To Earn on Bitcoin. Three Steps to Creating a Trading Strategy in the Crypto Market
Eugene Dubovoi, CEO and a founder at SIMDAQ, wrote an article for the Forbes.ru. We present this article in English and wondering if you have thoughts about creating trading strategies. Share your experience in our community chats!
At the end of the last year, bitcoin updated price records — since the beginning of the year, it got expensive more than 16 times, but later the crypto asset market demonstrated a deep correction and stagnation. To earn on such a volatile asset, knowledge in technical analysis will come useful for investor. Will coming of large investors and the launch of futures, which allow speculating to bear, add volatility? Or on the contrary, will they smooth out the usual for the cryptocurrency market jumps by 20–30%?
You can ask these and other questions, which almost daily explode media field. Another option is to fall back to a technical analysis of markets and strategies based on it, which take into consideration all available information and the reaction of the markets.
The technical analysis takes on more weight when it comes to cryptocurrencies and tokens issued during ICOs, as it is difficult for them to find basic data for fundamental analysis: there are few reports of companies and so on in this area. The technical analysis is well suited for developing short-term and utilitarian trading strategies.
Difficult Market
More and more investors are involved in transactions with crypto-currencies or plan to do so. According to various estimates, the number of active private traders is 3–6 million now. Even without planning for active trading, new players can use technical analysis and trading strategies to avoid costs when revising their portfolio in a volatile market with a specific infrastructure.
Any participant of the cryptocurrency community has to deal with exchanges on a regular basis when buying or selling a cryptocurrency. Owners of cryptocurrencies trade through both centralized and decentralized exchanges.
The model of centralized exchanges managed to compromise its reputation, but continues to operate. Thus, MtGox, one of the largest stock exchanges, closed in early 2014 due to theft of 321 million yen in bitcoin equivalent.
In August 2016, Bitfinex, another exchange was suspended due to hacking. Hackers stole 120,000 bitcoins. The model of decentralized sites is that users trade directly with each other without an intermediary represented by a stock exchange or a broker.
For example, the DEX exchange operates in such a way, which is integrated into the infrastructure of the Waves blockchain platform. It offers the exchange of cryptocurrencies directly between users without intermediaries.
Why Do You Need a Strategy?
The development of a trading strategy is especially relevant for a participant who doesn’t prioritize receiving quick benefit from transactions, but wants to simply change the composition of his portfolio or exchange a cryptocurrency for fiat money (traditional currencies).
Such transactions are associated with possible losses on spreads — the difference between the current sell and buy market price. In case of insufficient liquidity in the market, you can lose money on the difference between the maximum buy price and the minimum sell price.
An automated trading strategy can help both reducing losses on spreads and generating profits. You can buy or sell a cryptocurrency at a market price or leave a pending order at your desirable price on the exchange. All orders fall into a so-called order book. It includes orders for the sale and purchase of a cryptocurrency for a price different from the market one.
Buy orders with a price below the market will be less frequent, and those ones with a price above the market will be more often. The same is true with sell orders: those ones with a price above the market will be accepted less often, and those ones with a price below the market will be more often. With the help of market analysis, it is possible to set the price of a buy/sell order of a cryptocurrency that is different from the market one for a trader. In this case, the transaction will be activated with a probability of 90%.
In order to go beyond the “buy and hold” approach and not to make panic actions after reading the next portion of news, you should go through three stages of developing your own trading signals and automated strategies based on technical analysis.
Basic skills of understanding the market and technical analysis are acquired by analyzing a large number of charts to recognize and summarize the patterns seen that characterize the current situation between supply and demand.
Backtesting systems are the most effective tools here. The further development process, like any evolutionary process, is connected with the exchange of experience within the community. At the beginning, the community member listens more and is fueled by ideas, and finally, he/she starts sharing his experience and contributing.
The final stage of developing a trading strategy is the complete formalization of trade rules. The strategy will always be subjective without this, and it won’t be possible to test it on a sufficiently representative sample. Complete formalization allows you to program the algorithm and understand how it behaves in a wide range of historical situations, and then identify its strengths and weaknesses and improve it.
