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10 Best Crypto Trading Bot Strategies 2022
This article breaks down key trading bot strategies that might work regardless of the market situation and explains the core idea behind each. If you’ve ever been interested in ways to monetize trading bots, that would be a good take on the topic.
- What Are Trading Bots?
- A Brief History of Trading Bots
- What Are The Best Trading Bot Strategies?
- How to Choose A Suitable Trading Bot Strategy
- Best Crypto Trading Bot Strategies
- Best Trading Bot Strategies For Forex Trading
- Closing thoughts
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What Are Trading Bots?
A trading bot is an algorithm that interpretes market conditions into tradable decisions like buy, sell or hold. Bots use pre-built logic sets to trade on your behalf 24/7. As a result of a minimum downtime, they can process much more deals than any selected trader. Moreover, bots are not affected by emotional trading, which saves lots of money for those who do.
A Brief History of Trading Bots
Trading is quite a concept, and it has been repeatedly used, tested, and improved by humans. At first, we traded anything that would ease survival, but later financial markets came in and changed trading forever.
First trading bots were introduced back in 1949, featuring almost 70 years of evolution to follow. The first idea suggested a mere set of rules for buying/selling assets, and it took many years for the rule-based switch.
A decade later, the golden 90s brought a brand new automated trading system concept, which was limited at first, as only financial managers used it to manage portfolios for their clients. But things have changed after the 2008 crisis, unveiling the concept for the masses. That year was a truly game-changer, as savvy traders across the globe shifted towards algorithmic trading. As a result, automated trading has experienced a big leap in terms of software technologies, analysis techniques, strategies implemented, and more.
What Are The Best Trading Bot Strategies?
Trading bots have no rivals when it comes to speed and execution, but they can’t think independently. Instead, bots compare a set of built-in conditions with the current market situation. Trading strategies refer to the specific way bots compare. Each strategy has its own pros and cons, which is why it’s essential to know all in and outs before trading.
Bot trading strategies are usually classified as follows:
It might seem complicated, but it’s not as hard as it looks. Let’s boil down how you can choose the most effective strategies for trading.
How to Choose A Suitable Trading Bot Strategy
First off, you might want to read more about the strategy. You can pick several strategies from the table above and start educating yourself. Once you learn the basics, you’ll catch the rest much easier, as they are interconnected and repeat each other in terms of core ideas. Assuming you’re familiar with at least some concepts mentioned, you’re good to go.
Regardless of the strategy, its main goal is to bring cash flow your way. There are three core steps to test any strategy, learn more about it and understand whether it fits your trading style.
Analyzing Market Conditions
Global economy affects markets majorly and defines overall liquidity, prices, and even key levels. Some strategies are built for the bear market, while the rest focus on bull or flat trading. If the market is bearish, even top-notch flat strategies might cause significant losses. Which is why you should analyze the market first to understand how it works right now and what you can expect in the foreseeable future. Otherwise, you might end up with a useless trading strategy at best.
Addressing the table above, you might do the following:
- Pick trend trading if you believe the established trend will last for a while
- Use anti-trend strategies if you think the trend is somewhat temporary or a trap
- Leverage flat trading for markets with no obvious trends.
Assuming the market flats around a specific price corridor, you might step up and narrow down your strategy within flat-based ones like scalping or strategies focusing on technical indicators. The latter search for patterns in previous periods with the assumption that the patterns found will repeat in the future. Level trading and price action might also work well for such markets.
Demo Account Tests
You should backtest any strategy to avoid losses. Backtesting is the process of testing a bot strategy taking various types of data like analysis and historical data into account. Backtesting helps you to identify the potential performance your strategy might showcase. You might want to pay delicate attention to stats like averages, risk, volatility, and net profits & losses. A perfect way to backtest is a demo account. If your automated software provider doesn’t have a free one, you might use backtest data provided directly instead or get the cheapest subscription with demo access.
The Control Glance
Once you sorted your strategy out and backtested it, it’s time to take it for a spin. Start small and analyze each trade first — the key criteria is the win/loss ratio.
If things go well and you don’t carry more losses than wins, you should split your trades by groups of 10-20 trades each and evaluate results accordingly. If a group made you some profits, that’s a good sign. Otherwise, you can either analyze a few more groups or adjust your strategy. This step is crucial, as regardless of the strategy, your automated software will operate on scale.
