All you need to know about Algorithmic trading

Let’s go a decade back, and as a trader, you would have hoped your instructions were automatically met, from commands like pricing to timing or any other metric. Fortunately, in today’s fast-paced world, technology has ensured you can do all this with just a command. Welcome, algorithmic trading.

In the world of algorithmic trading or algo-trading, a computer program receives a command that follows those defined sets of instructions to place a trade. So, how is this helpful? Well, it does at a speed and frequency that a human trader cannot possibly do. The defined sets of instructions are based on

Timing

Price

Quantity

Mathematical model

And aside from the profits a trader is likely to earn through this trading platform, it also ensures markets are more liquid and makes trading more systematic by taking human emotions away from trading activities.

So how does it work in the real world?

Consider this, on a typical trading day, you pass on instructions to buy 100 shares of a particular stock when its 100-day moving average goes beyond the 200-day moving average and vice-versa. By following these instructions, the computer program will monitor the stock price and buy or sell a stock when these conditions are met. All this is done automatically, and a trader doesn’t need to manually monitor live prices and graphs.

Benefits of Algorithmic Trading

At the best possible price, trades are executed

Trade orders are instant and accurate; in fact, the probability of execution at the desired levels is higher

To avoid significant price changes, trades are timed correctly and instantly

Transaction costs are reduced

At the same time, under multiple market conditions, automated checks can occur

Manual errors reduced

Using historical and real-time data can be backtested before being applied as a viable trading strategy.

Reduces the possibility of errors based on emotional and psychological factors

So how has the market reacted to algo-trading?

Positively. In 2019, the global algorithmic trading market was at $11.1 billion. By 2024, it is expected to touch 18.8 billion. With more investors seeking quick, reliable, and effective order execution, its demand has soared. Plus, lower transactional costs, heightened government regulations and the rising demand for market supervision have further propelled the growth of algo-trading.

Through algorithmic trading, traders find a more systematic approach to trading than methods based on trader intuition, instinct or even emotion. Algo-trading is used in many forms of trading and investment activities, including:

Mid- to long-term investors, pension funds, mutual funds, insurance companies use algo-trading to buy large quantities of stocks discretely to avoid influencing stock prices

It is beneficial for short-term traders, market makers, brokerage houses, speculators, arbitrageurs that prefer automated trade execution. Also, it enables them to create sufficient liquidity for sellers

Trend followers, hedge funds, or pairs traders find algo-trading more efficient to program and are comfortable in letting the program trade automatically

Algorithmic Trading Strategies

For any strategy to come in place in algo-trading, it requires identifying opportunities that are profitable both in earnings and cost reduction: Here are some strategies algo-traders use

Trend-Following Strategies: As the most common algo-trading strategy, it follows trends in moving averages, price level movements, channel breakouts, and other technical indicators. They are easy strategies to apply as they do not involve making any predictions or price forecasts.

Arbitrage Opportunities: The strategy involves buying a dual-listed stock at a lower price in one market and selling it at a higher price in another market. By implementing an algorithm to identify such price differentials, traders can automatically place orders efficiently for profitable opportunities.

Mean Reversion: Based on the idea that a stock's high and low prices are temporary and will eventually return to their mean value periodically. So, by identifying a price range and implementing an algorithm, trades can be placed automatically.

Volume-Weighted Average Price (VWAP): By using stock-specific historical volume profiles, the strategy is to break up a large order and release smaller chunks to the market.

There are many other strategies, like index fund rebalancing, time weighted average price, percentage of volume (POV), implementation shortfall, etc., that traders can use to stay one step ahead.

Algorithmic trading brings together computer software and financial markets closer by leveraging computing power to perform high-frequency trading.