Step 1. Study the Statistics
Hypotheses about the adoption of trading decisions are generated in the process of trade. As a result of viewing a large number of stock charts, you notice certain patterns, repeated forms and figures of charts. Six months in historical data of cryptocurrency trading is enough to formulate a hypothesis about which market signals exactly indicate the expediency of buying or selling a currency. The process can be greatly accelerated by simulating trades on historical data (backtest). Using these data is possible to track the fluctuation of the selected cryptocurrency from the very moment it appeared on the market and get an idea of technical analysis.
At this stage, the trader may face difficulties — the lack of the necessary tools, historical data on the results of earlier trades. Brokers and trading platforms receive their commission regardless of whether a trader’s transaction is profitable or losing. Their main goal is to teach the user to work with the interface of the trading terminal, so that he/she should start open positions as quickly as possible. Trading services offer demo accounts for training. Their weaknesses are that demo trading is conducted in real time, without analysis of historical data.
Professional programs, such as Metatrader or WealthLab, allow using historical data: a list of transactions by periods, trading volumes and order books. The data helps to quickly carry out a trade simulation. For example, you can go through several years of the cryptocurrency trading during a day. Wealth Lab license will cost $799 for one trader. The software itself will require installation and configuration to work, as well as the need to obtain historical data that will be loaded for analysis. That is, the problem of searching for qualitative historical data is available.
However, this is already a progress. Just 10 years ago, for effective trading simulation, you had to print out or slowly scroll the trading charts on the screen and record the accepted trading decisions in a table.
Step 2. Connecting the Collective Intelligence
The next stage, which I recommend not to miss, is interaction with the community of market participants in one or another format, discussion their observations, getting to know the opinions and experiences of other traders of different levels.
Sharing experience and transferring knowledge in any field are a basis for development. If you ignore the experience of other traders and develop a strategy on your own, it’s difficult to make a sober estimate and test the hypothesis of a trade decision. Many traders are afraid to disclose their insights. But the downside of the coin is the lack of constructive criticism and a fresh look at his/her own hypothesis.
Even if you don’t have close colleagues and friends who can help you, you can discuss strengths and weaknesses of your strategy invented, get feedback, as well as disclose your portfolio and trade signals on such platforms as Cindicator, Cryptocompare or eToro, which contain elements of social trading. A number of traders also broadcast their trading strategies on Twitch.tv, a streaming platform.
Step 3. Algorithm Formalization
The trading strategy can be considered to be completed only after the algorithms for making trading decisions having been completely formalized. The formalization consists in developing rules by which a trader decides whether to purchase or sell an asset. They are formed from a trader’s experience, analysis of historical data and skills developed on the stock simulators.
Full formalization allows carry out automatic testing on a large number of historical data in a short period of time. It is enough to write down the rules in the trading simulator and run the test. The test will reveal whether the strategy really works as intended or whether it has weaknesses that need to be improved. For example, it may turn out that the formed strategy works only on the growing market and it will generate losses during the period of stagnation.
Creating a full-fledged trading algorithm may require programming skills, but now services are starting to appear that greatly facilitate this process. A modular algorithm editor, which, according to the principle of operation, reminds of the familiar MetaTrade platform interface to traders, can be a solution in this case; certain characteristics of the market or cryptocurrencies are registered with the help of graphic modules there. Using such modules, you can write a trading algorithm.
The process of developing trading strategies is cyclical, and we often return from step 2 or 3 to manual trading simulation using historical data to optimize a trading rule. The return is due to the receipt of new information or portions of data when communicating with other traders to improve the strategy and form a new hypothesis.
The complexity of the passage through these three steps is the imperfection and different intended purpose of the tools. Each step has to be done in different software environments, usually without the ability to import data and synchronize them. In the near future, solutions that will offer a single environment for the full cycle of developing trading strategies will be in demand for traders.
