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Even after the pullback, this crypto trading algo’s $100 bag is now worth $20,673


Bitcoin (BTC) was trading at roughly $40,200 exactly a year ago. And its current price of $41,800 represents a 4% increase year-over-year. Over the same time period, an automated testing method based on Markets Pro’s key indicator, the VORTECSTM Score, returned a 20,573% ROI. Here’s what it means for you and me as retail traders.

How can I get my 20,000% a year?

You can’t, to put it succinctly. No other human being is capable of doing so. However, utilising the same ideas that underpin this eye-popping ROI, crypto investors may significantly improve their altcoin trading game.

The headline figure is based on live testing of several VORTECSTM-based trading techniques that began on the platform’s debut day. This is how it goes.

The VORTECSTM Score is an AI-powered trading indicator. That sifts through the previous performance of each digital asset to uncover multi-dimensional combinations of trading and social sentiment variables. That have historically been bullish or bearish. Consider a scenario in which Solana (SOL) receives an additional 150% of favourable tweet mentions along with a 20% to 30% increase in trading volume versus a flat price. And its price surges dramatically within the next two to three days.

The higher the Score, the more confident the model is in the positive outlook

The algorithm will assign a strong VORTECSTM Score to the asset. If it detects a historically bullish arrangement like this one in, say, SOL’s real-time data. The traditional bullishness threshold is 80, with the higher the Score, the more confident the model is in the positive outlook.

To get a sense of how the model works, the Markets Pro team has been live-testing a number of hypothetical trading strategies. Based on “buying” any assets that reach a particular VORTECSTM Score. And then “selling” them after a specified period of time since day one.

These transactions were carried out in a spreadsheet rather than on an exchange. (Therefore no fees to eat into the gains), 24 hours a day, seven days a week. And involved complex algorithmic rebalancing to ensure that all assets that hit a reference Score were held in equal shares in the portfolio at any given time. To put it another way, only a computer could implement these tactics.

The winning approach, “Buy 80, Sell 24 Hours,” involved purchasing every asset with an 80-point score. And selling it exactly 24 hours later. Over the course of a year, this programme generated a notional gain of 20,573%. It’s an anomaly even among other humanly impossible strategies. The second-best, “Buy 80, Sell 12 hours,” created 13,137%. And the third-best, “Buy 80, Sell 48 hours,” produced a “mere” 5,747%.

Down to earth

These ridiculous figures illustrate that the returns generated by high-VORTECSTM assets multiplied nicely over time. But what good is a compounding approach if real-world traders can’t replicate it? Average returns after high Scores is a more realistic approach to look at the VORTECSTM model’s performance. There was no complex rebalancing, simply a simple average price adjustment. That all high-scoring tokens showed X hours after hitting Score Y. The figures are as follows:

Don’t these appear to be far more modest? However, the picture painted by these averages is just as strong as the mind-boggling possible annual returns. The table shows consistent positive price dynamics following high Scores, averaging across all asset kinds and market conditions over the course of the year.

The pattern is clear: tokens with VORTECSTM Scores of 80, 85, or 90 tend to gain in value over the next 168 hours. Better scores are linked to higher profits: the algorithm’s increased belief in the bullishness of the observed conditions is accompanied by higher returns (although higher Scores are also rarer). Another key consideration is time: the longer you wait after reaching a reference criterion, the higher your average ROI will be.

Predictability varies

Internal Markets Pro research looked into whether some coins are more likely than others to exhibit historically bullish trading conditions prior to significant price gains. This proved to be the case, with tokens such as AXS, MATIC, AAVE, and LUNA leading the field in terms of the most consistent positive price dynamics following historically favourable settings. Overall, the majority of high-VORTECSTM performers produced strong positive returns.

These disparate pieces of quantitative evidence – the mind-boggling ROIs of algorithmic live-testing strategies, the sound average gains of high-VORTECSTM assets, and individual coins’ steady average returns after high Scores – present a compelling case for the utility of the “history rhymes” approach to crypto trading after a full year in operation.

Obviously, a positive historical view, as expressed by a high VORTECSTM Score, is never a guarantee of a coming rally. However, having an extra set of algorithmic eyes capable of sifting through billions of historical data points and alerting you to bullish setups in digital assets before they happen can be a very useful addition to any trader’s toolbox.

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