Adaptive Net Indicators - neural nets especially adapted to pattern recognition, some of which automatically include lags of inputs. Useful for building your own adaptive moving averages. Adaptive Turboprop 2 - like the neural nets in the Prediction Wizard, but they operate like an indicator and automatically retrain themselves. You can optimize training set size, walkforward interval, number of hidden neurons, and even the lookahead period.

Advanced Indicator Set 1 - a set of indicators that users requested including chaos indicators, an indicator that gives the phase of the moon, and curvefitting trendline indicators. Advanced Indicator Set 2 - our second set of users requested indicators including indicators by Marc Chaikin and J.

Advanced Indicator Set 3 - an eclectic set of indicators that expand NeuroShell Trader's ability to find a value between two separate conditions or since the occurrence of a single condition.

In addition, Set 3 adds the power to count, remember or toggle values off and on based on conditions. These functions complement the NeuroShell Trader's emphasis on building indicators with a wizard rather than requiring the user to be a programmer.

The result is a significant speed increase in building and testing trading systems. Cluster Indicators - like the neural indicators, these give a buy or sell signal the probability that your issue is a buy or sell opportunitybut they work by clustering instead of using a neural net. Fuzzy Pattern Recognizer - Lets you describe patterns in which you are interested, and then tells you when these patterns appear.

Uses fuzzy logic to find the patterns, so it can tell you when a pattern is "like" the one you are seeking. Fuzzy Sets - With Fuzzy Sets the user can instruct NeuroShell with functions equivalent to fuzzy statements like: Neural Indicators - classification neural nets that give you the probability that the current situation is a buy or sell opportunity.

These nets don't predict any price, they give you a direct signal probability. Some of them are "recurrent nets" that automatically look back in time. Pattern Matcher - a set of indicators based on the concept of finding patterns, past or present, in a time series, and the subsequent activity that occurred after it.

Turning Points - a set of indicators based on the concept of finding local peaks and valleys in a price series. BMJ Fractal Analysis Indicator Set BMJ Fractal Analysis Indicator Set The BMJ Fractal Analysis Indicator Set is a group of indicators based on the concept of the fractal analysis of a time series.

All the indicators are based on a common core that takes any time series and analyzes the fractal dimension of the time series, converts the fractal dimension to the Hurst exponent, and produces a filtered time series that is theoretically stripped of most of the noise in the data. The result is a highly responsive smoothing filter of any data series.

The underlying technology is based on the estimation of the fractal dimension of a time series and the conversion of the fractal dimension to the Hurst exponent. The fractal dimension for a time period of a given time series is estimated and converted to the Hurst exponent.

The relationship between the fractal dimension and the Hurst exponent is such that the Hurst exponent is equal to two minus the fractal dimension. The fractal dimension varies between 1 and 2 while the Hurst exponent varies between 0 and 1. A time series with a Hurst exponent of 0. A time series with a Hurst exponent greater than 0. A time series with a Hurst exponent less than 0. A persistent time series can generally be expected to continue in the direction of the trend, at least until it reverses.

An anti-persistent time series will generally not be in a trend and may be expected to reverse direction more frequently. Any financial instrument and any financial time series can be expected to exhibit both forms of behavior over time. The theory of the fractal analysis indicators is that by using the fractal dimension and the Hurst exponent we can produce filtered time series that are theoretically stripped of most of the noise in the data.

The result is really two foundational indicators upon which all others are developed. The first is the BMJ Hurst indicator which is the calculated Hurst exponent for some look back window in the time series. The second is the BMJ FFilter or the fractal filter. The fractal filter is developed by using the Hurst exponent and converting it to an alpha for an adaptive filter of the time series based on the concept that price variation is directly proportional to some power of the time elapsed.

We might be tempted to call this an adaptive moving average. But it is really much more than that. The fractal filtered time series is so responsive to changes in direction with virtually no lag and no overshoot, that the filtered result can be used as a proxy for the original time series in any traditional technical analysis techniques.

The BMJ Fractal Filter can be used as a pre-processor of the time series for any traditional technical analysis. It can also be used as a post-processor to smooth traditional technical analysis techniques or to provide a signal line for cross over triggers.

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The BMJ Fractal Analysis indicators can also be used in concert with other traditional technical analysis indicators. All three of these approaches are illustrated in the Example Charts. To provide maximum flexibility and responsiveness, all of the fractal indicators have been developed as adaptive indicators where the period input is an adaptive input.

It can be entered either as a numeric value such as 30 bars or as a time series, such as some multiple of the BMJ Hurst indicator. Since the Hurst exponent will by definition vary from 0 to 1, using some multiple of this indicator is a valid input to this parameter. In addition, it meets the objective of an adaptive parameter, because the length of the FF period will be longer when the Hurst exponent is greater than 0.

This would theoretically result in a filtered time series that is more responsive to both trending markets and consolidating or trading markets. Using a multiple of the BMJ Hurst indicator as an input to this parameter is illustrated in the Example Charts included with the indicator set.

The beauty of the BMJ Fractal Analysis Indicator Set is that all of the indicators can be used out of the box either by themselves or with any of your favorite Neuroshell indicators.

The BMJ Fractal Filter can be used as a pre-processor of a time series input for any of the included Neuroshell indicators or technical analysis techniques. It can also be used as a post-processor to smooth any other indicator or technical analysis technique or to provide a signal line for cross over triggers. The BMJ Fractal Analysis indicators can also be used in concert with other traditional indicators or technical analysis techniques.

Simply add one or more of the BMJ Fractal Analysis indicators to your favorite prediction or trading strategy and see how it improves performance and consistency of performance over optimization, paper trading, and out of sample periods. The indicator set includes 30 example charts, many with multiple predictions and trading strategies, illustrating all of these concepts. The website also includes screen shots and commentary for a sampling of these example charts.

World class noise elimination filter for market price data. Lets you see underlying activity without the "jaggies". Has extremely low lag, is very smooth and unusually responsive to market price gaps. For details, visit http: Superior version of classical "momentum" indicator. Has extremely low lag. Precise and very smooth. Excellent for price-momentum divergence analysis. Superior version of classical "ADX" indicator.

Measures trend duration not momentummaking it ideal for adaptively adjusting the speed of other technical indicators. Very sensitive to market trend quality, making it useful as an early warning against trend collapse. Superior version of the classical "RSI" indicator. Combines market momentum and trend quality into one signal. See the top-right chart on http: Ehlers' book develops and demonstrates effective new trading tools through the application of modern digital signal processing techniques.

Modernizing popular trading procedures to take advantage of the incredible computing speed and power available to today's trader, Ehlers introduces: The Fisher Transform --ensure that the density function of any indicator is Gaussian, creating sharper trading signals.

The Relative Vigor Index --a responsive oscillator in which movement is normalized to the trading range of each bar. Improved Hilbert Transform --a more responsive method to accurately measure market cycles. The Laguerre Transform --a new tool to address the smoothing versus lag problem more effectively and create better smoothing filters.

Super Smoothing Filters --provide more smoothing with less lag. Simple Moving Average Computations --two new ways to compute the simple moving average with unprecedented ease "Advances made in computer technology in the past two decades have clearly outpaced advances in trading software and practice. Cybernetic Analysis for Stocks and Futures seeks to restore the balance between computational power and user proficiency," according to Ehlers.

Although there is a help file with the add-on to assist with mechanics, the add-on is a companion to the book, and the theory and usage of the indicators are explained only in the book. The Cybernetic Analysis add-on contains the following indicators from the book: Price - returns the average of the high and low values for the bar. Ehlers uses this value in most of his indicators when he is referring to a price data stream.

