The classic 1966 spaghetti western “the good, the bad and the ugly” featured Clint Eastwood, Lee Van Cleef, and Eli Wallach as three gunslingers vying for hidden treasure. Like the film, algorithmic trading has its own versions of the good, the bad, and the ugly. Successful algorithmic trading can be highly profitable, but poor strategies can result in losses, and fraudulent manipulation can lead to severe financial harm.
Algorithmic trading, or “algo trading,” involves using computer programs to generate trades based on specific market variables like price, timing, and transaction volumes. Unlike humans, computers can process vast amounts of data quickly, respond instantaneously, and operate without breaks, 24/7. These attributes make algorithmic trading appealing.
It’s important to distinguish between algorithmic trading and automated trading systems. Algorithmic trading typically involves large trade volumes and uses rules to decide when to buy or sell, and it doesn’t have to be entirely automated. Automated trading systems, on the other hand, fully automate the trading process.
A specialized form of algorithmic trading, high-frequency trading (HFT), executes transactions at incredible speeds, aiming to make small profits across multiple markets. But is algorithmic trading right for you? Let’s explore the landscape to find out.
Types of algorithmic trading strategies
Initially, algorithmic trading was the domain of big corporations like pension funds and insurance companies, due to the high costs of developing algorithms, acquiring powerful computers, and sourcing real-time data. Now, individual investors can implement their own strategies or invest in algorithmic trading firms.
You can choose to invest short, mid, or long-term using various strategies. These include:
- Market trend-following algorithms: Buy when the price falls to a certain level, sell when it rises.
- Mean reversion: Buy when a stock is under its average price, sell when it’s above.
- Arbitrage: Buy and sell in different markets to take advantage of price differences.
- Other factors: Trade based on index fund rebalancing, trade volumes, timing and size of trades, share prices, and unusual market patterns.
Always ensure that algorithmic trading firms are fully registered, regulated, and licensed to have some legal recourse in case of any issues.
Pros and cons of different algorithmic trading strategies
Algorithmic trading offers numerous strategies, each with its own benefits and risks.
Pros:
- Speed and efficiency: Be the first to react to market trends.
- High volume, small gains: Profit from numerous small trades rather than a few large ones.
- Emotion-free decisions: Computers don’t suffer from emotional biases.
Cons:
- Technical issues: Power cuts or internet outages can disrupt trading.
- Algorithm flaws: Undiscovered flaws in algorithms can lead to significant losses.
- Market manipulation: Unscrupulous companies can rig the market or misinterpret trends, causing adverse effects.
Potential threats to overall market health
Algorithms are only as good as their programming and the data they process. Issues like incorrect programming, power cuts, or internet drop-outs can cause problems. Additionally, algorithms can cause market imbalances, massive losses, and failures if something goes wrong. For instance, investments in companies with hidden flaws (e.g., Enron or WorldCom) can become worthless despite being initially based on reliable data.
Can algorithms be manipulated to make a trader lose?
Algorithms can be manipulated to cause losses through various methods, including:
- Spoof orders: Orders placed and cancelled last minute to trick algorithms.
- Fake news: Artificially driving up stock prices with false information.
While such behavior may not always be illegal, it is often immoral. In rapidly moving markets, regulators and legislators struggle to keep up. Hacking and data breaches can also significantly impact algorithmic trading outcomes.
