification of the channel entry and trailing exit. Specification: Table 1. Results: Figure 1-2. Trade Entry: Long Trades: A buy stop is placed one tick above the Donchian Channel (i. e. UpperChannelOne[i ? 1]). Short Trades: A sell stop is placed one tick below the Donchian Channel (i. e. LowerChannelOne[i ? 1]). Index: i

Current Bar. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 32 years since 1980. Testing Platform: MATLAB®.

II. Sensitivity Test

UpperChannelOne(Channel#1) is the highest high over a period of Channel#1. LowerChannelOne(Channel#1) is the lowest low over a period of Channel#1.

Keltner channels-3-phase model

Keltner channels-3-phase modelKeltner Channels 3-Phase Model | Trading Strategy (Setup)

I. Trading Strategy

Developer: Chester W. Keltner. Concept: Trend-following based on Keltner Channels. Research Goal: Performance verification of the 3-phase model (long/short/neutral). Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: Close[i ? 1] > Buy_Line[i ? 1]. Short Trades: Close[i ? 1] < Sell_Line[i ? 1]. Index: i

Current Bar. Trade Entry: Long Trades: A buy at open is placed after a bullish Setup. Short Trades: A sell at open is placed after a bearish Setup. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 33 years since 1980. Testing Platform: MATLAB®.

II. Sensitivity Test

Auxiliary Variables:

Typical_Price[i] = (High[i] + Low[i] + Close[i]) / 3

Keltner channels-2-phase model

Keltner channels-2-phase modelKeltner Channels 2-Phase Model | Trading Strategy (Setup)

I. Trading Strategy

Developer: Chester W. Keltner. Concept: Trend-following based on Keltner Channels. Research Goal: Performance verification of the 2-phase model (long/short). Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: Close[i ? 1] > Buy_Line[i ? 1]. Short Trades: Close[i ? 1] < Sell_Line[i ? 1]. Index: i

Current Bar. Trade Entry: Long Trades: A buy at open is placed after a bullish Setup. Short Trades: A sell at open is placed after a bearish Setup. Trade Exit: Table 1. Portfolio: 42 futures markets from four major market sectors (commodities, currencies, interest rates, and equity indexes). Data: 33 years since 1980. Testing Platform: MATLAB®.

II. Sensitivity Test

Auxiliary Variables:

Typical_Price[i] = (High[i] + Low[i] + Close[i]) / 3

Online trading concepts

Online trading conceptsTuesday, March 2, 2010

Adaptive Moving Average

Adaptive Moving Averages changes its sensitivity to price fluctuations. The Adaptive Moving Average becomes more sensitive during periods when price is moving in a certain direction and becomes less sensitive to price movement when price is volatile .

The chart below of the E-mini Nasdaq 100 Futures contract shows the difference between an Exponential Moving Average which weights current prices more heavily than past prices and the Adaptive Moving Average which changes sensitivity based on price volatility:

The advantage of the Adaptive Moving Average is show above in the e-mini chart in the center where price became directionless and choppy. During that period the Adaptive Moving Average maintained a straight line appearance; whereas, the Exponential Moving Average moved with the choppiness of prices. However, when price trended, like on the far right of the e-mini chart above, the Adaptive Moving Average kept up with the Exponential Moving Average.

The Adaptive Moving Average is definitely an unique technical indicator that is worth further investigation.

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Aaron, Texas, USA

I have taken both the emini & forex courses offered by Trading Concepts.

I believe Todd Mitchell to be sincere in his enthusiasm for teaching trading. I absolutely do NOT believe this to be a scam.

I never had much luck trading the emini. It always resulted in losses for me. Perhaps the course is a bit too complicated, involving many extraneous (aside from the price action & the market) factors like NYSE tick and time of day. At times, I placed too much emphasis on these & wound up in some bad trades as a result.

The forex stuff was much simpler, however, and I found by limiting my practice to a portion of what was taught, I traded euro futures quite profitably. I generally limited things to momentum setups and price action. I never traded based on trend alone, though he counselled doing that some times.

I absolutely disagree with those who state the teachings involve ridiculous risk-reward. Yes, that may be true when you enter a trade, but if you religiously follow the risk reduction he teaches, if you aren't knocked out of a trade immediately, the trade rapidly will become low or no risk almost without fail.