This indicator is described in Chapter 1. It may be combined with the FisherTransformTrigger indicator to create a trading system. The FisherTransformTrigger indicator may be combined with the Fisher Transform indicator to create a trading system. According to Ehlers, "having an Instantaneous Trendline with zero lag is a good beginning to generate a responsive trend-following system. This is a leading indicator that is created by adding a two-day momentum of the Instantaneous Trendline to the Instantaneous Trendline itself.

In order to incorporate a limit price for the ITrend crossover condition and no limit for the emergency exit condition which uses the RevPct Reverse Percentagethis add-on contains three additional indicators not included in Ehlers' book. Ehlers' Trading Strategy is built into these indicators: Cyber3TSLimit - Cyber3TSLimit is used in conjunction with Cyber3TSPosition and Cyber 3TSSignal. Cyber3TSPosition - Cyber3TSPosition is used in conjunction with Cyber3TSLimit and Cyber 3TSSignal.

Cyber3TSSignal - Cyber3TSSignal is used in conjunction with Cyber3TSPosition and Cyber 3TSLimit. This is an indicator that isolates the cycles in data with additional smoothing. The Trigger indicator is created by delaying the Cyber Cycle indicator by one bar. Ehlers describes this smoothed, zero lag indicator as useful for identifying turning points. The Trigger indicator is created by delaying the Center of Gravity indicator by one bar.

This indicator measures the up and down strength of the market normalized to the trading range. The Trigger indicator is created by delaying the Relative Vigor Index indicator by one bar. This indicator is a ratio of up prices compared to the sum of up and down prices, and the stochastic portion looks at the highs and lows over the same period.

The Trigger indicator is created by delaying the StochasticRSI indicator by one bar. It adds the stochastic component of examining the highs and lows to the Cyber Cycle indicator from Chapter 4. The Trigger indicator is created by delaying the StochasticCycle indicator by one bar. It adds the stochastic component of examining the highs and lows to the Center of Gravity indicator from Chapter 5.

The Trigger indicator is created by delaying the StochasticCG indicator by one bar. It adds the stochastic component of examining the highs and lows to the Relative Vigor Index from Chapter 6.

The Trigger indicator is created by delaying the StochasticRVI indicator by one bar. Ehlers adds the Fisher Transform to the Cyber Cycle indicator from Chapter 4 to produce sharper, better defined entry and exit signals.

The Trigger indicator is created by delaying the Fisher Cycle indicator by one bar. Ehlers adds the Fisher Transform to the Center of Gravity indicator from Chapter 5 to produce sharper, better defined entry and exit signals.

The Trigger indicator is created by delaying the Fisher Stochastic CG indicator by one bar. Ehlers adds the Fisher Transform to the Relative Vigor Index indicator from Chapter 6 to produce sharper, better defined entry and exit signals.

The Trigger indicator is created by delaying the Fisher Stochastic RVI indicator by one bar. It may be used to measure the Dominant Cycle period. This indicator enables the Cyber Cycle indicator from Chapter 4 to be adaptive to the measured Dominant Cycle period. The Trigger indicator is created by delaying the Adaptive Cyber Cycle indicator by one bar. This indicator enables the Center of Gravity indicator from Chapter 5 to be adaptive to the measured Dominant Cycle period.

The Trigger indicator is created by delaying the Adaptive CG indicator by one bar. This indicator enables the Relative Vigor Index from Chapter 6 to be adaptive to the measured Dominant Cycle period. The Trigger indicator is created by delaying the Adaptive Relative Vigor Index indicator by one bar. This indicator may be used to predict the turning point of market cycles.

It is plotted as the sine of the phase angle of the Dominant Cycle. This indicator measures the Dominant Cycle period and uses that measurement to compute a one-cycle momentum. Ehlers introduces Butterworth filters as better filters than exponential moving averages. Compared to the Two Pole Butterworth Filter, this one increases the sharpness of the filter rejection. This filter has less lag than the 2PoleButterworthFilter.

Compared to the Two Pole Super Smoother, this one increases the sharpness of the filter rejection. Ehlers describes this filter as a balance between smoothing a signal and lag in order to avoid whipsaw trades. Ehlers shows that you can apply the Laguerre Filter to familiar indicators. This indicator combines a leading indicator with an exponential moving average to show when the market is in an uptrend or a downtrend.

He describes this indicator as an oscillator that produces clear buy and sell signals. The following are NeuroShell Trader Example charts included with the Cybernetic Analysis add-on: Example Chapter 3 ITrend No Limit This chart builds a Trading Strategy based on the crossover of the ITrend and ITrend Trigger indicators from Chapter 3. Example Chapter 3 ITrend Limit Intel This chart builds a Trading Strategy based on the crossover of the ITrend and ITrend Trigger indicators from Chapter 3.

This chart incorporates a limit price for the crossover condition. Example Chapter 4 Cyber Cycle This chart uses a crossover of an indicator named Signal to generate trading signals. Example Chapter 4 Cyber Cycle Opt HD This chart uses a crossover of an indicator named Signal to generate trading signals. This chart is optimized on Home Depot HD.

Results are improved from the unoptimized chart named Chapter 4 Cyber Cycle. Example Chapter 4 Cyber Cycle Opt Intel This chart uses a crossover of an indicator named Signal to generate trading signals. This chart is optimized on Intel and includes an evaluation period of 6 months in the Trading Strategy.

Example Chapter 4 Cyber Cycle Opt Deere This chart uses a crossover of an indicator named Signal to generate trading signals. This chart is optimized on Deere and includes an evaluation period of 6 months in the Trading Strategy.

Example Chapter 10 Adaptive RVI This chart builds a Trading Strategy by using a crossover of the Adaptive RVI and Adaptive RVI Trigger. This is typical of many of the Trading Strategies Ehlers builds with indicators described in the book. Example Chapter 10 Adaptive RVI Opt This chart builds a Trading Strategy by using a crossover of the Adaptive RVI and Adaptive RVI Trigger. This optimized version of the Chapter 10 Adaptive RVI chart produces more profit than the original.

Example Chapter 12 Adaptive Trend This chart builds a Trading Strategy for the Swiss Franc by using a crossover of the Adaptive Momentum indicator and 0.

Example Chapter 12 Adaptive Trend Opt SF This chart builds a Trading Strategy for the Swiss Franc by using a crossover of the Adaptive Momentum indicator. This chart is optimized to increate profit. Example Chapter 12 Adaptive Trend Multiple Stocks Opt This chart builds a Trading Strategy for the multiple stocks by using a crossover of the Adaptive Momentum indicator. This chart is optimized to increase profit.

Example Chapter 12 Adaptive Trend Opt Dell This chart builds a Trading Strategy for Dell by using a crossover of the Adaptive Momentum indicator. For more details, please view the product manual for this add-on. John Ehlers has once again broken new ground applying scientific methods to market data with the release of the MESA91 indicators for NeuroShell Trader. The MESA91 indicators measure whether the market is in cycle or trending mode and deliver precise trading signals for either situation.

The new version includes an adaptive method of extracting the dominant cycle for each instrument and an EvenBetterSine indicator that can forecast market trend in only a half period of the dominant cycle. Each indicator now includes parameters for setting the Lowest and Highest Period of the cycle, and these parameters may be optimized in NeuroShell Trader.

Ehlers is a world renowned expert in applying scientific principles and DSP digital signal processing technology to the art of technical trading. According to Ehlers, a simplified model of the market consists of the combination of a trend and a cycle. Since the cycle period is known, it can be removed from the data to expose the underlying trend. The market is best traded using oscillator-type indicators when it is in a cycle mode and is best traded using moving average-type indicators when it is in trend mode.

The MESA91 collection of indicators is not only dynamically adjusted by the dominant cycle, but advanced DSP techniques are used to produce low lag and non-causal signals in time to give users a trading advantage.

The MESA91 add-on is a joint project between Mesa Software, Inc. Mesa developed the theory and programming and Ward Systems is selling the add-on for use with NeuroShell Trader. MESA91 requires NeuroShell Trader release 6.

