The Risks of Algorithmic Trading and How to Manage Them

Algorithmic trading is almost as old as the internet itself. It emerged in the late 1980s and 1990s in the initial stages of internet development. However, it gained mainstream popularity in 1998 when the U.S. Securities and Exchange Commission (SEC) started using computerized high-frequency trading. With every type of trading, there are risks of algorithmic trading that every trader and investor ought to watch out for.

Algorithmic trading involves the use of a software to carry out and implement various trading strategies with the help of mathematical models. In the first part of this series, we explored the various types of algorithmic trading strategies. These strategies are solely based on electronic information but still require technical analysis. This is known as the technical approach.
In this second part, we will be discussing the various risks of algorithmic trading that may affect a trade and how to effectively manage these risks to safeguard your assets.
Let’s get started!

6 risks of algorithmic trading

In our previous part, we already discussed what algorithmic trading is. In summary, algorithmic trading involves making trading decisions using a set of rules. These set of rules have been previously programmed into a computer. That way, when the market conditions are right the computer makes a trade by following those pre-programmed rules. This increases the efficiency of a trade and opens more opportunities for traders to make money.. In addition, algorithmic trading is also known as automated trading or black box trading.

Although the benefits of algorithmic trading are numerous, there are some risks that investors must watch out for while using algorithmic trading. Here are 6 risks of algorithmic trading:

Market volatility and instability

Algorithm trading strategies can be subject to the high market volatility of cryptocurrencies. The market volatility can affect the optimal performance of the algorithm. This could lead to significant losses and slippage.
Algorithmic trading can also create flash crashes or herd behavior. This can lead to rapid fluctuations in the price and liquidity of one’s assets.

Technology failure and glitches

Algorithmic trading is almost entirely dependent on the performance of the systems being used. A single technical glitch or issue with connectivity just for a few critical minutes may be devastating. Technical glitches can disrupt algorithmic trading strategies, leading to delays, errors, or losses on trading orders. Some glitches may even trigger unwanted trades that can affect the performance of your assets in the market.

Regulatory risks

Algorithmic trading is subject to many regulatory and compliance checks that may affect the flow of trading operations. Some of these regulatory checks also come with some unwanted financial commitments. This is because some of the algorithmic trading strategies may violate a regulatory code and result in fines, penalties, or bans. The result of this is a damage to one’s trading reputation and, ultimately, profitability.

Cybersecurity risks

Algorithmic trading is exposed to cybersecurity threats such as hacking, data breaches, and cyberattacks. This is due to the interconnected nature of financial markets which makes traders’ infrastructure a little exposed.

Also, due to its heavy reliance on data, corrupted data can create a weak link in the trading profile of an investor. This creates room for hacking and other cyberattacks. The effect of this is a massive loss in liquidity and assets.

Over-optimization and overfitting bias

Over-optimization and overfitting occur when an algorithm is optimized to perform well on the historical data that it was trained on but fails to perform well on live and future market conditions. This leads to huge losses during trade.

Model risk

Algorithmic trading strategies use mathematical models that govern their operations. These mathematical models ensure the accuracy of a trade. However, in conditions where this model may contain flaws or inherently, a trade does badly in the market. This ultimately leads to significant losses in the trade.

How to effectively manage the risks of algorithmic trading

Regardless of the risks of algorithmic trading, there are precautions that one can implement to mitigate these risks. They include:

1. Traders must ensure the integrity of the data that they are using for their algorithmic trading models
2. Traders and investors must seek to create flexible algorithms that can easily adapt to the changing market conditions.
3. Traders must stay up-to-date on the latest regulations and compliance policies. This is to help them avoid regulatory risks
4. Traders must also limit their trade volumes, especially in unsettling market conditions to minimize risks
5. Traders must ensure that they establish secure methods to safeguard them from cybersecurity attacks. An example is setting
6. up two-factor authentication to prevent unwanted access to your information
7. Traders should regularly backtest their algorithms to ensure its accuracy and reliability.

Conclusion

Algorithmic trading is still growing with the new technologies that are emerging. Therefore, traders must know how to effectively use algorithmic trading to maximize their investments.
How can you effectively use algorithmic trading? Get familiar with the various algorithmic trading strategies, the benefits of algorithmic trading, its risks and how to effectively manage these risks.
Algorithmic trading is a powerful tool that traders use to achieve their set financial goals. Remember to keep evolving to reduce potential losses and increase the chances of gaining returns.

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