Bitcoin trading is still a new concept for many, but quite recently, it has gained the interest of investors. According to a recent report, Bitcoin reached a striking new level of around $67,000 a few days ago.
This article helps you learn about Bitcoin right from the basics such as the meaning, working and reasons to opt for algorithmically trading this cryptocurrency (Bitcoin) to the advanced information such as trading strategies and what should be avoided.
- What is Bitcoin?
- What is Bitcoin trading with algorithms, and how does it work?
- Why go for Bitcoin Algo trading?
- Which quantitative trading strategies can be used for crypto trading using algorithms?
- Don’ts while algorithmically trading Bitcoin
- Learning resources for Bitcoin
What is Bitcoin?
Bitcoin is one of the major cryptocurrencies in terms of market cap value and leads the chart when compared to others such as Ethereum, XRP etc.
Bitcoin (₿) is a decentralised digital currency that is not regulated by the central bank and can be sent from user to user on the peer-to-peer bitcoin network without the need for intermediaries. Transactions are verified by network nodes through cryptography and recorded in a public distributed ledger called a blockchain.
What is Bitcoin trading with algorithms and how does it work?
Bitcoin trading with algorithms is the way of executing the trading orders by coding the execution instructions. In simple words, you program the system with the preferred entry/exit instructions and the system executes the trade orders as per the instructions.
Working part of Bitcoin algorithmic trading takes place by communicating with the crypto exchanges directly. Algorithms offer exceptional speed and efficiency, much lesser errors than manual trading and are not based on emotions.
Also, trading on crypto exchange requires you to authorise your algorithmic trading system to access your crypto account via API keys. This authority to trade can be withdrawn at any time, in the same way as you grant the system this authority.
The algorithmic trading system goes through these three steps every time during the trading process:
- Generating the signal
- Allocating risk
- Execution of the trades
Generating the signal
This is the first step in which you need to generate the signal for entry and exit by coding the algorithm. For signal generation, a trading strategy is used. There are some crypto trading strategies that you can choose from apart from the equity trading strategies (mean reversion, momentum etc.) such as Ichimoku cloud strategy, calendar anomalies and divergence strategy.
Risk allocation is another phrase for risk distribution which is done in accordance with the set parameters and rules set by the trader. The programmed system (with algorithmic codes), then, decides the quantity and how to allocate the capital.
Execution of the trades
This is the final stage in which Bitcoin or any cryptocurrency is bought or sold. The execution stage acts upon the pre-configured or preset trading signals or strategies. The signals are converted into API key requests that the crypto exchange understands and thus, the exchange then executes the process.
Why go for Bitcoin Algo trading?
Bitcoin algorithmic trading is a well-known approach adopted by most financial market traders across the globe. The investment in terms of time and effort to learn algorithmic trading is once but the results go a long way.
With algorithmic trading, a trader is benefited in the following ways:
- Emotionless trading
- Faster decision making
- Accurate predictions regarding the value of the underlying assets
- Can backtest the historical data
- Paper trading before live trading
- Risk management
The biggest benefit of Bitcoin algorithmic trading is that the emotions take a backseat since a programmed trading system does not have human emotions. With human emotions, come errors in judgement, decision making and thus, the probability of a lot of losses.
Especially during times of volatility, it is extremely difficult for human traders to keep their temperaments in check. But it is not so with the algorithmic trading system.
Faster decision making
Algorithmic Bitcoin trading is much faster than manual trading with regard to decision making since the system can act within a few milliseconds. The system only follows the instructions that it is pre-programmed with and acts quickly in accordance with the same.
Moreover, the algorithmic system can perform millions of computations and transactions across the time zones as well as markets instantly and simultaneously. Even before a human trader can think of buying or selling manually, the programmed system will be already done making multiple decisions and trades for the trader.
Backtest the historical data
The algorithmic trading system’s one of the most essential steps is to backtest the historical data so that the predictions are perfectly accurate. Backtesting does not “predict the future” because that is, of course, not possible for anyone. Still, it at least increases the likelihood of the predicted performance of the stock or an underlying asset.
Paper trading before live trading
It is so much better to practice before you start anything new. Be it cycling, driving a car or flying a plane, practice makes a man perfect! Not using the real money, and using the paper money instead, helps the trader to be ready and confident in the real market with real money.
Risk management is one of the most important steps of algorithmic trading, be it crypto trading or another financial market trading such as stock, commodity etc.
For example, the price fluctuation of Bitcoin occurred due to uncertainty regarding its success. Nevertheless, you can keep your invested capital safe if you follow risk management practices such as portfolio optimisation, hedging, stop loss etc.
Also, crypto exchanges suffer from over exhaustive trade order executions during high volatility times, which leads to the website server going down, whereas, the APIs still keep running.
Hence, you get prevented from trading or closing your position manually as and when needed during volatility. The simple solution is to go algo!
Which quantitative trading strategies can be used for crypto trading using algorithms?
Generally speaking, all the trading strategies such as momentum, trend reversal, technical analysis-oriented strategies etc. are used for crypto algorithmic trading.
Since there are a lot of trading strategies that are used algorithmically, we have simple three categories to sum them up:
- Technical analysis
- Market making
A trading strategy based on the price action of the financial markets is known as the technical analysis. One of the assumptions of technical analysis is that the price movements in the future follow one particular pattern. Thus, the analysis of historical market data plays an important role here in forecasting the price movements of financial securities.
Some of the indicators used are Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) etc. One or multiple indicators can be used to generate buy and sell signals.
Arbitrage is the process of purchasing at a low price and selling the same at a high price.