The same is true for the MESA91 Adaptive RSI and Adaptive Stochastic indicators included in the set. Its amplitude is plotted to reflect the cyclic swing of the input time series. A smaller number gives a narrower bandwidth to eliminate extraneous cycle components and a larger number gives a wider bandwidth to improve responsiveness to transients.

This display enables an easy estimation when a swing peak or valley is reached and therefore a higher probability of reversion to the mean.

MESA91 Dominant Cycle This indicator displays the MESA-measured Dominant Cycle.

The Dominant Cycle can be used to dynamically tune other indicators to maintain consistency with changing market conditions. MESA91 Sine and LeadSine The problem with virtually all indicators is that they are causal. That means they directly depend on data for their computation. As a result, the computation cannot be accomplished until after the data arrives, and - as a result - all causal indicators have lag. Lag is perhaps the traders' worst enemy, particularly when trading the cycle mode when relatively short term entries and exits are expected.

The market is coherent in the cycle mode, meaning that the Dominant Cycle has existed for a short while in history. It is further assumed that the dominant cycle will continue for a short time into the future. Since the dominant cycle is known, and its phase can be computed, we can advance time by advancing phase of the coherent dominant cycle.

For an 16 bar cycle, the crossing occurs 2 bars ahead of the cyclic turning points - just right for making a timely trade entry. The original Sine indicator correlates a pure sinewave with the phase of input cycle or dominant cycle in MESA91 over a full cycle period. This completely removes any trend component and only gives the cycle inherent in the data. The disadvantage of this indicator is that sometimes the cyclic swing is so small that the dominant cycle data is inconsequential. This is particularly true when the market is in a trend.

On the other hand, the EvenBetterSine correlates the data with a sinewave over a HALF period of the dominant cycle. The degree of smoothing is altered by the Mult input parameter, which is the fraction of the Dominant Cycle to which the filter is tuned. This definition may not be strictly true, but it suffices as a qualifier of uncertainty of the intraday prices. For the purpose of this indicator, Signal is the peak-to-peak amplitude of the Dominant Cycle.

When the wave amplitude of the Signal is twice the Noise amplitude the SNR has a value of 6 dB. This ratio is the threshold below which it is not advisable to swing trade on the basis of cycles. This results in an indication of the trend. If the ratio is greater than one, then the uptrend is swamping the Dominant Cycle and it is not advisable to use the Dominant Cycle for swing trading. The MESA91 indicator set includes eight example charts that you can examine inside of NeuroShell Trader.

BUY NOW Contact Information: For sales questions, please contact: Ward Systems Group, Inc. Executive Park West 5 Hillcrest Drive Frederick, MD Voice: John Ehlers PO Box Goleta, CA Voice: Meyers Analytics N. LaSalle Drive Chicago, IL Voice: Adaptive Mixture of Experts AME Causal Singular Spectrum Analysis CSSA Entropy Indicators NEI Adaptive Mixture of Experts AME Noxa AME is a world-class expert advisor able to adapt to not just changing market conditions, but changes in the fundamental way the market works.

It is self-learned, and has only one parameter to set. Markets are not static. They are dynamic and susceptible to quick changes, even more so with the influx of High Frequency Trading. Adaptive strategies should be able to adjust to not just changing market conditions, but changes in the fundamental way the market works.

Mixtures combine the beliefs of several expert algorithms into a single prediction. They are capable of greater predictive performance than any of their individual experts. It is possible for price patterns to develop with different outcomes; they often run contrary to each other.

Most often we are pretty useless at making sense of it all. Expert algorithms however can deconstruct a pattern into low level features and look at how they progress through time in various contextual scenarios. BUY NOW Causal Singular Spectrum Analysis CSSA. I am very comfortable working with the package. It is incredibly useful just to look at the raw CSSA indicators Nature and its parts fluctuate in cycles. Markets are no exceptions.

A quick glance at any price chart will reveal cyclical behaviors; price bobs up and down with a good degree of regularity giving evidence of rhythm. Obviously, if cycles are genuinethe presumption is that they will continue. And mostly they do, so we cannot afford to ignore them. It is packed with a set of zero-lag indicators that provide a full wave-composite picture of the market at all time-frames. As you can see on the graph below, the peaks and troughs of the cycles emphasize the swings as if they were predicted with perfect hindsight.

To learn more about CSSA, CLICK HERE. Following is a brief overview of the indicators in the CSSA add-on: CSSA-Cycles The cycles are designed to be a direct reflection of the price action so that they don't lag.

You will be able to quickly anticipate turning points independently of the time-frame. CSSA-Slope and Trendlines These indicators are derivatives from CSSA-Cycles; they are particularly useful in identifying and confirming the direction of momentum behind a move. CSSA-Long and Short Entries Signals are triggered by CSSA-Cycles from its bases and peaks.

A causal lead and filtering features have been added to compensate for inherent execution lags so that you can make the most of each market move. CSSA-QPhase This indicator operates a 90 degree phase shift of CSSA-Cycles; the peaks and troughs of the cycle line become zero crossings. Signals are then triggered when the transform breaks through its center line.

Because of the accuracy of the signals, tight stop losses can be kept for even better results. CSSA-Oscillator In addition to generating signals, this centered oscillator can also be used to confirm developing trends. CSSA-Turning Levels Lines are drawn horizontally from the base before an up—move in CSSA or a peak before a down—move.

The purpose of this indicator is to show where price is liable to find some local support and encounter some local resistance. The violation of these lines can generate reliable entry points.

CSSA-Percent Variance, CSSA-Coupling Index Both indicators are variations of the same concept. They use the variance accounted by individual cycles or group of cycles to compute a degree of coupling between them. Any sudden change in this coupling can announce that something is amiss with the current trend or that the current trend is how much has dhoom 3 earned till now to change.

CSSA-Change Point Score The degree of change between recent and past price action is returned. It can be interpreted as the probability that some change is likely to occur due to strong causal dependencies in the data.

In other words this indicator reveals hidden dependencies that may announce significant changes in trend. CSSA-ShowRange Select a range, and then use the values shown in the caption to set the training range of CSSA indicators. CSSA-ShowEigenvectors Visualize the elementary patterns of behavior in price and start day trading penny stocks propagating modes.

Their inherent persistence over time makes these modes especially worthy of attention. Example Following is a screenshot illustrating crossovers from CSSA-QPhase. The out-of-sample equity curve looks upper trending and pretty strong: The Japanese developed Renko bar charts in an attempt to show price based upon a specified amount of movement in a single direction rather than reporting price based on a time schedule as in a 5 minute bar chart.

Richey Enterprises developed an entirely new concept in Renko bars - optimizable Renko bars based on price, volume, or a combination of both, that may be customized for each security. The result is that your trading systems are based on less noise and subsequently generate more precise trading signals. These innovative Renko Bars comprise the InterChart Tools Renko Bars Add-On for NeuroShell Trader.

The InterChart Tools How to make money as a kid bookies bonuses Bars are virtual bars capable of generating trading signals and performing their calculations using the same methods as traditional bars.

Once a trading signal is generated by the Renko bar, both the trade and fill are correctly displayed on the open of the next bar of the base chart. For example, you can create a 0. Renko Bars are only created when price has moved either up or down by the amount of the specified high-low range.

This amount is referred to as the brick size. In all classic Renko charts, all bricks must be exactly the same size and remington 11-87 youth stock for sale change specified in the high-low range must be in the same direction, either up or down, before a new bar is formed. The InterChart Tools Renko Bars include parameters that allow you to specify the number of ticks used to calculate the up part of the Renko bar as well as the number of ticks used to compute the down part.