In summary, whether you trade eminis or prefer forex/currency futures as I do, there are concepts in the course you will find invaluable in your trading and I highly recommend the course.

Adaptive portfolio trading strategy implementation

Adaptive portfolio trading strategy implementationadaptive portfolio trading strategy implementation

New Member

Hi everyone, I'm new here and getting my first post in with a problem.

This is mainly a learning exercise for myself. Basicly the algo applies an eigenvalue filter to identify if the market is good to trade on. I have implemented this part, and am up to 2c) in the algo as identified in the paper.

Im struggling to get my head around the state vectors and there uses. If i write out how I interpret the steps, I would be beyond grateful if somebody with a bit more experience could point out if I am wrong! I understand that this would probably not be the exact implementation (you could calculate some things at different times to make things more seamless im sure).

2c) find the various moments of the vector of returns for each asset. the return vector is the form r(1) = return at t-tau+1, r(2) = return at t-tau+2 etc. so this step would give a single mean value for each moment and asset. where t is the most recent time, and the return is that given by the return matrix.

2d) average each moment for all assetts. so this gives four values, the mean return, variance, scew and kurt over the past tau days.

2e) calculate again, but rather than t as the latest time, repeat this for all values of t from tau+2 to latest-1. use all previous values to find the percentile each moment sits in (high, mid, low). For simplicity, state low would 1, mid 2 etc.

then save the average of each moment in a state vector, so a high mean, low var, med scew, med kurt would be added to the vector denoted by 3,1,2,2.

2f) for the most recent stats calculated in d), find the percentile of each one using all values calculated in e), and calculate the state vector for the most recent readings. for example, the latest one may be 1,2,3,2.

2g) go into the vector 1,2,3,2 which was created by calculating 2e). If this is blank invest in risk free, and add the current readings. if this has several values, eg. the mean returns are 0.5 1 0.5 2, and variances 2,2,2,2, average each moment, and then calculate mean over variance and apply the rules to make a decision of investment. so in this example it would be 1/2, meaning invest in risk free.

Im not 100% sure where the logaritihmic return kv is used, if anybody knows I would be most grateful!

I hope that was clear, please ask if anything isnt!

Forex quantitative analysis

Forex quantitative analysisQuantitative Analysis: Price Channels

One of their major strength is their ability to use both price action and volatility. Price bands or channels are trading indicators composed of two lines. The upper line is a sort of resistance line (Area of abundant supply) while the lower line is a sort of support line (Area of strong demand).

Over years, technical analysts have developed several price channel indicators; some of these include the Bollinger bands, Donchian channels, Keltner Channels, Volatility Channels, Standard Error Bands, Adaptive Price Channel and Moving Average Envelopes.

Bollinger Bands

Probably, Bollinger bands is the most popular one. Its middle line is simply a moving average.

By calculating the standard deviation of past prices and adding/subtracting it to the middle line, we can build the upper/lower line of the Bollinger bands.

Bollinger bands indicator is built-in QuantShare. Here is how to reference this indicator in QS language:

Upper Line:

BBandsUpper(20, 2, _masma)

The above line creates the upper band by adding 2 standard deviations to the 20-bar simple moving average.

Lower Line:

BBandsLower(20, 2, _masma)

Donchian Channels

Donchian boundaries are based on high and low of previous N-Periods.

Keltner boundaries are set around a moving average. It is based on the average true range or the high/low range.

Volatility Channels

The volatility channels use the highest and lowest previous values to determine the upper and lower lines.

The indicator can be downloaded here: Volatility Channels Indicator

Upper Line:

VolatilityChannels(20, 0)

Lower Line:

VolatilityChannels(20, 1)

Standard Error Bands

This price channel indicator is based on the alpha and beta coefficients of the linear regression of the past N-prices.

The indicator can be downloaded here: Standard Error Bands

It also requires the following functions: calcA and calcB.

Adaptive Price Channel

The adaptive price channel uses the highest high and lower low values of the price series over a non-fixed lookback period. The lookback period follows changes of the 30-bar standard deviation of the close series.

