What Are the Benefits of Algorithmic Trading?

One of the primary benefits of algorithmic trading is that this technology allows traders and investors to execute trades faster than they would otherwise be able to. With the ever increasing pace at which our society is moving, and with the markets fluctuating faster and faster every day, time is of the essence, and having an algorithmic bot in your investing arsenal can prove to be an incredibly timely tool. Algorithmic trading systems can not only be trained to execute trades quickly, but can also be programmed to execute trades based on specific rules and conditions, for example when a certain price level is reached, or when a certain indicator crosses a predetermined threshold. This can help investors make disciplined trading decisions.

Another benefit to algorithmic trading is the potential reduction in human error. Humans are very smart creatures, but our capacity to retain and utilize information is limited. No single person is able to learn the entire market history of, for example, the forex market, but an algorithmic bot can be programmed with that knowledge, and that knowledge can be utilized and executed in real time to perform informed trades. Similarly, it may be difficult for any one person to learn every successful investing strategy, but algorithmic bots can be programmed with as many strategies as can fit on their hardware.

Human error stemming from emotion is another pitfall that we oftentimes succumb to when trading and investing. Our emotions can oftentimes get in our own way and can become an impediment to good decision making, leading to mistakes such as making impulsive trades, over-trading, or simply allowing our fear and greed to run amok. Algorithmic trading bots are programmed according to predetermined rules and functions, and can therefore execute trades in a more consistent and disciplined manner.

Are There Any Drawbacks?

While algorithmic trading has a plethora of real and potential benefits, the technology carries with it several drawbacks. One of the main concerns is that algorithmic trading systems can be prone to technical issues. These technical issues can range from connectivity problems to software viruses, and even cybersecurity hacks. If not properly monitored and managed, algorithmic bots can do significant damage to one’s investment portfolio.

In addition, algorithmic trading systems can be expensive to set up and maintain, requiring significant time and resources to design, test and optimize.

How Can I Get Started?

First, it is imperative to conduct thorough research and understand the financial markets. This includes learning about various trading techniques and strategies, as well as risk management techniques. Traders should also develop an informed understanding of the various technicals and fundamentals underlying any informed trading decision.

Next, traders should choose a trading platform that offers algorithmic trading capabilities. There are numerous platforms available, each with their own set of pros and cons. Some of these platforms are simple and user friendly, while others are catered to the more experienced trader, with a wider range of advanced features and tools. It is also important to choose a platform that is both reliable, and offers adequate customer support, in case there is ever the need for it.

Upon having chosen the trading platform, traders can start designing and testing their algorithmic trading bots. This involves choosing the specific rules and conditions that your system will adhere to.

Finally — and this one is perhaps the most important step — traders should never rely exclusively on algorithmic trading bots to earn capital. This technology hasn’t yet been perfected, and should be utilized as a tool among other tools in your investing arsenal. Investors should continuously monitor their algorithmic trading bots.

What Exactly is Algorithmic Trading?

As previously defined, algorithmic trading involves the use of sophisticated algorithms that aid an investor in buying and selling financial assets on various markets — gold, forex, the stock market, or even crypto. In recent years algo trading has become increasingly popular. The demand for this technology is only increasing, as the global financial sphere has become more intricate and complex.

How Does Algorithmic Trading Work?

Algo trading systems are programmed to follow predetermined rules and conditions that are built into the lines of code upon which the bots operate. For example, a trading bot might be programmed to buy or sell a certain financial asset when its price reaches a certain point. A well trained algorithmic trading bot will have rules and conditions that are based on sound technical and fundamental analysis, or on historically successful trading strategies. Once the algorithm has been programmed and turned on, no further human intervention is required, except to turn the system off, if necessary.

Because this technology is still emerging and evolving, it probably wouldn’t be wise to solely rely on algorithmic trading bots — at least not until further developments. Algo bots offer many benefits as a tool in an investor’s arsenal, but not as a standalone get rich quick protocol.

Advantages of Using Algorithmic Trading

There are several benefits to using algorithmic trading:

• Speed: Algo bots can execute trades faster than humans, which is especially useful in fast moving markets. If connected to the internet, algorithmic bots can also study current events in real time and integrate that information into its trading strategies.
• Accuracy: Algorithmic trading systems are programmed according to set rules and conditions. These rules and conditions cannot be deviated from, reducing error and potentially reducing risk.
• Discipline: Algo bots are essentially lines of code. They are not sentient and have no emotion, and are therefore not prone to fear, greed and nervousness.
• Knowledge: Algorithmic trading systems can retain and recall far more information than any person can. Because they can be trained according to current and historical market data, trading strategies, and can be connected to the internet and be updated with information in real time, trading bots can far surpass humans in their ability to hold and utilize information.

Disadvantages of Using Algorithmic Trading

There are also some drawbacks to algorithmic trading:

• Technical issues: Algo bots can be prone to technical issues such as software viruses, cyber attacks and hacks, which can lead to financial losses.
• Cost: Algorithmic systems can be expensive to set up and maintain.
• Cyber Attacks: Algorithmic trading bots can be hacked. Cybersecurity threads to also trading systems can include hacking the system to gain information or disrupt trading. It is important to always upgrade the cybersecurity measures and to consistently maintain and monitor your algorithmic trading systems.

Is Algorithmic Trading Profitable?

Like other investment activities, algorithmic trading bots carry risk as well as the potential to be profitable. Whether a trading bot is profitable will depend on a number of factors. As previously mentioned, it would be unwise to rely solely on any algorithmic trading system to manage your portfolio, though as a tool in the investor’s investing arsenal this technology may potentially offer several benefits. This technology isn’t perfect, and is being actively developed and upgraded every day. Having said that, algorithmic trading bots can be profitable. In fact, many algorithmic bots have been shown to significantly outperform human traders.