Since any bar's function is to absorb noise and rising price jitter is often different from falling price jitter, the IctRenko bars permit an asymmetrical definition to accommodate this. IctRenko bars are only created when price has moved either up or down by the number of virtual ticks specified in either the Ticks per Up Bar or Ticks per Down Bar multiplied by the Bar Size Multiplier.

NeuroShell Renko bars may, at the user's discretion, be controlled by the NeuroShell Trader optimizer to identify the optimal bar size and how much money does tom brady make per year absorption for a given algorithm or security.

You need NeuroShell Trader 6. For more information, call Ward Systems Group at Streams may be sent or received from any of NeuroShell DayTrader Professional chart types: Because InterChart Tools 1 works with daily, monthly, and weekly charts, it may also be used with NeuroShell Trader crude oil price in dollar history NeuroShell Trader Professional.

These streams are time series chart items. Any time series which can be plotted on a chart can be sent to another chart using the SendStream and GetStream indicators respectively.

Items that may be sent to another chart include: The multiple streams are processed summed, min value, max value, or averaged and displayed on another chart as a single data stream using the GetGroup indicator. Volume Indicators Volume data may be transmitted from a stock chart to an options or futures chart using the SendVolume and GetVolume indicators.

The SendVolume indicator is different from the SendStream indicator because it accumulates data until the completion of a bar on the receiving chart. Cautionary Note There is no way to guarantee the order in which two separate intraday charts will update with a new bar, and thus it is likely that charts updating bars at the same time may not receive the most recent data.

As an example, suppose a 1-minute chart is sending a stream to a minute chart. Six times an hour these charts will update at the same time, and which updates first is usually a function of the unpredictable timing properties of stock options hull which data is received, or other factors.

Therefore at any one of those six times per hour, it is possible that the minute chart will update and ask for streams a second or so before the 1-minute chart updates.

The minute chart will get the streams that are currently available, and will not wait for the 1-minute chart to update. Therefore it asking for stock options in a startup possible that the minute chart will receive 1-minute-old data from the 1-minute chart.

Do not use these indicators where this what are bulls and bears in stock market be a problem for you.

Generally simultaneous updating is not as likely when at least one chart is a volume, tick, or range bar chart. To correct this problem, you can right click on the chart and select recalculate chart to manually update "out of sequence" operations. Another time that older bars may be sent is when there are no bars to send. This could occur when there are gaps in price bars due to missing data, the exchange not being open, or other causes. When a new value for a bar is available, the bar may change.

If you build a prediction or trading rules based on these bars, your signals could change. Such problems may be less troublesome when sent data is received by the chart with the fastest bars.

InterChart Tools 1 will NOT work on charts that have more than one chartpage. InterChart Tools 1 indicators include: SendStream — transmits a single data stream GetStream — receives a single data stream SendGroup1, 2, 3, 4, 5, and 6 — transmits up to 6 similar data streams GetGroup — accepts data from the SendGroup indicators and applies a treatment such as summing, extracting the minimum or maximum value, or averaging to compress the data into a single stream SendVolume — sends volume data.

This indicator accumulates volume data until the completion of a bar on the receiving chart. GetVolume — receives volume data that accumulates since the last update Examples Example 1: This example shows how to send a 10 bar moving average computed on a 5-minute chart to a 7-minute chart. The 5-minute chart contains the following indicator SendStream that uses a StreamID of 1: SendStream 1,Avg Close,10 The 7-minute chart contains the following GetStream indicator, which reads StreamID 1: GetStream 1 Example 2: In this example a range bar chart computes the spread between an RSI on itself and an RSI from a daily chart.

The daily chart contains an RSI indicator that has been renamed DailyRSI. It also contains the following SendStream Indicator with a user selected StreamID of SendStream 13,DailyRSI The range bar chart contains an RSI that has been renamed RangeRSI. It also contains the following indicator: Spread RangeRSI,GetStream 13 Example 3: The user in Example 2 also creates an hourly bar chart to which he would like to send the spread on his range bar chart.

The following indicator is added to the range bar chart from Example 2, now called Example 3 Range SPY. SendStream 5,Spread RangeRSI, GetStream 13 The following indicator is added to the daily chart from Example 2, now called Example 3 Daily SPY. SendStream 12,Avg Close,10 Then on the hourly bar chart called Example 3 Hourly SPYthe following option strategies implied volatility is added: Divide GetSteam 5GetStream 12 For more details, please view the product manual for this add-on.

BUY NOW InterChart Tools 2 Richey Enterprises has developed a set of price indicators called InterChart Tools 2 that generate early trading signals for NeuroShell Trader.

The TimeBars indicators call higher timeframe data to a chart and update every time the base chart updates. There are separate indicators for the open, high, low, close, and volume data as well as several different combinations of that data. The Consolidated Bars indicators combine x number of the most recent bars that you specify into a single data stream and are useful for fast moving tick and range bars.

The TimeBars indicators let you to create 5, 10, 15, 30, etc. The optimizer in the Trader can determine the bar size which is most appropriate for your desired algorithm and equity. The Consolidated Bars indicators can combine the high value from the most recent 5 bars, for example.

The Consolidated Bars are especially useful when your trading system is based on tick and range bars. Consolidated bars allow you to de-noise high frequency range and tick bars. The optimizer can identify the optimal number of bars to consolidate during the morning, mid-day and closing sessions to properly de-noise range data without lag and without having to wait for a higher range bar to complete.

Time Bars High and Volume On the Example 1 chart we have added a TimeBar High indicator. The high bar displays the "highest" stock market returns 1930s value from the 10 minute bar since the 10 minute bar began to form.

The TimeBar High will continue to build until 10 minutes past the hour at which point it will be identical to the high of a standard 10 minute bar. At 10 minutes past the hour both indicators will reset and the operation repeats. We also added the TimeBar Volume indicator to the chart. When you look at the example chart, the TimeBar high values from the 10 minute advanced short stock strategy term trading trading wizard are almost always correctly defined before the end of the bar time.

Therefore any Trading Strategy, Prediction, or indicator which references the high of a higher time frame bar may fire before a standard bar would be able to issue a signal. Similarly, the bar volume builds at the chart frequency. Any Trading Strategy, Prediction, or indicator which depends on a volume level from a higher time frame will fire when that has been achieved.

Often this is before half of the bar has been built. Intrinsic value of an american call option course, if the volume requirement is not going to be met for this bar, it will not fire falsely.

We did not optimize any input parameters. The model shows a We entered a Trading Strategy as follows: RSI based on TimeBars Low 10 minute Optimize the number of periods in the RSI from 1 to 10 and optimize the RSI value from 15 to 45 Short Entry: The model returned an annual return on account of Example 4 Optimize Time Frame If you don't know which higher time frame to use in your model, you can let the optimizer choose.

We created a prediction much like Example 2, but instead of using different TimeBars indicators based on the same time frame, we used the same TimeBarsHL2 indicator, one for 10 minute bars and the other for 15 minute bars, both on a 5 minute chart.

In the Prediction Parameters settings on the Optimization tab, we limited the maximum number of inputs to 1 so the optimizer was forced to make a choice of inputs. You could do the same thing with various numbers of Consolidated Bars. Letting the optimizer choose the best TimeBars calculate number of workdays between two dates in access Consolidated Bars could also be used in the Trading Strategy wizard by choosing Rule Selection Optimization on the Long and Short rules tabs.

Example 5 Consolidated Bars We created a. On tick based charts range and volume these consolidated bars act like variable time bars. In this example, a 5 bar ultimate day trading system reviews of a.

These bars are continuous and always reflect the high of the previous N bars, so as a new bar is added the oldest bar is dropped off. Unlike any moving average which might attempt to do indian stock market ebook same, there is never any lag. The Prediction predicted 5 0. We set the number of hidden neurons down to 1.