Quantitative trading analysis using R

Several techniques are available for navigating the financial markets. Technical analysis, which mainly centers on price patterns and trends to project price action, is the basis that most traders use to place trades. And, an example of technical analysis that is growing in popularity is quantitative trading analysis. It refers to a method of trading that employs supercomputer analysis as well as complicated algorithms to hunt out profitable yields in the market. A common tool used in carrying out quantitative trading analysis is the R programming language .

Initially designed by Ross Ihaka and Robert Gentleman at the University of Auckland, R refers to a functional language for statistical computation and graphics. R can be said to be an open source implementation of the S language, which was developed by AT&T, and has been a major milestone in how people interpret financial data. Notably, under the GNU General Public License, R has been made available to the public free of charge and it can be customized easily to reflect the needs of the user. The language can be downloaded at r-project/ and it has versions for various operating systems.

The R programming language has greatly borrowed from the S-Plus language. The syntax of the two languages is considered to be closely related. Some notable features of R include availability of built-in tools for time series, regression etc, collection of intermediate tools for data analysis, efficient data handling capabilities, ease of production of properly-designed publication-quality plots, and enhanced graphing and visualization capacities.

It is important to note that R is a rich and a well-suited language for carrying out quantitative trading analysis in the financial markets. When used properly, it’s a valuable strategy one can use for making decisions on whether to enter or exit the market. And, a common way of using R in quantitative trading is for momentum identification. This technique looks for momentum in financial data, aiming to identify trends or hidden relationships, to forecast price action. The markets usually form trends that last for an extended period of time. Traders using R may employ the strategy with the aim of discovering possible trends in the market.

Quantitative trading analysis using R is not as complicated as it may seem. The infrastructural design for the language has already been done for the user. Therefore, this enables the users to concentrate on what they are trying to achieve instead of focusing on the nitty-gritty of how to realize it. More over, its user-friendliness and price are very essential elements to the investment industry in the current price-conscious world. Lastly, R is designed such that it can be extended for specific uses. Importantly, there is ready assistance from the R community through discussion forums, mailing lists, and other means.

The benefits of R are making an increasing number of traders to start using it for quantitative trading. Most of all, it is loved for its open source nature and the community around it that is dedicated at ensuring the problems of its members are amicably addressed. R has a very big contributor base, which also continues to grow day after day. More so, novel add-on packages are being created on a constant basis to increase the user-experience of its practitioners. As such, the use of R for generating trading signals will continue even in the coming years.

Here is a simple example that can be used for merging two trade series using different securities. Note that this aims to result in a derived time series. And, the spread between the two financial instruments is more than 0.5.

xy .5, "y"]

Although this may be difficult to grasp for those seeing it for the first time, members of the R community undertaking time series analysis see it as bread and butter.

In conclusion, quantitative trading analysis using R is easy to use and it’s a very good method for identifying trade opportunities in the financial markets. R has an extensive supporting community that is always willing to address the problems of its members. More over, using it does not increase expenses in terms of product licensing or proprietary language expertise. R deviates from the complexity of analysis present in the current world of investment. Therefore, it is an innovative tool that makes quantitative analysis easier rather than harder.

Forex tsd elite indicators free download

Forex tsd elite indicators free downloadForex TSD Elite Indicators Free Download

Here, I am going to share Forex tsd elite and advanced sections indicator . Jurik filter simple 1 indicator was programmed for Innovative Top level area of the community. It was some strong research done about Jurik filter signal. Some research was created for the signal created in different ways:

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As a results of this evaluation – the JMA signal as unique work/calculation/coding (adapting flexible calculation) was created which is solving the crucial mistakes for the last 2 signals. We can see the differences:

Pivot oscillator signal was designed for elite area. We can choose which stages we want to show with Rotate Stage choice. Stage 1 reveals Rotate, S1 and R1. Stage 2 reveals Rotate S1, S2, R1 and R2. Stage 3 reveals Rotate S1, S2, S3, R1, R2 and R3. Also, we can use any period of your efforts and time (so it is not restricted to time supports you need) and we can place several oscillators on graph.

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Alpha20tm trading system

Alpha20tm trading systemALPHA 20 TM Trading System

ALPHA 20 TM is a proprietary trading system using fractals. The trading system has a self-adaptive design that does not use classical technical analysis tools such as moving averages, volatility bands, or price derivatives. ALPHA 20 TM is price-driven, since price will eventually reflect all relevant fundamental, political, and psychological factors. All rules are disclosed and verifiable.

