What is the Probability of a YUCE-8 Forecast?

Let's have a look at the current chart of the week. On June 12th the randomly selected asset is LTC-USD with a time period of 1 day:

  • The forecast was created on 1st of June, 23:59 UTC

  • It forecasted a very bearish scenario for LTC-USD until the 18th of June

  • If you zoom into the chart you can see that the last closing price of LTC-USD was approx. 182 USD:




This is the full chart. As you can see the forecast of LTC-USD on 06-01 | 23:59 was extremely correct (in contrast to many, many Twitter influencers who predicted a massive bull run).



Now, how accurate is a forecast? The short answer: there's no guarantee. The only thing we can do is to measure the success of the previous forecasts. And that's calculated on a regular basis. The latest results of this calculation can be found in this heatmap:

The success of a model is determined by using a backtesting algorithm. After a new model is trained the algorithm will check how precise the forecast was in the last 90 time periods.

Let’s say today is t=-90 and a new model finished training. Then the backtesting algorithm will match the forecast of t=-89, t=-88, … with the real closing prices.

If the forecast of t=-70 is bearish for let's say t=-60 and both, the real closing price of t=-60 and the forecasted closing price of t=-60 is lower than the price of t=-70, then "timestep +10" will receive 1 point.


For LTC-USD 1d(ay) the resulting value is 70. That means that in 70 out of 100 cases during backtesting the YUCE-8 AI model predicted the a right direction of LTC-USD at timestep +10.



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