The profitable results from the optimization period continued into the out-of-sample period. Example 6 Optimize Data Stream If you don't know which data stream you want to use in your Trading Strategy or Prediction, you can use the TimeBars indicator and let the optimizer choose a display parameter, which means that the optimizer will choose the correct data stream. In this example, we forex rates icici bank india two TimeBars indicators in a prediction and optimized only the display parameter.

The two TimeBars were based on 10 and 15 minute bars respectively, and the optimizer chose the 10 minute bar based on the low as the only input for the model. Consolidated Bars You can also let the optimizer choose the data stream for Consolidated Bars by optimizing the display parameter for a Consolidated Bars indicator.

BUY NOW InterChart Tools 21 Richey Enterprises has developed a set of price swing trading strategy in forex called InterChart Tools 21 that generate early trading signals for NeuroShell Trader. Adaptive Consolidated Bars indicators also combine the information from the most swedish stock market today live ticker bars on a chart, but unlike the regular Consolidated Bars the Adaptive Consolidated Bars treat rising bars and falling bars independently.

The Adaptive Consolidated Bars offer the option of consolidating a different number of bars for rising prices as contrasted to the number of bars for falling prices. Since explanation of green room binary options review function of a consolidated bar is to absorb noise and rising price jitter is often different from falling price jitter, the Adaptive Consolidated Bars permit an asymmetrical definition to accommodate this.

Example 7 Consolidated Bars vs Adaptive Consolidated Bars The Adaptive Consolidated Bars were able to increase the profits from the original Trading Strategy built on crossovers of Exponential Moving Averages of consolidated bars. BUY NOW RJ5 Group LLC Product s: The basis of the indicators is extractions of dynamics of price and time with the added mathematical algorithms that attempt to capture the pure impulse movement of the instrument being evaluated.

The W3 and V2 indicators can also be filtered by other indicators such as RSI, Linear Regression Slope as well as others that the user may want to experiment with in their models. How all this came to be… Interview with Raul Jimenez, creator of iCinDER W3 and V2. I have been trading since about and have devoted time to studying trading systems, indicators, Dow Theory, Elliott Wave Theory, etc.

During all my trading years, I found systems that worked for a while then stopped working. At the time, I did not understand why but changed to another system that would work for a while. Inafter working for a large software company for a number of years, I decided it was time to stop the traveling and fast paced lifestyle and devote some time to something I was passionate about — trading in the stock market.

I had spent time reading books on cycle analysis, MACD, RSI, adaptive indicators and other methodologies. It all came back to me as either the cycles were too closely correlated, tight fitting with virtually no divergence or loosely coupled. Ucla electrical engineering computer science option knew that mathematically it was possible to measure multiple timeframes and correlate them to a single wavelength, which while not adaptive could provide high correlation to the measured instruments.

I will not bother with discussing all the experiments, but one thing was clear — the business cycle was part of the solution. With this in mind, I devised an algorithm that analyzed price and time in 5 dimensions — this became V2 — and a secondary indicator that added a theoretical momentum type dimension. This last part was composed of 2 dimensions at 2 timeframes.

Adding all this together to V2 W3 was born. This was December of when this was completed. Initial complex implementations with scanners and strategies were done for Tradestation, and to date that is the most complete and complex model I have developed.

The simple V2 and W3 were ported to other platforms — Cause and effect of stock market crash 1929, eSignal and others.

Now we fast track to when a good friend of mine, George D, started discussing GA with me. I had worked on this before and thought of having a fresh look at V2 and W3 within a GA. My friend recommended Neuroshell.

Today, we have both V2 and W3, implemented in an how much money does sports analyst make DLL. We ship the indicators with an extensive Help File and sample models that the user can use as starting points for their own models. We plan on providing more complex models for the users that have TurboProp, NI and even Chaos Hunter.

RJ5 Group LLC Dishman Loop Oviedo, FL Voice: He or she would scan the price stream close looking for distinct movements. Then he or she would examine the pattern formed by the changes in close for some number really profitable binary options strategy named the sandwich bars let's say 11 just prior to the distinct movements.

If this human is pretty good at pattern recognition, he or she might even examine the changes in the open, high, and low of the preceding 11 bars as well as the change in close in those bars. The human is looking for what types of patterns in the prior 11 bars ky cattle market report foretell the distinct movement.

Once the human is satisfied that there is a high probability of the distinct movement following certain patterns, he or she can then watch for those patterns in the future. When the patterns appear, the human expects one of the distinct movements to follow and places orders appropriately. The example above is the inspiration behind the enhancements to Adaptive Net Indicators ANI release 2.

ANI always did pattern matching, but now in release 2. Adaptive Net Indicators are special versions of GRNN and PNN neural nets formulated to do pattern matching, both predicting and classifying.

They binomial option tree example quickly on every new bar, so they are never more than 1 bar behind. You can set the contribution factors yourself so that the net fx volatility trading strategies your specification of how important the inputs are, instead of the other way around.

Of course, you could also let the genetic algorithm find them if you own the NeuroShell Trader Professional or the DayTrader Professional. As a matter of fact, you can also let the GA find the optimal number of bars ahead to predict and the optimal training set size!!

If that's not enough exclamation points, how about this: Adaptive Net Indicators is a package with unprecedented flexibility and capabilities!!!! Many of you have expressed a desire to have confidence factors for your nets. The classification series of Adaptive Net Indicators will provide you with confidence.

In addition, Adaptive Net Indicators will make no prediction at all if they feel they have no basis on which to do so. Our Adaptive Net Indicators do pattern matching by comparing each new pattern encountered with a number of immediately previous known patterns. They do not use weights like most neural nets.

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The Net "output" i. It is most heavily influenced by the most closely matching of the known patterns, and so the output of any new pattern encountered will be much like similar known patterns. You the user can set the number of immediately previous patterns which the Net select option in angularjs example to the new pattern.

The Net indicator has "inputs" in which the pattern is stored, just like other indicators and neural nets. If a Net has 3 inputs, you can feed in the current values of the RSI, a CCI, and the Momentum to form the pattern, for example.

Or you could feed the Net today's close, yesterday's close lag 1 of closeand the close the day before lag 2 of close. You can feed Net outputs into a Net, just as you could do with any other indicator.

With some of our indicators, you can also input many "lags" of the primary inputs as well. Nets also have another type of input, called the "Actual" value. This is where you show the Net what you want the outputs to be like. In other words, you "train" the Nets to produce values like the Actual value whenever the corresponding inputs are closely matched. You want the Net to predict for you the Actual value X bars in advance. The output of the Net is the prediction signal of the Actual value X bars ahead.

You get to pick what X is for each Net. This is just like our neural nets in the NeuroShell Trader. Furthermore, you can even optimize the value of X in a Trading Strategy. There is another big difference between our Adaptive Nets and the neural nets in the NeuroShell Trader. The contribution factors for each input are also inputs. That's right, instead of the net telling you the contribution of each input variable, you get to tell the Net what the contribution should be.

The higher the contribution, the more heavily the Net will weigh that input when it does pattern matching.

Of course, if you'd rather have the contribution factors figured out for you, the NeuroShell Trader Professional can optimize them. There are two kinds of Adaptive Nets, depending on the type of output they produce. There are "Prediction Nets" whose outputs are predicted values like price change, percent change in price, predicted indicator values, etc. There are also "Classifier Nets" whose output is a probability of the pattern being of one type or another.

Types might be "Buy" and "Hold", for example. Other types can be "Good" and "Bad", or "Up" and "Down", etc. The Classifier Nets don't actually read or produce the strings like "Buy" and "Hold". You use positive numbers in the Actual for one category like "Buy", and zero or negative numbers for the other category like "Sell". The predicted output will be a number between -1 strong probability of sell and 1 strong probability of buy. Numbers close to zero could be considered "Hold" YOU would decide how close to zero a prediction should be to be considered a "Hold".