Best Crypto Trading Bot Strategies
Some crypto trading bot strategies are more flexible and reliable than others, making them much more popular among traders. Let’s break down core strategies you can implement to make money.
Mean reversion strategies suggest a regular price return to a certain average level on longer timeframes. The expected level of price reversion plays a crucial role in the performance.
The process of returning to the average level (on any time frame) is determined by the influence of positive or negative feedback. Therefore, the most important step is analyzing a financial instrument for the presence or absence of reversion.
If present, the chance for reversal and hence profits increase, once the price approaches the upper/lower limit. Time and volume-weighted average price can be used as an average value. The same indicators can be used in correlation trading and market-making strategies. Mean-reversion strategies demonstrate the best results during consolidation periods in the market when there is no identifiable trend.
Momentum trading strategies refer to buying/selling an asset according to the recent trend. The core idea suggests if there is enough force behind a trend move, it will keep going in the same direction.
When an asset climbs higher, more buyers tend to enter, pushing the price even further. But eventually, something happens and high prices garner selling pressure. An obvious example is news trading based on negative/unforeseen events. Once the selling pressure is higher than buying pressure, the trend reverses and drags the price down to the bottom.
Momentum strategies analyze volume, volatility and time frame of the trend to identify how strong it might be in a given direction. Then an algorithm or trader opens a position to ride the trade until the momentum is lost. Some traders try to make the most of trends and do their best to spot top and bottom. However, emotions bring bad luck quite frequently. Which is why disciplined bots implement most momentum trading strategies.
Arbitrage strategies are all about the price difference — buy cheaper, sell higher, repeat it multiple times on scale. Most arbitrage strategies use bots, as they do routine operations way faster.
These strategies have been used for a while across financial markets, but the crypto market is a bit different, as it has a higher volatility. Most crypto assets are more volatile than any other assets, implying potentially higher profits but also higher risks. One of the most substantial risks here is the price slippage, especially for manual arbitrageurs. But why?
The price differences are usually miniscule and traders have to move large volumes quickly. Even a slight slippage in price may eat up a bite of profits, leaving a trader without profits at best. In fact, deep losses are quite common for arbitrageurs with large volumes, as they need to take many things into account. Unlike robots, humans might fail accidentally.
Despite all the risks associated with crypto arbitrage, it still attracts many traders. The biggest arbitrage barrier is a high entry cost, which is especially painful for retail traders.
Most machine learning models perform better than those of statistical and econometric models. In particular, the ability of Gaussian Naïve Bayes (GNB) algorithm to predict crypto quotes price movement has not been addressed until recently. But things change and this method is widely used now. In essence, GBN algorithm leverages probabilistic machine learning combined with different scaling and feature extraction techniques in crypto price movement prediction.
Simply put, this algorithm classifies data into increasing and decreasing prices. Imagine an asset has been dropping in price for two straight days in a row. Machine learning strategies can access the probabilities and give you directions with a higher chance to trade successfully during such events.
Unlike other strategies, this one works well on small datasets and doesn’t require significant computational power, making it quite affordable. However, it doesn’t fit on-scale traders willing to discover big data.
Natural Language Processing (NLP)
News and crowd psychology go hand in hand and both affect finance markets, but it’s hard to evaluate something without numbers. Natural language processing (NLP) trading partly solves this issue, as NLP programming helps bots to react to the news with certain keywords.
Imagine trading bots can scan news digests, Medium articles, social media and more to spot specific keywords to decide whether it’s a good time to trade an asset. You can go further and combine the strategy with trend-following trading or play smart against the whole market.
Best Trading Bot Strategies For Forex Trading
Forex is a currency pair market, which means it uses the same principles as any other financial market. Luckily for traders, stock & crypto bots can efficiently operate on Forex as well. But what about the strategies? They are also pretty much similar. Let’s boil down some key bot strategies available on Forex.
Average price, also known as the mean reversion strategy, leverages the principle that historical returns and asset prices will return to their average levels, especially over the long run.
In essence, trading bots make money on price fluctuations regardless of the market, meaning traders get yields on upswings and then save on lows. This strategy can be used to buy and sell assets, making it quite flexible and popular. Even though the price returns most of the time, there is always a risk that the asset might break the pattern. Another risk is a black swan event no one can predict. A bright example was the housing bubble back in 2008.
