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How we forecast the short-term future of stocks & cryptos with AI

The nature of capital markets is determined by ups and downs. Geopolitical effects and investor sentiments influence prices. Today you have access to Terabytes of data in real time. But the human brain is not capable of processing this amount of information. As a result, traders and risk managers get overrun by data. Whilst the human brain gets overrun by the amount of data that is produced per second another technology is waiting for its deployment: AI. AI is able to learn from the past in order to predict the future. But financial data is difficult to predict. Every asset is different and operational success requires experienced traders. Building an AI driven platform requires lots of time, lots of developers and years of patience.

Historical vs. future data

There vast majority of available datapoints are historical datapoints. Every Terabyte of data was created in history. An analyst needs to access the data, filter the datapoints and finally run the analysis. The result is an individual assessment and mitigation of investment consequences. We call that future data. Every farmer knows that the best time to get seeds in the ground is when the soil is relatively dry, but right before a good soaking rain. Competition exists in agriculture, too. If farmers were today's investors every farmer would collect datapoints such as air pressure or humidity to calculate his own probability of a rainy tomorrow. And then they would wonder, why the big farmers are always winning with their AI.

About Y8

Y8 has built several AI models that predict the most likely future of various assets on a 24/7 basis. The main input parameters are market data, technical analysis data, asset specific data (such as blockchain data) and a secret sauce. The models are continuously improved and back tested.


The day-to-day trading market is driven by approx. 70% algorithmic trading. In 2020 Citadel said, that retail is 25% during peaks. Both participants leave traces in historical data. These traces explain how and when most market participants reacted to certain data points in the past. The sum of these traces is a “hidden” script, that was written with invisible ink. Y8 aims to reveal these messages. Y8 has different models for the same asset. An algorithm chooses the right model for the right situation. A situation is determined by several parameters such as regime class and volatility. Let's have a look at a specific model trained for QQQ and 4-hour time periods. Y8 always forecasts 13 future data points. The black dots are the real changes from one 4-hour candle to the next. The blue dots are the forecasted minimum changes by Y8. Here's a scatter plot of real price changes for timestep +3 in a back testing scenario where Y8 didn't know what's coming next. 74% of all blue dots (= forecasted price changes for this future timestep) are above / below 1 when the black dots (= real price changes) are above / below 1. That means, that in 74% of all cases QQQ closed higher 3 timesteps later when the forecast predicted a bullish scenario. In 36% of these back tested cases the Y8 prediction was wrong.

How to read the Y8 forecasts

Y8 forecasts look like this one: the forecast of BTCUSD starts with the vertical grey bar on the 28th of January.

Within a forecast we can see a maximum of 8 datapoints:

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. Y8 displays the back-tested results of the model that was used to predict the future of the selected asset. Two levels of accuracy displayed:

The following image shows a historical forecast. As you can see the real 4-hour candles of SPY moved perfectly within the forecasted price range of Jan 23rd

About Y8 and BLOCKSIZE

Y8 now has partnered with BLOCKSIZE to deliver crypto price predictions for bitcoin and ether based on market data sourced from BLOCKSIZE CONNECT. As a result, users of Y8 can get a crypto asset forecast which was not available before. More details on request.