Algotrading evolution

Algotrading evolution: what to earn on when robots wise up?
Algorithmic mechanisms have replaced manual trading — today up to 99% of Forex transactions are made not by people, but by trading robots. Robots are constantly developing and successfully do most of work instead of a trader. But a man’s knowledge, skills and intuition still remain in demand in a relatively new area – on cryptocurrency exchanges. In the article I will explain how artificial intelligence will change exchange trading and what a trader can earn on in the future.

Why algorithms trade better than people
A trading robot is not subject to emotions: it will always strictly follow the specified trading scheme; it will not lose its nerve.

The speed of a program’s response on market events is tens of thousands times higher than a man’s reaction. While a trader realizes that a quote had moved, a robot manages to open and close transactions on this movement for several times. For example, only a robot can trade in a scalping style, when transactions are done in fractions of a second.

Frequency of transactions and position holding time are key features, including for trading on cryptocurrency market where volatility amounts to hundreds percent in 24 hours and jumps of quotes are chaotic.

A robot can simultaneously analyze several currency pairs and that is priceless for basket trading. It is also crucial in case of cryptotrading: one robot can trace not only quotes of several pairs, but do it on several exchanges simultaneously. Such a robot will earn on, for example, starting to redeploy resources from one pair to another on those exchanges where it is profitable at a particular moment of time.

What robots cannot do
Despite the obvious benefits, algorithmic trading system cannot be called a “perfect soldier” on an exchange battlefield yet.

A set of a robot’s operational parameters and technical indicators, on which basis it makes decisions, are chosen and corrected by a human once, and may not comply with all conditions of a forming price chart.

A robot will not react to price outbreaks and will not show a critical deposit drawdown in a situation where its reaction is not programmed.

And another important aspect is that a human can timely react to market fundamentals – publication of macroeconomic statistics or geopolitical events, for example; while a robot is focused only on pre-set technical characteristics of a price chart.

What will happen next
The main prospect of trading robots development is connected with their potential ability of self-learning. Modern computing power allows to back-test robots on a long history of quotes just in few minutes. Using obtained data, one can later on simulate a variety of market situations. Robots are optimized and trained on neural networks and stochastic models, such as Monte Carlo simulations.

It looks particularly promising for cryptocurrency market that has just been shaped and has not gained a long history of quotes – robots can be taught from the very beginning of a historical process of cryptotrading.

Revealed statistical correlations will be used for forecasting of markets performance depending on multiple factors: it will become possible, for example, to combine formation of technical analysis patterns and upheavals in commodity exchanges.

A modern robot can easily operate just with several pre-set parameters. In some years a robot of the future will be able to maintain high operation speed and precision working with dozens and even hundreds of diversified variables.

Robots will become self-learning and will be able to correct their input parameters themselves. They will learn to replace non-optimal indicators of market situation on those that will work in that particular situation. It will be possible to insert several various strategies in a robot and it itself will determine which one should be applied in a certain market situation.

Example. If a modern robot has pre-set trading on the overbought/oversold levels, it will open transactions only in case of intersection of these levels. Such trading program will “sleep” on flats and can potentially lose the profit a scalper could earn during this time.

Based on a self-learning system AI, a robot of the near future will be able to switch to a scalping scheme, in case a quote moves to a sideways channel, and continue earning funds to its owner’s deposit.

Will algotrading safeguard the stability of the world financial system?
Many practitioners and theoreticians of algotrading predict that market crises and collapses can forever become the thing of the past: robots will be able to quickly quantify potential risks and avoid them.

Moreover, such algorithms can be inserted directly to microchips and thus you may program a hypothetical “global toggle” switching the market from a high-risk stage to a stable phase. It might sound crazy, but the idea of emergence of a specific “worldwide regulator” of non-protein nature is no longer a fantasy; and such system can act both on currency and stock markets and on commodity exchanges.

What traders will earn on when the market becomes unpredictable?
In this case a logical and slightly philosophical question arises: what about the global essence of the very trading, playing on the markets? After all, if somebody wins, should anyone lose? Will the only algorithmic scalping on small changes of quotes remain the fate of traders? There is no exact answer to this question yet, but the most young, non-stable and at the same time the most prospective sphere of trade – cryptotrading – seems to remain in question.

There are no distinct regularities here; the database accumulated for construction of statistic patterns for this market is still not large. Cryptoexchanges are agitated constantly; and even if an ideal system for trading decision-making based on technical analysis will appear, fundamental and human factors (panic, hype, new altcoins launch and opening of exchanges) will seriously influence the quotes – and therefore it will long remain possible both to make a fortune on cryptotrading and to lose shirt on it.