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You check the buy wall in the order book or the latest tweet on the coin’s feed for market-moving announcements or perhaps it’s your favorite Telegram chat room that you turn to for trading signals or a notification from a news site you rely on for up-to-the-minute information on cryptocurrency news and the coins you follow.
And of course, there’s also the tried and trusted technical indicators honed in the stock markets over many years that have been transferred wholesale for use in crypto trading markets.
Whichever is your favored channel or method to source and interpret the vital information you need to make your trading and investment decisions, chances are you are doing it by spending a lot of valuable time in a probably fairly haphazard and unscientific manner.
Squeezing cognitive bias and emotion out of trading
There has got to be a better way, right?
Yes, and there is. Blockchain projects such as Enigma and Signals, are attempting to fill the gaps between the world of professional traders, the many millions of crypto investors worldwide who are now turning to more active trading as they look to diversify their portfolios and the data scientists who are turning the firepower of new technologies such as machine learning to target crypto trading.
Technical indicators, social media and the Telegram messaging service that has become the go-to app for market participants seeking trading signals for crypto, are just some of the tools of this new breed of traders.
However, more often than not, things are more rudimentary. It would be fair to say that many traders rely on nothing more sophisticated than gut instinct or are drawn to make rookie errors such as buying high at the end of a rally and panicking into selling low because they let emotion get the better of them.
Human psychology plays games with traders. For example, it is psychologically easier to buy Litecoin at $180 than it is to buy Bitcoin at $11,700. This phenomenon of traders and investors overlooking the fundamentals of a coin in favour of selecting it on the basis of a seemingly low price, especially when it sells for less than a dollar or better still, less than a cent, is rampant and is similar to the penny stock phenomenon in equity markets.
New tools for new times
All of these mistakes, or at any rate skewed decision-making, can be avoided by bringing data science to the toolset already being used by professionals, and then putting these re-fashioned tools into the hands of today’s ordinary crypto traders.
On the face of it, this is being done by any number of new blockchain projects, but if you look a little closer none has developed an easy-to-use system that provides a robust testing ground for newbies and professionals alike to build their very own trading algorithms.
Mainstream indicators derived from the world of the chartists are being applied all the time in the cyryptomarkets but are often confined to the world of more experienced traders and they are not systematically married to other metrics such as in sentiment analysis.
Recognising chart patterns such as “head and shoulders”, “bull trap”, “cup and handle”, the “triple bottom” and so on are well-known patterns in price movements that the human eye and brain can be taught to recognise. These patterns can be analysed alongside other information such as tweets pertaining to a coin that contain the word “burn” and perhaps a date string, that taken together could provide a valuable price signal to trigger a buy trade. This is all commonplace in investment banking where resources have been ploughed into quantitative analysis for many years now.
Signals makes it easy for all of us to play
But now its time for the little person to have a look. Signals is creating a platform to achieve this by the application of machine learning and artificial intelligence to recognise patterns, both the established ones we have just mentioned in addition to the ones yet to be discovered – new asset classes have their own characteristics as far as price movements are concerned and crypto is no different.
There are also likely to be patterns that appear more often or less often as the crypto market matures. Assigning software as opposed to humans to the task of tracking, recording, collating and then analysing all those price points and their relation to other data will be a more complete, and therefore successful approach.
What is unique about Signals, compared with competitor Enigma, is its focus on enabling the average person with no computer programming skills or extensive trading experience to select indicators such as moving averages or the relative strength index simply by dragging them on to a canvas – or playground – along with, for example, sentiment analysis from crowd-sourced data, to create trading strategies built with a programmatic flow of statements and calculations.
If you are familiar with the drag-and-drop computing language developed by MIT Media Lab called Scratch, which is used to teach programming, then you’ll see where Signals is going with its fresh approach and how important it could be in jump-starting a revolution in trading technology and how investors interact with it.
Artificial intelligence that can interpret indicators and make decisions based on them – and learn from past decisions – is also part of the mix and will be extremely powerful not just in and of itself but precisely through the mass adoption platforms such as Signals are designed to facilitate. Many humans experimenting with many strategies, and learning from each other, is going to be more powerful than less complex arrangements.
Not just another trading algorithm platform
To take this further, Signals needs to be understood not as yet another trading algo offering in a one-too-many set up with the blockchain being used to deliver one trading strategy to any number of clients, or perhaps a handful of tweaked strategies depending on a clients risk profile in the manner of the robo-advisor approach that is spawning in mainstream financial services market. Or perhaps a platform does let you develop and test strategies but in a set-up that is so difficult to use it represents a barrier to entry for the average trader.
Signals is radically different because the trader is in charge of designing their own strategy.
And more than that, traders can also choose to follow the strategy of another platform user by copying a strategy from the marketplace. In other words, if your signals are good at what they do, you can make money from them by letting other make money from. Alternatively, you many still be developing, back-testing and tweaking your own strategy on historical data and may wish to buy a trading strategy from the marketplace while yours is still in development.
For machine learning to work to its full potential it must be able to train on massive amounts of data which requires the utilisation of the power of supercomputers. Signals has got that covered too because it plans to use the decentralised supercomputing power of blockchain projects such as SONM.
All of this, taken together, gets rid of the emotionally driven trading mistakes rooted in the cognitive dissonance that clouds judgement and will lose traders money. There is an old saying that 90% of new traders lose 90% of their money within the first 90 days of activity. That is scary, but it doesn’t have to be that way, as the innovative Signals project shows.
The token sale for its “data science powered marketplace off data-science powered signals for trading cryptocurrencies” starts on 26 February or if you want to get a bit more hands on first, take a look at the alpha.