One of the interesting things you can do with Adaptive Net Indicators is build adaptive moving averages. You can adjust how tight or how loose the adaptive moving average is. The chart below shows an adaptive net indicator configured as an adaptive moving average. There are a total of 18 Adaptive Nets, nine Predictor Nets and nine Classifier Nets. There are 9 of each because each of the nine takes a different number of inputs as follows: Predict2 - Prediction Net which takes 2 inputs Predict3 - Prediction Net which takes 3 inputs Predict4 - Prediction Net which takes 4 inputs Predict5 - Prediction Net which takes 5 inputs Predict6 - Prediction Net which takes 6 inputs LagPredict1 - Prediction Net which takes many inputs: LagPredict2 - Prediction Net which takes many inputs: LagPredict3 - Prediction Net forex trading neural networks takes many ways to make money with chickens LagPredict4 - Prediction Net which takes many inputs: Classify2 - Classifier Net which takes 2 inputs Classify3 - Classifier Net which takes 3 inputs Classify4 - Classifier Net which takes 4 inputs Classify5 - Classifier Net which takes 5 inputs Classify6 - Classifier Net which takes 6 inputs LagClassify1 - Classifier Net which takes many inputs: LagClassify2 - Classifier Net which takes many inputs: LagClassify3 - Classifier Net which takes many inputs: LagClassify4 - Classifier Net which takes many inputs: Many of our customers have asked for a version of our famous TurboProp2 that retrains itself as often as every bar.

Well here it is, formulated as an indicator! Just insert it into your chart or trading strategy just like any other indicator. Never has a neural net been easier to use, yet so powerful!

Adaptive TurboProp2 AT2 is the same basic neural network algorithm that is used in the NeuroShell Trader, Trader Professional, and NeuroShell DayTrader Professional Prediction Wizard. However, AT2 can retrain itself as frequently as every new bar or after a number of bars which you can specify.

The training set is always the most recent bars. AT2 does not make predictions on the training set bars, and its predictions are free club penguin money maker download 2016 "out of sample" exception: Therefore, there are no walk forward periods to worry about, since the net is essentially walking forward each day or each bar in the case of the NeuroShell DayTrader Pro.

An AT2 net may be used as an indicator, as an input to a regular TurboProp2 net in the Prediction Wizard, or it may be used directly in a Trading Strategy. The output is a signal, meaning that the prediction is shown on the current bar, even if it is a prediction how to earn money fast on horse isle 2 10 bars from now.

AT2 doesn't require the optimizer in the Professional versions of the Trader because the parameters are so easy to set. However, when used with the NeuroShell Trader Professional or NeuroShell DayTrader Professional, you can optimize the following parameters:. AT2 nets allow 2 to 14 inputs. The names of the indicators are correspondingly Tprop2, Tprop3, …, Tprop Adaptive TurboProp2 requires release 3.

However, that didn't stop our users from wanting more! They sent us requests for more indicators, some of which were simple to build, and some of which required a great deal of research. So we built another add-on called the Advanced Indicator Set 1 with these requested indicators. They require release 3. Click here for a brief overview of the indicators in Advanced Indicator Set 1which are all listed below:.

Click here for a brief overview of the indicators in Advanced Indicator Set 2which are all listed below:. Advanced Indicator Set 3 is an eclectic set of indicators that expand NeuroShell Trader's ability to find a value between two separate conditions or since the occurrence of a single condition.

In addition, Set 3 adds the power to remember or toggle values off and on based on conditions. The Remember and Toggle indicators may be used to create complex Predictions and Trading Strategies. Advanced Indicator Set 3 also includes indicators specifically designed for pair trading. The PairEntry and PairExit set lets you build traditional market neutral systems that simultaneously buy and sell a pair of instruments that follow one another and frequently cross prices.

Rounding out this diverse mix are two indicators that compute the correct sun time and distance to the moon. The following descriptions of the Advanced Indicator Set 3 indicators are abbreviated. There are more comprehensive descriptions in the help file. The task oriented indicators in Set 3 such as Find, Count, Remember, and Toggle require the use of conditional indicators. The NeuroShell Trader includes many conditional indicators such as rules, Boolean, relational, crossovers, candlesticks, etc.

Advanced Indicator Set 3 expands those choices with the following indicators:. FollowedBy - returns a 1 for true when a Condition1 is followed by a Condition2. Other times it returns a zero. BarNumber - returns a 1 when the specified bar number appears in a chart. The first bar in the chart is numbered 1, the second bar is numbered 2, etc. Find - calculates values such as count, point change, percent point change, max, min, sum, average, standard deviation, variance, median, regression slope, number of advancing bars, number of declining bars, max advance, and max decline based on two conditions occurring in a data stream.

FindInclusive — does the same as the Find indicator but includes the bars on which the conditions are true. FindSince and FindSinceInclusive - find similar values from the time Condition1 occurs until the end of the chart.

Count - calculates a running total of the number of times a specified condition occurs in between a start condition and an end condition. CountInclusive — same as the Count indicator but includes the bars on which the conditions are true.

CountSince and CountSinceInclusive - these indicators begin their running total with the occurrence of Condition1, but Condition2 is replaced by the current bar. Remember - outputs a time series value based on a condition you specify. For example, the Remember indicator would output the value of the high the time series when the 9 period moving average crosses above the 13 period moving average the condition.

The output value would remain the same until the condition is met once again, at which time the current high would become the output. Remember2, Remember3, and Remember4 - output a different value depending upon which of several conditions is activated.

The Remember indicators may be used as variable inputs to other indicators, Predictions or Trading Strategies. Toggle - signifies the presence or absence of conditions you specify.

The Toggle indicators may also be used to remove certain data when training a neural net, e. The Toggle indicators output 0, 1, or a missing value based on the settings for the What parameter.

ToggleInclusive — same as Toggle but includes but includes the bars on which the conditions are true. ToggleSince and ToggleSinceInclusive - these indicators begin their running total with the occurrence of Condition1, but Condition2 is replaced by the current bar.

PairEntry - compares the value of the close, which is different for each of the two chart pages, to the value of Price1 the first stock and Price2 the second stock and determines which stock goes long and which stock goes short. The values of Price1 and Price2 are also used to compute the spread between stocks in order to determine an entry point for the trade. PairExit - determines the exit conditions for trades entered with the PairEntry indicator.

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The PairExit indicator includes the StopSpread parameter that can be set as an emergency exit for both stocks. ProxyEntry — similar to PairEntry but uses a neural net prediction to create proxy pairs by using one stock to predict the price of another. Uses the spread between the actual and predicted prices to pair trade the predicted stock and the one used as an input to the net.

ProxyExit - determines the exit conditions for trades entered with the ProxyEntry indicator. The ProxyExit indicator includes the StopSpread parameter that can be set as an emergency exit for both stocks. EquationofTime - returns the difference between solar time as measured by a sundial and mean clock time. MoonDistance - outputs the distance between the center of the Earth and the center of the Moon expressed in kilometers.

The Cluster Indicators, like some of the other add-ons from Ward Systems Group, are based on how the human brain might classify the market.

Suppose you have two good inputs. Now suppose you made a scatter plot of a bunch of recent bars worth of these inputs. For the math minded, all recent bars are plotted with one input on the Y axis and the other on the X axis. Now suppose the inputs are good, as defined by the fact that their patterns foretell an uptrend or a downtrend in the price. Then wouldn't the bars that precede an uptrend look somewhat similar, at least after they were "normalized"?

Wouldn't those that precede a downtrend look similar too? In other words, wouldn't the buy bars cluster together and the sell bars cluster together? The graph displays long entry and short entry clusters for a Cluster Indicator based on the MACD and CCI indicators as inputs. Our new Cluster Indicators tell you how far the current bar is from the cluster center of the recent "buy" bars or "sell" bars.

