What is Algo Trading?

When you unlock your phone and open any application, it functions based on algorithms. What you do, what you see, and how the application is customized to match your preferences, the reason is algorithms. With the advent of advanced technologies, almost every sector is basing its effectiveness on this piece of logical code. Algorithms leverage user data, past patterns, and a designated set of prespecified instructions to achieve the set goals. For example, an algorithm is used by Mutual Fund companies to deduct the set amount from your bank account every month towards a SIP.

Algorithms are not new to the Indian financial market as they are used in the virtual transaction system to ensure trading transparency, effective user experience, and the mitigation of lags or glitches. However, using algorithms is not limited to depositories or stockbrokers. Investors actively use algorithms to avoid human errors and increase profit potential while trading. The process is referred to as Algorithmic Trading or Algo Trading.

What is Algorithmic Trading?

Algorithmic Trading is the process of using pre-programmed trading instructions to execute trading orders at high speed in the financial market. Investors and traders use trading software and feed it trading instructions based on time, volume, and price. Once the set instructions are triggered in the market, the trading software executes the orders set by the investor. Generally, algorithmic trading is used by Mutual Funds, Hedge Funds, Insurance Companies, Banks, etc., to execute a large number of high-volume trades that are otherwise impossible for humans to undertake.

For investors personally, algorithmic trading allows more trades in a limited amount of time without the impact of human emotions and trading errors.

To better understand what is algo trading, consider the following example.

An investor can feed the following set of instructions for executing algorithmic trading:

Instruction 1:

Buy 100 shares of XYZ company if it goes above Rs 450 before 2 PM.
Now, if the share price goes above Rs 450, the order under the algorithmic trading will automatically place an order for 100 shares of XYZ company. However, the algorithmic trading software will only execute the order if the target price is achieved before 2 PM. After 2 PM, the instructions become void.

Instruction 2:

Sell 100 shares of QPR company if its 20-day moving average goes below the mark of 200- day moving average before the closing of the market.
In this case, the algorithmic trading software will sell 100 shares of QPR company if, before the closing of the market, its 20-day moving average falls below the 200-day moving average. If not, the order is not executed.

For algorithmic trading to execute orders, the set instructions must be fulfilled only once. For example, in the case of Instruction 1, if the price reaches above Rs 450 for even a few seconds, the algorithmic trading software will place the buy order. It may be that after those few seconds, the price may fall below Rs 450 again. However, the order would have been placed already at the market price or any price prespecified by the investor above Rs 450.

Strategies of Algo Trading

There are numerous strategies investors use to undertake Algorithmic Trading. The most common are listed below:

• Index Fund Rebalancing: Index Funds continuously rebalance their portfolio to match the underlying asset’s current market price. In this way, they create opportunities for algo traders to capitalize on the expected trades and make profits from the difference of 20-80 basis points. These trades triggered by the index fund rebalancing are majorly undertaken through the use of algorithmic trading.
• Trend Following: This type of algorithmic trading is the most common among algo traders. In the process, they use moving averages, price movements, channel breakouts, etc., to prepare a set of instructions for the algorithmic trading software. Once the set trend is achieved, the software executes the order for the investor.
• Arbitrage: Arbitrage is when you buy a lower-priced stock from one market and sell it simultaneously in another market where the stock price is high, making a profit from the price difference. Investors leverage data to identify such stocks that are trading at different prices and then use algorithmic trading to implement buy and sell orders in both markets.
• Mathematical Model: Investors use proven mathematical models to simultaneously trade on the same underlying asset’s stock and derivative. Since it can be a complex set of transactions, they use algorithmic trading to identify such assets and execute orders among various asset classes based on price fluctuations.
• Mean Reversion: This strategy promotes the temporary highs and lows of an asset, and if given needed time, the asset price will always revert to the mean value (average price). The investors use algo trading to define the asset’s price range and ensure they buy/sell the asset automatically if it breaks in or out of the defined range.
• Volume Weighted Average Price: Investors aim to execute their orders as close as possible to the volume-weighted average price. Algorithmic trading allows the investors to break up big order volumes into dynamically smaller chunks and ensure the closing price goals are achieved.
• Time Weighted Average Price: This type of strategy also breaks up big order volumes into dynamically smaller chunks. However, investors use divided time slots between the start and end time to execute the strategy through algorithmic trading. The aim is to minimize the market impact by executing an order as close as possible to the average price between the start and the end time.

Benefits of Algo Trading

Here is why investors and financial houses use Algorithmic Trading:

• They can execute a trade or high-volume orders at high speed.
• The orders placed are automatic and highly accurate without any human errors.
• They can avoid significant price changes as the orders are executed within seconds.
• It allows the reduction of transaction costs.
• Investors can identify differently priced stocks in various markets and make profits.
• Big financial houses can use algorithmic trading to execute a large number of orders without significantly influencing the market price of the asset.

Algo trading is one of the best ways for an investor to ensure they do not commit physical or emotional errors while trading and miss out on potential profits. However, algorithmic trading is highly technical and requires immense knowledge related to the financial market, data analysis, and computer programs. Furthermore, algorithmic trading demands access to past asset performance, live market feed, and a detailed infrastructure of trading platforms and integrated networks.