Systematic traders can customize parameters and benefit from system robustness. ALPHA 20 TM was tested on multiple time frames with risk-neutral, risk-seeking, and risk-avoiding exit strategies. Trading rules and parameters are same for all markets.

The instructional manual includes trading philosophy, trading rules, entry-exit examples, risk management rules, sensitivity tests, and benchmark tests. The research modules are part of the premium package .

Robust design

Self-adaptive algorithm

Same parameters for all markets

Same parameters for all time frames

Simple trading logic

For more information regarding pricing and performance please contact us .

A3step trading plan for channel breakouts

A3step trading plan for channel breakoutsA 3 Step Trading Plan for Channel Breakouts

Talking Points:

First find the trend to determine the trend Learn to enter Forex breakouts using Donchian Channels. Channels can be used to trail your stop and lock in profit.

The Forex market is known for its strong trends, which can make trading breakouts of support and resistance levels an effective approach to the markets. To plan for such market conditions. today we will review a three step breakout strategy using the Donchian Channels.

Lets get started!

Find the Trend

The first step to trend trading is to find the trend! There are many ways to identify the trends depicted below, but one of easiest is through the use of the 200 period MVA (Moving Average). To begin add this indicator to your chart, and then see if price is above or below the average. This is how we will determine the trend and our trading bias.

Given the information above, traders should look for opportunities to buy the EURJPY in its current uptrend as price is above the average. As well, the AUDNZD pictured below offers selling opportunities since the pair is priced under the 200 period MVA. Once we have this information, then we can plan entry placements for a potential breakout.

Learn Forex Daily Charts 200 MVA

(Created using FXCMs Marketscope 2.0 charts)

Trading Donchian Channels

Donchian Channels are a technical tool that can be applied to any chart. They are used to pinpoint current levels of support and resistance by identifying the high and low price on a graph, over the selected number of periods. For todays strategy we will be using 20 periods meaning that the channels will be used to identify the 20 day high and low in price.

Since the price of the EURJPY is trading above the 200 MVA, traders will want to identify new entries to buy the pair on a breakout towards higher highs. With our current 20 Day high identified by the Donchian Channels at 145.68 traders can set an entry to buy the EURJPY one pip above this value.

Now, lets look at how to enter into a sell position.

Learn Forex EURJPY Daily with Channels

(Created using FXCMs Marketscope 2.0 charts)

The process of initiating sell positions in a downtrend is exactly the opposite. Again, we will revisit the AUD/NZD Daily graph pictured below. As price is below the 200 MVA, traders will look to sell the pair in the event of price creating a new 20 Day low. Currently that low resides at .8775 and traders can look to initiate new sell positions under that value.

Learn Forex AUDNZD Daily with Channels

(Created using FXCMs Marketscope 2.0 charts)

Setting Risk Trailing Stops

When trading any strategy, setting stops and managing risk should be considered. When using Donchian Channels, this process can be simplified. Remember how our pricing channels (representing the 20 Day high or low), act as an area of support or resistance? In an uptrend, price is expected to move to higher highs and stay above this value. If price moves through the bottom channel, representing a new 20 Day low, traders will want to exit any long positions. Conversely in a downtrend, traders will want to place stops orders at the current 20 period high. This way, traders will exit any short positions upon the creation of a new high.

Traders may also use the Donchian Channels as a mechanism to trail their stop. As the trend continues, traders may move their stop along with the designated channel. Trailing a stop in this manner will allow you to update the stop with the position, and lock in profit as the trend continues.

Setting Up Channels

Donchian Channels are great tools for identifying potential breakout levels. However you will need to download them to add them inside of Marektscope 2.0 for the use of this strategy. For more information on downloading this FREEE Indicator and adding them to Marketscope 2.0, visit the FXCM APP Store linked HERE.

To contact Walker, email wenglandfxcm. Follow me on Twitter at WEnglandFX.

To be added to Walkers e-mail distribution list, CLICK HERE and enter in your email information

New to the FX market? Learn to trade like a professional with DailyFX!

