One year ago, Cointelegraph launched Markets Pro, a subscription-based data intelligence platform. Bitcoin ( ETH0_) traded at $40,200 on that day. Today’s price of $41,800 is a 4% increase over the same period. A market-pro’s key indicator VORTECS(tm), yielded a 20,573% return over the same period. This is what it means to retail traders like yourself.
How do I earn my 20,000% per year?
The short answer is no. You can’t. This doesn’t mean crypto investors can’t massively increase their altcoin trading skills by following the same principles that lead to this amazing ROI.
Live testing of different VORTECS(tm-based trading strategies began on the day the platform launched. The headline shows the result. This is how it works.
The VORTECS(tm), Score is an AI-powered trading indicator that analyzes each digital asset’s history and identifies multi-dimensional combinations trading and sentiment metrics that are historically bearish or bullish. Consider a scenario where Solana (SOL), receives an additional 150% in positive tweet mentions, along with a 20%-30% increase in trading volume, and its price jumps dramatically within the next two-three days.
Upon detecting a historically bullish arrangement like this one in, say, SOL’s real-time data, the algorithm will assign the asset a strong VORTECS™ Score. The conventional cutoff for bullishness is 80, and the more confident the model is that the outlook is favorable, the higher the Score.In order to get a sense of how the model performs, starting from day one the Markets Pro team live-tested a number of hypothetical trading strategies based on “buying” all assets that cross a certain VORTECS™ Score and then “selling” them after a fixed amount of time.
These transactions were executed in a spreadsheet rather than an exchange (hence no fees to eat off the gains), 24/7, and involved complex algorithmic rebalancing to ensure that at any given moment all assets that hit a reference Score are held in equal shares in the portfolio. In short, following these strategies was something only a computer could do.
The winning strategy, “Buy 80, Sell 24 hours” entailed buying every asset that reached the Score of 80 and selling it exactly 24 hours later. This algorithm yielded a hypothetical 20,573% of gains over one year. Even among other humanly impossible strategies, it is an outlier: the second-best one, “Buy 80, Sell 12 hours,” generated 13,137%, and number three, “Buy 80, Sell 48 hours,” yielded a “mere” 5,747%.
Down to earth
What these insane numbers show is that the returns that high- VORTECS™ assets generated compounded nicely over time. But what’s the use if real-life traders could not replicate the compounding strategy? A more practical way to look at the VORTECS™ model’s performance is through average returns after high Scores. No fancy rebalancing, just a plain average price change that all high-scoring tokens demonstrated X hours after reaching the Score of Y. Here are the numbers:
These look much more modest, don’t they? However, if you think of it, the picture that these averages paint is no less powerful than the mind-blowing hypothetical annual returns. The table demonstrates robust positive price dynamics after high Scores, averaging across all types of assets and in all market situations that occurred throughout the year.
The trend is unmistakable: tokens that hit VORTECS™ Scores of 80, 85, and 90, tend to appreciate within the next 168 hours. Higher Scores are associated with greater gains: the algorithm’s stronger confidence in the bullishness of the observed conditions, indeed, comes with greater yields (although higher Scores are also rarer). Another important factor is time: the longer the wait after a reference threshold is reached, the greater the average ROI.
In this sense, rather than trying to follow the complex “Buy 80, Sell 24 hours” algorithmic strategy (which is, again, a futile exercise), real-life traders could maximize their fortunes by buying at higher Scores and holding for longer times.
Varying predictability
A separate stream of internal Markets Pro research looked at whether some coins are more prone than others to exhibit historically bullish trading conditions before dramatic price increases. This turned out to be the case, with tokens like AXS, MATIC, AAVE and LUNA leading the pack in terms of the most reliable positive price dynamics following historically favorable setups. Overall, the majority of frequent high-VORTECS™ performers delivered robust positive returns.
After a full year in operation, these disparate pieces of quantitative evidence – the mind-bending ROIs of algorithmic live-testing strategies, high-VORTECS™ assets’ sound average gains, and individual coins’ steady average returns after high Scores – present a compelling case for the utility of the “history rhymes” approach to crypto trading.
Obviously, a favorable historic outlook, captured by a strong VORTECS™ Score, is never a guarantee of an impending rally. Yet, an extra pair of algorithmic eyes capable of seeing through and comparing across billions of historical data points to alert you of digital assets’ bullish setups before they materialize can be an incredibly powerful addition to any trader’s toolkit.
