Jeffrey Gibby

Predicting Price Action Using Probabilities

By Jeffrey Gibby,

Technical systems involve the use of technical indicators, chart patterns, or price action to enter and exit a trade.  
Many successful traders use back testing to help them identify the accuracy of a given system.  It’s a good idea that is helpful for traders in quite a few ways.  It helps them to understand: 

  • The frequency in which they will trade the markets.
  • The systems risk and reward ratios
  • Open and Closed position draw downs
  • Expectations of profit and/ or losses arising from using a specific method to trade 

Technical traders use systems to trade the market like a business plan.  Their rules are well laid out and established in advance.  It is their business plan for trading the market and testing that plan allows you to understand your business.  It’s a great tool to help traders prepare both emotionally and financially for trading. System Testing is a great tool and I’d recommend it for traders of all skill levels.

Trading systems use well indicators,  price and volume, and chart patterns to produce well defined entry and exit points.  They are objective not subjective.  As such they are easy to interpret and understand when applied to your trading.  

One of the questions, a lot of traders have is what is the expectations for price after my buy signal has occurred on a chart?  For example, if you are trading with a Bollinger Breakout buy signal, is the price likely to rise?  How much?  How likely?  Where is the price action likely to be afterwards?  What would this price movement look like on a chart?  

At MetaStock, our engineers designed our Forecaster module to help traders answer these questions.  I find it’s beneficial to help establish price targets, stops, and even to confirm entries.  It can statistically analyze over 70 different technical events and give you a visual price projection of likely prices. 

Let’s take the example of the Bollinger Breakout buy applied to a chart of the Dow ETF (DIA).

In this chart, the Bollinger Band Break out signals are identified by the yellow markers on the chart.  These are called event markers. 

The software takes these event dates to analyze price movement after the event to generate a probability of price movement.  It looks to see what happens with price movement after the event dates. It can be easy to get a bit overwhelmed by the amount of data generated by the forecaster.  However, the forecaster takes these statistics and visualizes them in a very easy to understand format.

The product of this analysis is a Forecast Cloud.  The Forecast Cloud identifies the probability of price movement after a given event.  Here’s an example of a Forecast Cloud for DIA:

On the right hand side of the forecast cloud, you will see a probability scale. You’ll notice that brighter colors indicate a higher probability of price action.   Orange and yellow equate to a 90%+ probability of a certain price being in a certain area, where the darker areas indicate a lower probability.   Underneath you have a measurement of time after the event.  Let’s look at a few examples to clarify some examples.  

Look at the portion of the cloud I’ve identified as A.  Notice a few things about this location: 

  • The color is purple. The corresponding color for this price is roughly 70%  
  • The nearest horizontal axis marker is at 14 bars after an event.  Meaning this is about 14 days after the Bollinger        Breakout signal  
  • The closest Vertical access to this event marker is 0%  
  • This means historically, between 70 and 80% of the time (represented by the purple color), prices have passed    through this region.  

Based on this region it represents a 0% increase in prices within 14 bars.  

Looking at point B on the cloud, we can make similar assumptions.  30 days after the event triggers, the price has declined 2 percent between 70 and 80% of the time after the Bollinger Breakout Triggers.     

Looking at point C we can determine that 30-40% of the time the price is between 0 and -2% of its initial price after 90 days after the cloud formation.   

It is important to point out about the Forecaster and the analysis that is being done under the hood.   The Forecast Cloud is not exclusively using statistics to calculate and display the cloud settings.  It uses an extensive set of statistics in its calculations, but it also uses a complex set of patent-pending, proprietary algorithms to allow for expected fluctuations in pricing from its historical patterns.

Once a cloud has been generated, it can be overlayed on the chart.   This is extremely helpful in determining probable price action following an event.  It can also display price action 180 days out into the future. 

The Forecaster includes 40 built in event recognizers.  These cover a broad range of price, and candlestick events.  

In addition, traders that like to use chart patterns have the ability to easily create their own patterns based on their own patterns.  Any pattern can be drawn using the Forecasters drawing tools.  This means you can easily identify your chart patterns on a chart and easily perform statistical analysis using the tool.

In this example, I’ve created the bottom formation of a V Pattern.   There are options for your drawn patterns for shape, number of price bars, pattern sensitivity, and the focus for the cloud on the chart.  Once you’ve completed your hand drawn pattern, you can identify your entries and exits on a chart using event markers.

Using the hand drawn patterns allows you to easily identify your patterns on a chart.  It also provides an event driven forecast cloud.

One of my most interesting uses of the Forecaster is to use recent price activity to establish a pattern.  Most of the time when I am using the Forecaster, I’ve already made a decision to buy or sell a specific instrument.  You can create a forecast event using current data by defining it on a chart. 

As an example, let’s say that we are looking at a short opportunity for DIA on June 15 2016.  Using the Forecaster, I can create a pattern based on any of the available chart data.

In this example, I’ve taken the last 14 days of chart data to establish a hand drawn pattern.  Once created, I can scan the chart and get a good idea of the following:

  • How often this price pattern has happened in the past
  • What price activity has happened after this event
  • What the probably price outcome is after the forecasted event.  

Here’s a graphic of the forecast cloud generated from the June 15th DIA event:

Here are the assumptions we can make from this chart when we understand the forecast cloud.

  • This event happened four times since 2011
  • DIA has a probability of 60 to drop to as low as 167.5 between July 8th and July 15th
  • DIA has a probability of 60 to 70 to then raise up to 180 by mid September 

I find this information to be extremely valuable to help me confirm my trading decisions, set profit targets, and identify an exit strategy.   It’s a great tool in MetaStock and something I would recommend you include in your trading arsenal.  In case you aren’t familiar with MetaStock, the software has been rated number one in its price category by the readers of Technical Analysis of Stocks and Commodities 24 times in a row.  It is designed to help traders by finding the right strategies on the right stock at the right time.    

Watch a Video on the MetaStock Explorer Here!


Jeffrey Gibby

Jeffrey Gibby has been working for MetaStock for over nineteen years. He is currently in charge of new business development and works to create new MetaStock distributors and partners worldwide. 

Mr. Gibby works with training companies to help people learn the power of MetaStock. He has spoken to traders from around the world and has trained people on how to use the software and trade various markets. Among his areas of responsibilities are the management of new products and services for MetaStock and creating strategic partnerships. 

Disclosure: The author of this article had an active position in DIA during the writing of this article.