Arbitrage is a risk-free strategy, although this is not always the case. There is always a possibility of execution risk, i.e. risk due to high volatility in the market and a sudden change in price makes it impossible to close the trade at a favourable price. Bitcoin can be simply arbitraged by buying low at one exchange and selling high at another.
Market making is aimed at infusing liquidity and it is mostly a market neutral trading strategy used for securities traded on exchanges. The two most important features of market making are the bid-ask spread and trading volumes.
A market maker is an individual, professional trading firm or brokerage firm that is prepared to buy or sell securities continuously at a publicly quoted price to provide liquidity to the market.
Market makers quote on both the buy and the sell side simultaneously. Once they attain a position, they continue to provide liquidity but are generally more aggressive from the opposite side of their held position.
They accept the risk of holding the securities for which they quote prices and once the order is received, they often immediately sell from their own inventory or seek an offsetting offer almost immediately and vice-versa.
They make a profit from the spreads between buy and sell quotes.
Don’ts while algorithmically trading the Bitcoin
Algorithmic trading for Bitcoin sure is more convenient, with lesser errors, speed, accuracy and whatnot. Nevertheless, there are certain points you can keep in check so as to avoid facing some common hassles, and here we have mentioned them as the “don’ts of using algorithmic trading for Bitcoin”.
Take a look at what to avoid:
- Using the algorithm that is easily available to all
- Not having a development team and a programming language in place for coding the crypto trading strategy
- Not using the APIs of currency exchanges
- Not having the right trading model as the base
- Following an unrealistic approach with regard to deploying the model live
Using the algorithm that is easily available to all
The algorithm you use for trading should not be easily available to everyone. In case it is open to all, the algorithm (and the trading strategy created by you) can be misused easily. This is one extremely important point while algorithmically trading Bitcoin.
Not having a development team and a programming language in place for coding the crypto trading strategy
Not having a programming language sorted and a team to program the trading system are big hurdles to act smartly in the trading domain.
The most common programming languages are Python, C, C++ etc. but Python is most favoured in today’s time. Having a development team will help you to be able to work on different parts of the architecture.
For instance, the developers can be distributed to work on different strategies/models in accordance with the market performance or predictions. Good communication between the team goes a long way when it comes to success.
Not using the APIs of currency exchanges
APIs help access the exchanges that your algorithmic trading system should trade on. For example, the APIs of main currency exchanges such as Coinbase, Kraken, Bittrex etc. allow access to their currency data. Hence, the APIs are extremely helpful.
Not having the right trading model as the base
Confusion in choosing between the models such as a mathematical model (machine learning) or a simple model (moving average crossover) can be a hurdle in creating a good model with favourable results.
The most important thing you must be mentally prepared about is that a more complex model like a mathematical model will take more development time.
Following an unrealistic approach with regard to deploying the model live
Without testing for overfitting and without continuous monitoring for a while in the live market is an unrealistic approach. While deploying your model in the real life market, you must be sure that your algorithmic trading system is built after a thorough paper trading and historical data analysis.
Learning resources for Bitcoin
Going further, let us find out which resources can help you best with regard to learning about Bitcoin. Below, we have segregated these learning resources into blogs and courses:
Getting Started with Cryptocurrency Algorithmic Trading
A brief article starting with the importance and popularity of Bitcoin. Going further, you get to know about a successful EPATian named Garv Khurana who has shared how he formulates the trading strategies, backtests them and executes the orders for Bitcoin Algorithmic Trading.
Cryptocurrency Wallets - A Beginner’s Guide
With this article, you get an idea about the cryptocurrency wallets, including their meaning, types and working. Moreover, you learn about the parameters to look into before choosing a wallet and risk factors that surround the use of cryptocurrency wallets. For someone who is learning about cryptocurrencies, this article can set up a perfect base to explore all about this new digital currency.
The Journey of Cryptocurrency in India
This is an interesting article that takes you through the time when cryptocurrency evidently first became useful to Indians, to its ups and downs that India witnessed. Gradually going further in the blog you also get to read how. during cryptocurrency trading, you must take care of the rules and regulations along with the dos and don’ts.
Top 9 Cryptocurrency Trading Platforms
After going through the basics of cryptocurrency trading, this article reveals the best 9 trading platforms that are popular amongst crypto traders. The article mentions why and how these platforms have made to top 9. Still the choice rests with you as a trader to decide which one you find apt for yourself.
Learning Track: Cryptocurrency Trading for Quants
This learning track consists of all the courses from intermediate to advanced level for those who aim to use quantitative trading techniques for crypto trading.
We discussed how algorithms are non-emotional in nature that is one of the main aims while trading since human emotions restrict the logical/rational application of trading strategies.
Moreover, with backtesting and risk management practices the algorithmic trading makes for a safe trading environment. Also, we saw the broad categories of quantitative trading strategies such as technical analysis, market making and arbitrage for algorithmic trading practice.
For learning more on crypto trading, explore our course on Crypto Trading Strategies: Intermediate.
Disclaimer: Any information regarding cryptocurrency in this article is intended to convey general information only. This article does not provide investment, legal, tax, etc. advice. You should not treat any information in this article as a call to make any particular decision regarding cryptocurrency usage, legal matters, investments, taxes, cryptocurrency mining, exchange usage, wallet usage, etc. We strongly suggest seeking advice from your own financial, investment, tax, or legal adviser. Neither QuantInsti® nor the author of this article accept responsibility for any loss, damage, or inconvenience caused as a result of reliance on information published in, or linked to, from this article.