You can use a Cluster indicator as a buy rule, buying when the current bar is "close" to the cluster center of recent "buy" bars. Sell when the current bar is "close" to the "sell" cluster center. The genetic algorithm optimizer in the Trader Pro or DayTrader Pro finds the cluster centers that optimize the profit. The Cluster indicators also make dynamite inputs to a neural network.

For the neural net enthusiasts, this creates a paradigm much like the popular classic Radial Basis Function neural nets, except in the Trader Pro, your clusters don't have to all be based on the same inputs, and in fact can be optimized!

There was also a paradigm called Counter-propagation that was similar to feeding our Cluster indicators into a neural net. Now expand the concept to as many as 16 inputs. Those can't be plotted because you'd need a 16 dimensional scatter plot.

But you can still measure how close the current bar is to a 16 dimensional cluster center! There are 16 Cluster Indicators. Let's carry the concept a little further. Suppose some of the inputs are less effective than others in determining whether there is a buy or sell situation.

You wouldn't want to consider these inputs as much when determining clusters and "closeness". No problem, we have 8 Cluster "contribution" indicators, each of which has contribution factors which reduce or increase the impact of an indicator. You can set these contribution factors yourself or you can let the genetic algorithm do it for you. Either way, you now have a more powerful clustering indicator.

Cluster Indicators require release 3. How many times have you wished you could just let your software scan a price series and let you know when it has found a particular pattern that you like? You have in your mind a special pattern of moves that you believe could precede a strong change in the market, but you'd like the software to just monitor the incoming bars looking for your pattern.

Well now you can do just that with the Fuzzy Pattern Recognizer add-on for the NeuroShell Trader series! And you can do it using fuzzy logic! Fuzzy logic was invented by Lofti Zadeh, and written about extensively in books by Bart Kosko.

Fuzzy logic has been used successfully in machines and software around the world, even in "smart" household appliances. Now you can add this smart control to your trading, and it is easy to use because we've done the hard work for you!

The Fuzzy Pattern Recognizer is a fuzzy logic engine which lets you describe your pattern in "fuzzy" rules approximate rules of thumb. It is really a series of indicators that show you, on a scale of 0 to 1, how closely the current price series matches your pattern. Turn on an alert in the DayTrader Professional and the Fuzzy Pattern Recognizer will scan your incoming bars looking for all of your favorite patterns. The alert will sound when the match is above.

Fuzzy rules are rules that are general in nature, not exactly specified. We describe price or indicator curves with the following fuzzy verb rules:. Here are some example rules written in English which can be specified in the Fuzzy Pattern Recognizer add-on:. There are 8 "fuzzy verb rule" indicators in the add-on, Fuzzy1, Fuzzy2, Fuzzy1 handles "1 segment" rules such as "close rises" or "open drops sharply". Fuzzy2 handles "2 segment" rules such as "close rises, then drops sharply".

Fuzzy3 is for "3 segment" rules such as "open rises, then drops, then remains steady", etc. Example of the Fuzzy2 indicator output bar chart at the bottom. There are 3 FuzzyOR rules and 3 FuzzyAND rules: FuzzyOR2, FuzzyOR3, FuzzyOR4, FuzzyAND2, FuzzyAND3, FuzzyAND4. As previously mentioned, these combine rules. For example, suppose you are looking for either a pattern that rises sharply then drops sharply, or a pattern that rises sharply, then remains steady, and then drops sharply.

Then you would use a FuzzyOR2 indicator which takes as arguments a Fuzzy2 indicator and a Fuzzy3 indicator, each specifying their respective rules.

FuzzyOR and FuzzyAND indicators may take other FuzzyOR and FuzzyAND indicators as arguments, as long as the lowest level indicators are "rule" indicators such as Fuzzy2. There are also 8 FuzzyGA indicators, which allow the genetic optimizer to tune the fuzzy logic engine better. We believe that Fuzzy Pattern Recognizer indicators open a whole new world of possibilities in trading with artificial intelligence.

We think it will be our most popular add-on yet! The Fuzzy Pattern Recognizer add-on requires release 3. If you do not own one of the Pro versions, you can still use the Fuzzy Pattern Recognizer add-on to find patterns, but you will not be able to optimize the Fuzzy indicators.

You've asked for it, and now it is here: Fuzzy logic was invented by L. Zadeh and further popularized by Bart Kosko. Fuzzy logic is not some theoretical idea that has yet to catch on. By the Japanese had over real fuzzy control applications and products. The city of Sendai in Japan has controlled its subway with fuzzy logic since Duke University engineers have shown that intentionally imprecise rules of thinking can help hotel computers sell the right room to the right customer at the right time, thus boosting income.

Ward Systems Group introduced what we believe was the first commercial trading software to allow users to describe price movements with fuzzy logic statements the Fuzzy Pattern Recognizer add-on. A user could essentially give NeuroShell instructions such as:.

The new Fuzzy Sets add-on is somewhat different in that it allows users to describe a combination of values of traditional indicators with fuzzy logic.

The Top 5 Technical Indicators for Profitable Trading

With Fuzzy Sets the user can instruct NeuroShell with functions equivalent to fuzzy statements like:. Those 2 rules above are sometimes called "crisp" rules, because they "break off" suddenly. Fuzzy rules are a little different than crisp rules in that they do not break off suddenly.

Actually the Fuzzy Sets add-on does not really use fuzzy words like low, very high, etc. For one thing, instead of just 5 fuzzy sets very low, low, medium, high, and very high you can have 10 or 20 or even more if you like. So instead of words, we use 1 for the lowest, 2 for the next lowest, etc.

Of course, most people will have no idea what fuzzy set you should be looking for in order to buy or sell, so that's where the NeuroShell optimizer comes in. The optimizer will decide the total number of fuzzy sets, and which set you should have for a long entry, long exit, short entry, and short exit. Our Fuzzy Sets indicators can be used in Trading Strategies as well as neural nets. We have some that do a Fuzzy-AND of up to 10 fuzzy indicators, and other that do a Fuzzy-OR of up to 10 fuzzy indicators.

Neural Indicators NI are several types of neural networks packaged as technical indicators. They will probably appeal to those who like to experiment with neural nets, because there are several types, all with different features.

They are based somewhat on the "backpropagation" nets that we feature in our NeuroShell 2 classic network package, but there are two major differences. First, they are not trained with the old backprop algorithm. Second, they are not trained to predict anything, only to produce accurate buy and sell signals.

Here are the salient features:. NI provide signals from -1 to 1. The closer to -1, the stronger the probability of "don't' sell". NI are "unsupervised" neural networks, meaning that they do not need to be trained by showing them the correct answers, like most neural networks i. You do not teach them by providing any kind of actual output which they learn to reproduce, as with most neural nets.

NI "learn" how to give their signals based upon evolutionary pressure. The genetic algorithm GA in the NeuroShell Trader Professional or NeuroShell DayTrader Professional "evolves" NI that give better and better signals.

Survival of the fittest controls the evolutionary process as usual, where fitness is determined by how much money the NI make, or how good they work as inputs to other nets or indicators. Although anyone can use NI, neural network aficionados will love them because there are several highly technical neural network "architectures" from which you can choose. You do not have to understand how these architectures work in order to build profitable trading systems.

You can insert Neural Indicators into your trading systems and let the optimizer find the appropriate settings. Neural Indicators are highly technical from a neural network standpoint, and although they can be used by novices, they can only be fully understood internally by those who have a background in how neural networks function. This architecture has two different "activation functions" in the hidden neurons. These are called "Ward Nets" since Ward Systems Group invented them many years ago they first appeared in our classic product NeuroShell 2.

The genetic algorithm will find out how to pick the activation functions for you. Ward Nets include Ward2, Ward3, Ward4, Ward5, and Ward6, depending upon the number of inputs. This architecture has connections directly from inputs to outputs as well as the usual hidden neuron connections. This architecture also features connections from one hidden neuron to the next, like Turboprop 2 has. Jump Nets include Jump2, Jump3, Jump4, Jump5, and Jump6, depending upon the number of inputs.