This is perhaps the easiest of the trading strategies, as it involves following market trends. A bot repeats the same actions the majority does. If the price goes up, a trading bot follows by opening a long position buying in anticipation of the asset rising in value.
Whenever the market experiences a dip, the algorithm shorts an asset, expecting the price to go down. In other words, a bot sells an asset (price go down) to purchase it later at a lower price. The difference becomes profit. Bots use this strategy quite effectively, as large volumes of historical data help them to evaluate the market and accurately predict whether the trend will repeat itself or reverse.
Arbitrage is the technical trading style to leverage on price inconsistencies. In other words, you buy an asset on one market for a specific price and sell the same asset immediately somewhere else for a higher price. The difference you make is your profit. Even though the price moves are fairly small most of the time, traders use bots to operate on scale and do it as fast as possible. As a result, some algorithmic traders yield high returns using arbitrage strategies.
Simply put, arbitrage trading programs (ATP) implement algorithms to identify price differences across various markets. ATPs compete with each other, leaving almost no place for retail traders arbitraging manually.
Given how advanced technology has become, price anomalies don’t stay for long – they are picked up by traders with systems scanning for the same thing and then rectified. Therefore, ATP systems are the only way that these price differences can be taken advantage of – it is not something a human could do fast enough.
This strategy may seem fairly straightforward, but it should be noted that price differences in forex are usually minute. Therefore, traders using ATPs need to trade large positions to make a substantial profit.
One of the most valuable aspects of using an automated system is its ability to operate at a pace no human could. High-frequency trading (or scalping) is the method of using an automated system to potentially make hundreds of thousands of trades in a fraction of a second.
The biggest criticism of HFT is that it allows the big players to dominate because they can trade in such substantial blocks (using algorithms). This type of trading adds liquidity to the market; however, many consider this a negative because the liquidity produced only lasts for seconds – too short a time for non-HFT traders to benefit from it.
A positive of HFT is that it removes small bid-ask spreads. A bid-ask spread or a bid-offer spread is the difference between the price at which an asset can be sold, versus the price at which the same asset can be bought. By widening the gap between, HFT traders can often exploit the system and make more money.
Wars, inflation, and natural disasters have affected the market more than anything else — the impact driven by news is hard to overestimate when it comes to finance markets and trading.
While negative news like big-picture economic and political uncertainty normally causes traders to sell, positive occasions might push the prices far beyond adequate rates. Even though experienced traders rarely follow the news, they still try to anticipate it and think outside the box. Sometimes traders intentionally play against the market and bad news becomes good news, sometimes it’s quite a gambling.
For example, news that a hurricane has made landfall may force a rapid decline across some assets because people anticipate emergency responses and repairs that cost a penny. On the other hand, other assets might gain positions significantly. In this case, that would be real estate quotes, as the demand anticipation rises due to the ragestorm.
News-based trading strategies react to news and generate trade signals based on what is happening in real-time. Positions traders hold are limited in time because news agenda tends to change quite fast. Traders use bots to analyze news and act accordingly. Newbie traders set up robots and receive signals to act manually, while more seasoned market participants set up trading bots in advance. The latter take bigger risks, but potential profits also grow in folds.
Forex and crypto markets might be an excellent place to test out a wide range of trading strategies. However, some methods work better than others in hard times of uncertainty, when sudden moves substitute long flats only to be followed by another unavoidable dip.
As history shows, there’s a set of flexible, simple, and powerful bot-trading strategies like news-based approach, trend following, arbitrage & machine learning opportunities, mean reversion model, and more. That doesn’t mean you can’t check out other ways of monetization through bots, though.
Not all bots are designed equal, as profits trading bots depend on the strategy you pick and the market conditions. However, some reliable bots like 3Commas can make money steadily regardless of the market.
Trading bots might perform badly if the strategy is poor. However, it’s not common for reliable bots like 3Commas. Moreover, one trade is not as important as the number of trades. If your bot wins more frequently and the number of trades is significant enough, you can completely neglect one-time failures.
Trading bots operate 24/7, which allows them to monetize way more opportunities than humans. Moreover, robots do not lose money due to emotional trading.
Depending on your needs, some bots fit better than others. However, you might want to limit your selection to the most reliable trading bots. A vivid example of such a bot is 3Commas.
You do not necessarily need a bot, but lots of traders leverage automated trading because robots are effective and easy-to-use. A bigger part of the crypto and forex markets are bot traders.
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