Algorithmic Trading

Algorithmic Trading (also known as 'algo-trading', 'black-box trading', or 'automated trading') is the practice of using sophisticated computer programs to execute trading orders automatically. Think of it as putting a robot in charge of your trading account. This robot doesn't have emotions; it just follows a strict set of pre-programmed instructions—the algorithm—at lightning speed. These instructions can be based on timing, price, volume, or complex mathematical models. When the market conditions match the algorithm's rules, it instantly places a buy or sell order, often faster than a human can blink. The primary goal is to generate profits from tiny, fleeting market movements, executing a vast number of trades that would be impossible for a human to manage. While it dominates modern markets, especially in the realm of High-Frequency Trading (HFT), it is fundamentally different from the patient, long-term approach of value investing. For the value investor, algo-trading is more like the frantic, noisy weather of the market, not the underlying climate of a business's worth.

The concept is simple at its core, but the execution is incredibly complex. An investment firm or a team of quantitative analysts (often called quants) designs a set of rules. These rules are the “if-then” logic that guides the computer. For example, “IF stock XYZ drops 2% in 5 minutes AND trading volume exceeds 1 million shares, THEN sell 10,000 shares.” This algorithm is then coded into a powerful computer system connected directly to a stock exchange's trading network. The computer constantly monitors market data, looking for the specific triggers it was programmed to find. Once a trigger is detected, it executes the trade without any human intervention. The key advantages are speed, accuracy in execution, and the removal of emotional decision-making, such as fear or greed, which can often lead to poor investment choices.

Algo-trading isn't a single strategy but an umbrella term for many different automated approaches. Most of them are focused on exploiting short-term market inefficiencies rather than a company's long-term value.

• Arbitrage: This is the classic “buy low, sell high” strategy, but executed in microseconds. An algorithm might spot that a stock is trading for €50.10 on the Euronext exchange and €50.11 on the London Stock Exchange. It will instantly buy the stock on Euronext and sell it on the LSE, capturing a tiny, almost risk-free profit of one cent per share. When multiplied by millions of shares, these cents add up quickly.
• Trend Following: These algorithms are designed to ride the wave of market momentum. They use technical analysis indicators, such as moving averages or the Relative Strength Index (RSI), to identify when a stock is trending up or down. For instance, an algorithm might be programmed to buy a stock when its 50-day moving average crosses above its 200-day moving average (a famous signal known as a golden cross) and sell when the opposite occurs.
• Market Making: Some algorithms act as automated market makers. They simultaneously place both buy (bid) and sell (ask) orders for a stock, aiming to profit from the difference, known as the bid-ask spread. This strategy provides liquidity to the market, making it easier for other investors to buy and sell, but its primary goal is to scalp small, consistent profits.

So, what does all this high-speed, robotic trading mean for a patient value investor? Mostly, it's just noise. Warren Buffett and his mentor, Benjamin Graham, built their fortunes on a completely different philosophy.

Value investing is the art of buying stocks for less than their underlying intrinsic value. It involves deep fundamental analysis of a business—its earnings, debt, management quality, and competitive position. You buy a wonderful company at a fair price and hold it for the long term, letting its value grow. Algorithmic trading, by contrast, is often about the price of the stock, not the value of the business. It’s a game of milliseconds and technical signals that a value investor should wisely ignore. As Graham famously said, “In the short run, the market is a voting machine but in the long run, it is a weighing machine.” Algo-trading is the hyperactive operator of the voting machine.

While you shouldn't participate in algo-trading, its existence can actually create opportunities.

• Increased Volatility: The sheer volume and speed of algo-trading can create wild, short-term price swings and even “flash crashes.” A perfectly sound company's stock might plummet for a few minutes or hours because of a rogue algorithm or a herd of trend-following bots.
• Finding Bargains: This algorithm-induced volatility is a gift for the prepared value investor. When the market panics and sells off indiscriminately, the price of a great business can fall far below its true worth, creating a significant margin of safety. While the robots are reacting to blips on a screen, the value investor can calmly step in and buy a piece of a fantastic business at a discount.

In essence, algorithmic trading is a feature of the modern market that you should be aware of, but not fear. Let the algorithms create the chaos; your job as a value investor is to find the clarity and value within it.