This architecture analyzes not only the current bar of information to produce its signal, but it also reviews a condensed summary of the most recent bars as well. More recent bars receive more weighting than older ones.

Recurrent Nets include Recur2, Recur3, Recur4, Recur5, and Recur6. These are nets which are not fully connected between the input and hidden neural layers. This means that more inputs can be fed to them without increasing the number of weights drastically. The fact that less information can be stored in sparse weighting connections is compensated for by the fact that less weights allow better optimization. Sparse Nets include Sparse8, Sparse10, and Sparse We have implemented modified versions of all of the above nets.

The conditional version of each of these architectures produces a value of either true or false rather than a value between -1 and 1. These nets generalize very well, meaning they do not have a strong tendency to "overfit" or "curvefit" like backpropagation neural nets do.

Neural Indicators require the NeuroShell Trader Professional or NeuroShell DayTrader Professional, release 3. The Pattern Matcher add-on grew out of many requests by users who wanted to know if patterns in their data streams had occurred before in history, and if so, what type of activity followed those historical patterns.

Some users also wanted to identify a pattern in history and be alerted when a similar pattern occurs in the future. The Pattern Matcher add-on meets both needs by providing indicators that match patterns and revealing the subsequent activity. Pattern Matcher indicators work on any data stream in the NeuroShell Trader, Trader Professional, or DayTrader Professional.

The Pattern Matcher can find patterns in raw price data streams or indicators made from raw data streams. It is often advantageous to match patterns in indicators applied to prices rather than to the prices themselves, as you will see in a subsequent section of this document.

It is intended that the user treat the Pattern Matcher as an intellectual tool to provide input to one's own biological neural networks for discretionary trading, or as confirmation of other signals you may be obtaining in other ways. So what does this mean? It means that the Pattern Matcher is designed to provide answers to the questions that have plagued technical analysts since long before computers were born:. You will be making your own subjective decisions about whether or how to trade based on the information the Pattern Matcher is showing you.

These subjective judgments will be based on your own study and experience watching similar patterns, and based upon your decisions about what data streams in which to watch for patterns. Price streams like open, high, low, close, and volume may not be the proper data streams to be monitoring for patterns. Indicator data streams, in our experience, seem to provide a more reproducible pattern source.

At Ward Systems, we have used the Pattern Matcher in the way just described. We have found that there is less value in trying to feed Pattern Matcher input into either neural nets or rules. We believe the tool is a powerful resource which will help you even the playing field, so to speak, as you compete with professional traders who have years of experience recognizing and reacting to patterns in the markets.

They rely on their memories and intuition - you now have an analytic tool to bring to odds of success more in your favor. Furthermore, you should not assume that past patterns are an indicator of future performance. The pattern matcher may very well be a powerful tool for the contrarian trader too.

The markets are quite capable of reversing what usually happens after recurring patterns. If this were not true, it would be easy to predict and make money in the markets, and we all know that it isn't easy. The following descriptions of Pattern Matcher Indicators are abbreviated.

Match - The Match indicator takes a very recent pattern on the chart and displays the probability that other patterns in history on the chart match that current pattern. MatchPast - The MatchPast indicator takes a designated pattern on the chart and displays the probability that other patterns in both history and future on the chart match that designated pattern.

ProjectAvg - The Project Average indicator returns the average of all projections leads of the projection series for all pattern matches that are greater than the indicated projection threshold.

ProjectMin - The Project Average indicator returns the minimum of all projections leads of the projection series for all pattern matches that are greater than the indicated projection threshold. ProjectMax - The Project Average indicator returns the maximum of all projections leads of the projection series for all pattern matches that are greater than the indicated projection threshold.

ProjectStndDev - The Project Standard Deviation indicator returns the standard deviation of all projections leads of the projection series for all pattern matches that are greater than the indicated projection threshold. ProjectRange - The Project Range indicator returns the range of all projections leads of the projection series for all pattern matches that are greater than the indicated projection threshold. ProjectUpperB - The Project Upper Band indicator returns the upper envelope of all projections leads of the projection series for all pattern matches that are greater than the indicated projection threshold.

ProjectLowerB - The Project Lower Band indicator returns the lower envelope of all projections leads of the projection series for all pattern matches that are greater than the indicated projection threshold.

ProjectCount - Given a projection threshold, the Project Count indicator returns the total number of matches between the current pattern and patterns in history. ProjectPercent - Given a projection threshold, the Project Percent indicator returns the percentage of total number of matches between the current pattern and patterns in history.

The Turning Points add-on for the NeuroShell Trader series is based on the concept of finding local peaks and valleys in a price series. A turning point TP peak is defined as the point where the high is higher than or equal to any other highs in the neighborhood of the point. A turning point valley is defined as the point where the low is lower than or equal to any other lows in the neighborhood of the point.

The add-on contains indicators that do all of the following with respect to these turning points: We are especially fond of the probability indicators above, because many issues exhibit repeating cyclic tendencies which can be captured with this technique.

Of course, news and other factors can affect normal cyclic tendencies, and not every signal generated will be correct. However, there is plenty of capability in this add-on to build trading strategies that even we haven't thought of yet. The Turning Points add-on requires the NeuroShell Trader, NeuroShell Trader Professional, or NeuroShell DayTrader Professional, release 3.

NeuroShell Trader Features Data Brokerages Add-Ons Examples Videos FAQ Buy Now. Box Essex Junction, VT Voice: Adaptive Indicators Bowfort Wave Chande Momentum Oscillator Data Cleanse Datafile Utility Fuzzy Candlesticks IBFeed IBFeed Professional mYFeed Zero Lag Indicators. Bowfort Technologies Inc Memorial Drive Suite Houston, TX Voice: Jurik Indicators Jurik Indicators JMA - Jurik Moving Average World class noise elimination filter for market price data. Jurik Research Software South Arroyo Parkway Suite Pasadena, CA Voice: Mesa Software, Inc Sold by Ward Systems Group, Inc.

This add-on also includes more than 10 example charts and additional Trading Strategy templates. For more details, please view the product manual for this add-on BUY NOW. MESA91 - Mesa Software, Inc. MESA91 is as easy to use as any of the indicators built into NeuroShell Trader. Ted Achacoso Nature and its parts fluctuate in cycles. To learn more about CSSA, CLICK HERE Following is a brief overview of the indicators in the CSSA add-on: Entropy Indicators NEI Make your purchase safely and with confidence using our secure online ordering system.

Probably not but it may be just what you need to find profitable patterns in the market. The backbone of NEI add-ons Noxa Entropy Indicators is a powerful search engine for patterns that are resistant to entropy the tendency of systems to disorder. That means you will be able to trade compelling pockets of order that arise in the market.

NEI Prediction-Days Markets sometimes lock themselves into predictable futures. NEI Prediction-Days detects these events by searching for local histories with high predictability potential. NEI Shannon Entropy Shannon Entropy gives a measure of statistical regularity in price data, making it a good proxy for changes in market condition. You will be able to explore the market and select inputs that maximize their Mutual Information. NEI Transfer Entropy Transfer Entropy is a measure of information flow between two series.

It takes into account the amount of additional information required to represent future events. In essence, Transfer Entropy tells us which input leads which. You can see that some information flow between Oil service and Airlines stocks materialized in the form of islands whose tops happen to precede significant changes in trends 12 and early 34.

Particularly successful trading strategy example; two neural-nets were built with NEI indicators as inputs to cope with changes in market conditions out-of-sample backtest period in green: Richey Enterprises Sold by Ward Systems Group, Inc. Interchart Tools Renko Bars InterChart Tools 1 InterChart Tools 2 InterChart Tools