I Know First Algorithmic Market Prediction Services
Understanding What We Do
I Know First is a financial services firm that utilizes a state of the art self-learning algorithm to analyze, model and predict the stock market. The algorithm is based on artificial intelligence, machine learning and incorporates elements of artificial neural networks as well as genetic algorithms to model and predict the flow of money of almost 2,000 markets from 3-days to a year: stocks, ETF’s, world indices, gold, currencies, interest rates, and commodities.
Our retail products offer hundreds of pre made packages such as the Top 10 Aggressive Stocks Package, Top 10 Small Cap Stocks Package, and Top 10 Commodities Package which can be ordered directly online.
We also work with many institutional investor such as investment banks, hedge funds, insurance companies and credit groups. Prediction tables for such clients are much more comprehensive, sometimes including hundreds of stocks, indices, and gold forecasts for both the long and short positions. We offer customized packages made to suit your exact needs.
Our Product: I Know First Heat Maps
A prediction file will always include 6 heat maps with the 3 days, 7 days, 14 days, 1 month, 3 months, and 1 year prediction maps. In each forecast by the algorithm, there is the stock/asset, signal and the predictability indicator. The signal is the number in the middle of the box flush left. The predictability is the number at the bottom of the box. At the top, a specific asset is identified. This format is consistent whether you are receiving the Top 10 Stock Predictions + S&P Forecast or the Top 10 Commodities Forecast or any other I Know First prediction for that matter.
In this particular Top 10 Stocks Forecast from November 27th 2013, XOMA had the strongest 1-month signal but did not have the strongest predictability. The importance of each indicator will be discussed in the next few sections. As the asset is in a deeper green color box, this indicates that the algorithm is very bullish. XOMA had a gain of 61.45% in 1-month from the forecast date. To see how the rest of these assets performed according to the forecast click here.
This indicator represents the predicted movement direction/trend; not a percentage or specific target price. The signal strength indicates how much the current price deviates from what the system considers an equilibrium or “fair” price.
Analogy with a spring: The signal strength is how much the spring is stretched. The higher is the tension the more it’ll move when the spring is released.
The signal strength is the absolute value of the current prediction of the system. The signal can have a positive (predicted increase), or negative (predicted decline) sign. The heat map is arranged according to the signal strength with strongest up signals at the top, while down signals are at the bottom. The table colors are indicative of the signal. Green corresponds to the positive signal and red indicates a negative signal. A deeper color means a stronger signal and a lighter color equals a weaker signal.
This measures the importance of the signal. The predictability is the historical correlation between the prediction and the actual market movement for that particular market. For each asset this indicator is recalculated daily. Theoretically the predictability ranges from minus one to plus one. The higher this number is the more predictable the particular asset is. If you compare predictability for different time ranges, you’ll find that the longer time ranges have higher predictability. This means that longer-range signals are more important and tend to be more accurate.
* Stocks with the strongest signal and largest predictability are preferable.
To learn more about our product please use the following links
For information about private investor products click here
For information about institutional investor products click here
For the most recent I Know First Research articles and news click here
Want to know just how accurate our predictions are ? click here
Contact us with any questions: email@example.com
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