Register HERE to start your Forex learning now!

mailto:wenglandfxcm

Free forex scalper ea

Free forex scalper eaAdaptive Scalper EA free download - forex trading strategies - expert for MetaTrader 4

Description:

Adaptive scalper ea is made according to the market conditions. it can adjust itself by all market conditoins and becoming most popular among the professional traders. it is used on almost all currency pairs but recommended in Eur/Usd, Gbp/Usd, on the time frame M15.

It is not a tick Scalper, all trades are opened on the bases of popular and conditonal indicators, Risk management is well managed by this indicator.

It should be used in low spread Brokers like exness, hot forex etc. it can be start as low as 100Usd. try the demo first..if u have VPS then it would be better. Good luck

Daytradeforex Free 5 Pip Scalping EA

Daytradeforex Free 5 Pip Scalping EA

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Tradestation technical indicator

Tradestation technical indicatorTradeStation Technical Indicator

The Squeeze Trading Station Technical Indicator

The Squeeze is a TradeStation technical indicator we will look at that I use for both day trading and swing trading. The Squeeze TradeStation technical indicator takes advantage of "quiet periods" in the market when the volatility has decreased significantly, and the market is building up energy for its next major move higher or lower. This TradeStation technical indicator was introduced to me by my trading partner, Hubert Senters, and it has become an integral part of my own trading plan.

For students of Bollinger Bands, periods of low volatility are identified as the times when the bands "move closer together." This is always great in hindsight, but in real time, how does a trader know that the current narrowness is really narrow enough to qualify as low volatility? This TradeStation technical indicator answers that question by adding in the Keltner Channels as well as a Momentum Index Oscillator.

For readers who are unaware of how these TradeStation technical indicators work, I'll take a few moments to explain them here. Bollinger Bands are a type of envelope that are plotted at standard deviation levels above and below a moving average. This produces an effect of having the bands widen during periods of higher volatility and contract during less volatile periods. During periods of lower volatility, in sideways moving markets, the bands contract toward the moving average. Keltner Channels are based on a standard Moving Average. The actual band lines are offset by a positive and negative standard deviation value from the central moving average value, to provide upper and lower bands. While the Bollinger Bands expand and contract as the markets alter between periods of high and low volatility, the Keltner Channels stay in more of a steady range. The Momentum Index is used to estimate the direction, velocity and turning points of market movements. Make sense? Ok let's look at how I use all of this for a TradeStation technical indicator set up.

The quiet periods I'm looking for are identified when the Bollinger Bands narrow in width to the point they are actually trading inside of the Keltner Channels. This marks a period of reduced volatility and signals that the market is taking a breather, building up steam for its next move. The TradeStation technical indicator signal occurs when the Bollinger Bands then move back outside the Keltner Channels. I use a TradeStation technical indicator 12 period Momentum Index Oscillator to determine whether to go long or short. If it is above zero when this happens, I go long, if it is below zero, I go short. These are all canned studies that come with most charting packages. On the TradeStation technical indicator for the parameters, I just use the default settings on TradeStation. These readings are 20 1.5 for the Keltner Channels and 20 2 for the Bollinger bands. I also took an extra step and turned all of these into an TradeStation technical indicator which makes it easier to read on the chart.

A basic breakout strategy for forex

A basic breakout strategy for forexA Basic Breakout Strategy For Forex

Talking Points:

Forex tips for finding support and resistance levels. Learn to enter Forex breakouts using Donchian Channels. Complete a breakout trading plan with stop orders.

The Forex market is known for its strong trends, which can make trading a breakout strategy an effective approach to the markets. Normally the first step of any breakout strategy is to identify the key levels of support and resistance for a currency pair. Today we are going to review using Donchian Channels for just that purpose, while complete a trading setup on the GBPUSD.

Lets get started!

Learn Forex GBPUSD Price Channels

(Created using FXCMs Marketscope 2.0 charts)

Trading Donchian Ch annels

Donchian Channels can be applied to any chart to extrapolate current levels of support and resistance. They do this by clearly identify the high and low on a graph created during the selected number of periods. Above we can see the Donchian Channels applied to a GBPUSD 4Hour chart, using a 20 period setting. The channel lines highlight the current 20 periods high and low values, which can be used as support and resistance when trading breakouts. Breakout traders in a downtrend will look for price to break below the lower channel prior to creating new entries in the direction of the trend. The same is true in an uptrend, where traders will identify the upper channel as a potential area to enter the market.

