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Forest

Quantifiable Historical Price Patterns

Turning Visibility  Into Profit

Our Mission

Combining Big Data, Analytics & Cloud Computing into an easy to use  platform that levels the playing field for millions of underserved Retail Traders

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Data Engine

Data Engine

Free Basic & Premium Advanced Search.

Expected Moves

Expected Moves

Weekly Expected Moves & Price Zones.

Analytics Charts

Analytics Charts

Dozens of Detailed Analytics Charts for Insights.

Alert Engine

Alert Engine

Set & Manage Alerts on Price Conditions.

Trade Alerts

Trade Alerts

Notifications that go where you go.

Know Price Moves

Know Price Moves

Historical probabilities on price movements.

Knowledge Base

Knowledge Base

Help Guides, Instructional Videos, FAQ's and more.

Customer Support

Customer Support

24/7 Ticketing System to connect with experts.

Learn the Method

Learn the Method

Free Book! The Quantitative Directional Trading Method.

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 “History doesn’t repeat itself but it does rhyme”    - Mark Twain.

From Noise to Clarity

     Almost by accident - By overlaying price action with the weekly expected moves by options traders we began to see correlations- the market rhyming.  As we ran more scenarios, we found hundreds of patterns that repeat with very high statistical correlations of 80-95% across various time periods and implied volatility conditions.  And even the outliers are often correlated.  The repeated price conditions had similar characteristics when viewed in the context of their expected moves as priced by options traders.

     

     

 

 

These price conditions often begin and end at the same “zone” points.  They accelerate and reverse off key price levels that can be measured within this context.  After mapping virtually every price scenario of every week in the S&P 500 since 2018 we could see measurable moves that behaved similarly and so we measured the correlation. 

 

     Some of these moves were random but others were highly correlated.  In many cases they behaved the same way 80-95% of the time. 

 

     We extended the mapping of the S&P 500 to the, Nasdaq 100 & Russell 2000 across over 1500 price conditions for each week over a four-year period.   

Expected Move Illustration

      From the resulting hundreds of thousands of data points, clear patterns emerge that correlate across the same conditions across different time frames as well as different levels of volatility and even different indices.     

 

     There are many cases where price does the same thing in the same way over 90% of the time – that makes price direction over certain time periods highly predictable.  While the reasons for this price predictability can be debated, the fact that price has behaved this way is in evidence in the data.

 

     While there is no guarantee a price condition will behave the way it did 90% of the time in the past – it is highly useful to know which side of history you are on before entering any trade.

 

     In fact, mapping the major indices price movement against their expected moves by options traders, yields so many conditions and so much data that it requires a data engine and automation to extract the truths that were otherwise hidden from the everyday Trader.

 

     By leveraging our expertise in cloud technologies, big data & service automation we were able to bring together these capabilities into an easy-to-use platform delivered as an affordable service, that enables anyone to leverage the power of quantitative dynamics for their trading strategies.

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