At the end of the day, a bot is simply an empty storehouse of data — how that bot is trained and used is what will differentiate between a successful and unsuccessful investment tool.

It is important to carefully design and test your algo bots to ensure that they are outperforming as expected, and to continuously monitor and optimize them. It is also important to remember that all trading carries some level of risk and that past performance is not necessarily indicative of future results.

Top Algorithmic Trading Strategies

There are many different algorithmic trading strategies that can be used, including:

• Arbitrage strategy: Taking advantage of price differences between different markets or exchanges to make a profit.
• Trend-based strategy: Following the trend of a particular market or security, and buying or selling based on the direction of the trend.
• Statistical arbitrage strategy: This strategy aims to exploit the price difference between two or more strongly correlated financial instruments by using statistical models & algorithms.
• Mean reversion strategy: Buying assets that are undervalued and selling assets that are overvalued, based on historical averages.
• Momentum strategy: Buying assets that show strong upward momentum and selling assets that show strong downward momentum.
• Weighted average price strategy: This strategy involves determining a target price for a trade based on the average price of the security over a certain period of time, and executing trades incrementally at or near that target price.

These and any other successful (or unsuccessful) strategies can be programmed (trained) into the algorithm. This is why algorithmic bots can be profitable or not, depending on its algorithm.

Arbitrage Strategy

Arbitrage is the strategy of taking advantage of price differences between different markets and exchanges. If the price of a particular stock is lower on one exchange than on another, a trader could buy the cheaper stock on one exchange and sell it where it is more expensive on the other exchange. Algo bots can be designed to execute this type of strategy and perform them at far faster speeds than a human trader — and without the trader having to actively monitor multiple markets and exchanges.

Trend-Based Strategy

This type of strategy involves following the trend of a specific asset and buying or selling based on the direction of the trend. If a stock is trending upward, a trend based system trained algo bot might buy up the stock and hold it until the trend changes. Conversely, if the stock or asset is trending downward, the algo bot may sell the stock. Algorithmic trading bots can be designed with this strategy and execute trades with precision, and will not delay due to fear or greed. This will allow traders to capitalize on trends without having to actively monitor markets.

Trend based trading can be risky, and like all investment strategies programmed into trading bots, would require risk management strategies to be programmed alongside. Trends can change drastically and unexpectedly, and there is never any guarantee that any trend will continue in any given direction. Setting up risk management techniques, for example a stop-loss order, when using trend based trading would be wise.

Statistical Arbitrage Strategy

Statistical arbitrage is a type of trading strategy that involves taking advantage of statistical discrepancies in prices between different securities. This can involve buying and selling the same security across multiple exchanges. This strategy also allows for the buying of a basket of securities that are expected to move in a certain direction based on statistical analyses. This strategy is complex and requires a significant amount of computing power and skills in data analysis, making this a great strategy to implement on your algo bots.

Mean Reversion Strategy

This strategy involves buying assets that are undervalued and selling assets that are overvalued as compared to their historical averages. If a stock has consistently traded at a certain price for a long period of time but has recently fallen below that price, an algo bot could buy that stock with the expectation that it will eventually return to or near its historical average. Mean reversion strategy can be used in a variety of financial markets.

Weighted Average Price Strategy

This strategy involves executing trades at a specific price based on the average price of a security over a specific period of time. A weighted average price strategy may be designed to buy a stock at the average price it has traded at over the past week. Weighted average price strategies can be used to reduce the impact of stark market fluctuations and can be used to execute large trades in a consistent manner.

Weighted average price strategies can be useful strategies to be trained into an algo bot for traders who are looking to make faster and more accurate trades while reducing the risk for human error.

There are many algorithmic trading strategies that can be programmed into a trading bot, and it is important to carefully test your bots to ensure that they are operating as expected. It is also important to remember that all trading carries some level of risk, and while algorithmic bots can oftentimes reduce some risk, they cannot eliminate it entirely.

How Does it Benefit the Average Investor?

Algorithmic trading can potentially benefit the average investor in several ways:

• Reduced research time: Algo bots can analyze massive amounts of data & execute trades based on specific conditions, as well current and real time data, which can save investors time and effort in researching and analyzing the markets and the news.
• More accuracy: Algo bots can execute trades more accurately and consistently than humans, which can help to reduce the risk of human error.
• Zero-emotion: Algo bots are not influenced by emotions such as fear or greed, or any other emotion for that matter, which can lead to a more disciplined & informed approach to trading.
• Efficient backtesting: Algo bots can be tested and optimized using historical data.

Reduced Research Time

Because algorithmic trading bots use computerized algorithms, this technology can save the investor countless hours in research, as well as in learning investment strategies. The machine learning involved can quickly and accurately analyze massive amounts of meta data and execute trades based on that data in real time, allowing the investor to focus less on trading and more on other tasks.

More Accuracy

In a world of fast moving markets, where time is of the essence and where human emotions can lead to impulsive or poorly-informed trading decisions, it is more important than ever to be able to make accurate trades while minimizing the risk of error. Algo bots can help to achieve that.

Zero-Emotion

Algorithmic systems are not influenced by emotions, which oftentimes act as an impediment to human trading. This can lead to more disciplined and informed trading decisions, and can be particularly beneficial for investors who may struggle to control their emotions when trading.

Efficient Backtesting

Algo bots can be tested, programmed and optimized using historical data. This is known as backtesting and can help to identify potential issues or weaknesses in a strategy before it is put into use. Through backtesting an algorithmic trading bot, users can gain a deeper understanding of how it is likely to perform under different market conditions, and can show opportunities to make adjustments as needed.