Since the price of the GBPUSD has declined as much as 346 pips for the month of October, many traders will want to identify new entries to sell the pair on a breakout towards lower lows. With our current low already identified by the Donchian Channels at 1.5913, traders can begin preparing for a breakout below this value. As pictured below, you can find a sample breakout setup. Entry orders to sell the GBPUSD can be placed at a minimum of one pip below support, so traders enter the market on a breakout to lower lows.

Learn Forex GBPUSD 4Hour Breakout

(Created using FXCMs Marketscope 2.0 charts)

Setting Risk

As with any strategy, breakout traders should incorporate stops into their trading. When using Donchian Channels, this process can be made very easy. Remember how the top pricing channel (representing the 20 period high), acts as an area of resistance? In a downtrend price is expected to make lower lows and stay below this value. If a new high is created, with a breach of the upper channel, traders will want to exit their positions. Traders may also want to manually tail and move their stop order to lock in profit as the trend continues. On trading tip breakout traders can employ is moving this preset stop along with the decreasing pricing channel as the trade moves in their favor.

Setting Up Channels

Donchian Channels are great tools for identifying potential breakout levels. However you will need to download them to add them inside of Marektscope 2.0. For more information on downloading this FREE Indicator and adding them to Marketscope 2.0, visit the FXCM APP Store linked HERE.

To contact Walker, email wenglandfxcm. Follow me on Twitter at WEnglandFX.

To be added to Walkers e-mail distribution list, CLICK HERE and enter in your email information

New to the FX market? Learn to trade like a professional with DailyFX!

Register HERE to start your Forex learning now!

DailyFX provides forex news and technical analysis on the trends that influence the global currency markets.

Keltner scalping trading system-forex strategies-forex resources-forex trading-free forex trad

Keltner scalping trading system-forex strategies-forex resources-forex trading-free forex tradKeltner Channels Scalping System

Keltner Channels with a 22 period moving average

MACD Histogram with 2 settings (5/34/5 25/170/25)

445 Period Exponential Moving Average

Stochastic Momentum (5,3) or Full Stochastics (5,3,3)

Trading Rules

By design this system is a scalping system but I also use it to capture much larger profits. The entry rules for both methods are identical. The difference lies in the exit method. For the scalping method I enter my target exit order immediately after I enter my protective stop. For the larger trend trades I use a combination of the Keltner Channel and the 89 period moving average to help stay in the trades for longer periods. That being said lets go over the entry and exit rules for the scalping system first.

Long Trades

1. Price is above or testing the 89 period moving average on the one minute chart.

2. Price is within the Keltner Channels or closely above or below it. * Important - If price is below the Keltner Channels wait for the next trade unless there is a very clear positive divergence between price and the MACD (5/34/5) or it is testing either one of the 89 or 445 period moving averages. If price bar body is overlapping the upper Keltner Channels it is probably still a safe play but stick to your stop rules. It is always best to wait for it to come back and test inside the Keltner Channels .

3. The MACD (5/34/5) Histogram is below zero

4. The Stochastic Momentum is approaching or below –40. For the highest probability trades wait for it to go below –40, however it will not always make it that far especially in strong trends.

5. The 1-period moving average of the MACD turns back up in the direction of the trend and crosses the 5-period moving average of MACD.

At this point you would go Long on the open of the next bar provided price is still within or very closely above or below the Keltner Channel and enter a maximum stop in one of 3 places.

1. One pip outside the lower Keltner Channel

2. 1 pip below the 89 or 445 period moving average if they are directly below the Keltner Channel

12-pips below the trade entry point. Never set your stop further than 12 pips away using this system and try to keep it tighter using the first two choices when possible. This will help you cut your losses short and stay in the game for a long time to come.

Short Trades

Conditions required for trade entry - in sequence:

1. Price is below or testing the 89 period moving average on the one minute chart.

2. Price is within the Keltner Channels or closely above or below it. * Important - If price is above the Keltner Channels wait for the next trade unless there is a very clear negative divergence between price and the MACD (5/34/5) or it is testing either one of the 89 or 445 period moving averages. If price bar body is overlapping the lower Keltner Channel it is probably still a safe play but stick to your stop rules. It is always best to wait for it to come back and test inside the Keltner Channel.

