Connect with us


Algorithmic trading on crypto-exchange exchanges, drawing up of trading strategy



Every ten years a new market opens for public trade. So it was with commodities, stocks, options. Now a similar phase of crypto-active. All these markets initially showed increased volatility, trading volumes were low, there was no regulation, and derivatives did not yet exist.

Crypto currency has appeared relatively recently and is still characterized by increased volatility in comparison with other assets. High volatility leads to large-scale price movements and, with the right approach, makes a good profit.

For algorithmic trading in stock markets, you have to buy special software, get permissions from exchanges and pay for historical data on which the trading strategy will be developed. All this becomes a serious obstacle for ordinary investors.

On the other hand, most crypto-exchange exchanges provide simple and open APIs for trading. In other words, even a high school student can set up a workstation, run an algorithm, and earn money.

Kriptonok is so new that even strategies from textbooks on technical analysis, which have long become classics, work here. At the same time for a successful and profitable trade is enough for a typical PC.

How to trade in crypto currency?

Typically, traders tend to one of three approaches:

Fundamental analysis

Assesses the progress of the project, its technical aspects, market coverage and developer experience. For example, cryptoactivity without a real product on the market from the standpoint of fundamental analysis will be considered a weak investment, even if it is on the list of the ten largest crypto-currencies in terms of trading volume.

Analysis of moods

Some traders in the search for profitable opportunities conduct analysis of sentiment in Reddit, Twitter, social networks and the futures market. For example, a trader can find out that a certain cryptoactive will soon be listed on a large exchange, and based on this information, make a deal, assessing the impact of news on the mood of users and prices.

Technical analysis

Traders analyze the dynamics of quotations and the behavior of special indicators (of which there are a great many), trying to predict the further movement of prices. Technical analysis is very popular in the crypto-currency market.

This approach is much steeper than it seems at first glance. Together, the three elements of information give incredibly accurate signals about the opening and closing of positions. For example, you can use the following strategy:

Technical indicators MACD and RSI help to assess the direction and evaluation of crypto-active.

Even this simple strategy over the past year and a half ahead of the market on any two-month interval for most crypto assets – sometimes with a huge margin.

The right approach to successful trading

The ability to make money on the market with statistics is amazing! First of all, it is necessary to find hypotheses and trends that can be checked and automated using an algorithm. The program should work and earn money even when you are sleeping.

Let's look at an example of an algorithmic trading strategy. The development of its concept, analysis and configuration took more than seven months.

Hypothesis: if the price of a cryptoactive has fallen to an "unreasonably low" level, it will likely jump back with a high probability.

Soon we will return to how to determine this "unreasonably low" level. In the meantime, pay attention to how the price bounces off the line at number 3 on the charts. If this pattern repeats constantly, it can become a good basis for strategy. You just need to buy an asset when the price falls below the line, and sell when it bounces off after a while.

Notice how the price bounces off after the puncture of the green line.

The signal line in the chart above is designated as "2 standard deviations from the moving average". Let's see what that means.

Basics of statistics: Standard deviation

Any normal random variable satisfies the Gaussian probability distribution. The peak of the distribution corresponds to the mean value, and the standard deviation determines the possible variance of the values.

From the statistics, we know that 96% of the values ​​of the normal distribution are within two standard deviations (σ) from the mean. In other words, the probability that some price will go beyond the 2σ-interval from one side or the other is less than 2%.

Prices of crypto-currency assets can not be called normally distributed, however, when they exceed two standard deviations, they are likely to return to the center with a high probability. The above graphs confirm this.

The approach to compiling the algorithm of the trading strategy

The formulation of the hypothesis always begins with guesswork. The trader examines the charts, visually verifying his idea. Then he develops the appropriate algorithm and tests it at past prices of different crypto assets at different parameters.

For example, you can test the algorithm at different time intervals (5 minutes, 15 minutes, 30 minutes, 1 hour) and for different thresholds (2σ, 2,5σ, 3σ) on a variety of crypto assets. This will determine which combination of values ​​gives the highest percentage of reliable signals without sacrificing the profitability of each transaction.

The process of developing an algorithmic trading strategy.

Once the parameters are optimized, you can start real trading, simultaneously watching its performance (profitability, slippage, Sharpe ratio, etc.). Having convinced of the reliability of the algorithm, you can increase the amount of capital intended for trading.


Over the past seven months, this strategy has not only brought profit, but also made a lot of interesting observations about trading in the turbulent market:

  • Over time, the profitability of the algorithm decreases.
  • Algorithms that work well with a small capital (say $ 10,000), cease to make a profit if it is greatly increased (for example, up to $ 100,000).
  • The more difficult it is to conceptualize and program the algorithm, the longer it retains its advantage.
  • Most algorithms correlate with prices – some work better in a growing market, others do well with a falling one. It is necessary to intelligently compose a portfolio consisting of different algorithms, so that they compensate for possible weaknesses of each other.

Algorithmic trading is a constant pursuit of perfection. Markets never sleep and all the time evolve. The trader will simply lose the advantage if he stops implementing new and unique trading strategies.