3. The MACD (5/34/5) Histogram is above zero.

4. The Stochastic Momentum is approaching or above +40. For the highest probability trades wait for it to go above +40, however it will not always make it that far especially in strong trends.

5. The 1-period moving average of the MACD turns back down in the direction of the trend and crosses the 5 period moving average of MACD.

At this point you would sell-short on the open of the next bar provided price is still within or very closely above or below the Keltner Channel and enter a maximum stop in one of 3 places.

1. One pips outside the upper Keltner Channel

2. 1 pips above the 89 or 445 period moving average if they are directly above the Keltner Channels

3. 12-pips above the trade entry point. Never set your stop further than 12 pips away using this system and try to keep it tighter using the first two choices when possible. This will help you cut your losses short and stay in the game for a long time to come.

6. For this Keltner channels scalping system your profit goals should be modest with and emphasis on making several quick and small trades. I usually set my scalp trade exit orders immediately after I enter my protective stop in order to eliminate most of the emotional tendencies that naturally occur when trading. I set my exit price between 6 and 12-pips below my entry price.

This moving average strategy beats buy and hold by nearly3-to-1

This moving average strategy beats buy and hold by nearly3-to-1This Moving Average Strategy Beats Buy and Hold by Nearly 3-to-1

Moving averages (MAs) are one of the most popular trading tools. Their popularity may be due to their simplicity. Before there were calculators or computers, a 10-day simple moving average could be found by adding up the last 10 closing prices and moving the decimal point one space to the left. Ive talked to old floor traders who told me that was the reason the 10-day moving average become popular.

Now, MAs of any length are easy to calculate and widely used. We also have variations of the simple calculation. Rather than just adding up numbers and dividing by the total number, there are at least four other possible ways to find a moving average:

1. Exponential Moving Average: Assigns a greater weight to the more recent market action in an effort to be more responsive to changes in the trend.

2. Weighted Moving Average: Allows users to decide which data should be overweighted and allows for the weighting values to be changed.

3. Triangular Moving Average: Weights the middle of the data more heavily.

4. Adaptive Moving Average: Uses smoothing factors to adjust the number of days used in the calculations to current market conditions.

Each method has its proponents and each of the four methods adds a level of complexity to what was originally a simple indicator. Complexity, at least in my mind, is only OK if it adds value. Visually, it looks like the different moving averages move in the same general direction.

The chart below is a weekly chart of the SPDR SP 500 ETF (NYSE: SPY ) with the prices hidden so all we see are the moving averages. This eliminates the clutter on the chart and makes it possible to see that the moving averages rise and fall at the same time.

The adaptive moving average, the thin red line, stands out as consistently lagging the simple MA, shown as the thick blue line. At the bottom in 2009, the exponential MA, the brown line, was the last to signal a buy. That signal came after SPY had gained more than 35%. The other MAs signaled a buy after a gain of 25%. Large delays at bottoms are one of the most significant drawbacks of trading with a moving average. The other significant drawback is that there are a large number of small trades in a sideways market.

Based on the visual comparison, we can say that the averages are all close to each other. More detailed quantitative testing of the various MAs is required to develop a stronger opinion as to which one is best. The results are summarized in the table below. All results are for a 26-week MA and the system is always in the market, long when the price is above the MA and short when the price is below the MA.

Each MA delivered a low number of winning trades and none beat the market. Digging deeper, we learn that the performance problems are due to large losses on the short side.

Looking at the results for a long-only MA system, moving to cash when the price falls below the MA, we see much better performance.

Although the number of winning trades is still low, the adaptive MA beats buy and hold by a significant amount, nearly 3-to-1. This indicator will not call the top of the market. In fact, because it is calculated with historical data, it is impossible for any MA to signal at the exact top or bottom.

At the time of this writing, SPY is well above its adaptive MA, and based on this indicator alone, a bull market would be intact as long as SPY remains above $141.36. Of course, the precise value of the MA changes daily, and will likely be higher when the next bear market does begin.

There is no way to fully eliminate the problems associated with moving averages. But in my experience, the best way to use them is to apply an adaptive MA as a long-only signal. No matter what type of MA is used, when the prices are below the MA, the chances of profitable buys are low. Personally, Id consider selling any stock or ETF when the price moves below the 26-week moving average.