Advent of computers and internet has been a game changer in every field, providing opportunities to common people that were available to privileged few.
Many years back, buying and selling shares was long and cumbersome process and available to only few. Today as computers become more affordable and availability of internet across the country, anyone can buy and sell stocks within few clicks.
This, however, is just the beginning. In the near future, computers will be able to make buy and sell decisions on your behalf. Many large corporations(especially institutional investors and investment banks) are already using this technology called Algo trading.
What is Algo Trading:
Algo trading uses algorithms (a set of complex mathematical models) that can be used to make buying and selling decisions.
The algorithm of an algo trading software has predefined set of rules that are back tested(that is, tested on the historical market data) to check its accuracy and success rate. This algorithm is then applied to place buy and sell orders and make successful trades.
So what was the need to create algo trading system? What are the advantages of algo trading and why is it so popular especially among large institutional investors and high frequency traders? Let’s start by understanding the advantages of algo trading
How does Algo Trading Work?
As mentioned earlier, algorithmic trading uses a set of predefined rules, based on mathematical models and automatically places orders in such a way that there is high chance of making profit.
For this purpose, algorithms are programmed to study financial trends, which help in finding great trading or investing opportunities. Let’s take a simple example. Suppose a trader takes a simple trading criteria:
Buy 20 shares of a company when its 20 day moving average goes above 50 day moving average.
Sell 20 shares of a company if the 20 day moving average goes below 50 day moving average.
By using these two very simple criteria for buying and selling a stock, a trader, with the help of a computer programmer can create a software that would continuously monitor the market and place a buy/sell order automatically once the predefined criteria is met.
All the algorithms written are then back tested, that is they are tested on the past data to check their efficiency and success rate. Once an algorithm gives good success rate, it is then accepted and implemented for trading in similar market conditions for which it is built.
Traders can also develop their own strategies based on their past experience and market conditions. Some complex and advanced algo trading software can have multiple trading algorithms written in them, the software, based on various criteria(such as direction of market, financial trends, market inefficiency) can pick the best trading strategy that has had highest success rate in the past.
Types of Algo trading strategies:
There are various strategies used in algo trading, which scan various aspects of the market and make buy and sell decisions accordingly. Some of the most popular algo trading strategies are as follows:
This is one of the most basic trading algorithm used. This type of trading strategy looks for looks for market trends that will move in one direction with high volumes.
A simple momentum strategy invest in 5 stocks that have seen huge volumes growth in the past trading sessions with large volumes of shares exchanging hands.
By using this trading strategy, you can actually “ride the tide” of upward momentum and make handsome profit in the short term.
“What goes up, must come down”, this is the core principle of mean reversion trading strategy. Algorithms following this strategy assume that price of the stock will revert back to the average price.
In this trading strategy, the assets are bought when they are trading below their average trading range and sell it when it goes above the average. This trading strategy uses moving averages to do so.
This strategy involves algorithms monitoring the market for indicators to execute trades. Generally, these trades use technical analysis and market patterns and indicators to make decisions.
The goal of this strategy is to buy assets when prices break noteworthy resistance levels and sell short assets which fall below significant support.
This algorithmic trading strategy is popular among investors because of its functionality and ease of use compared to other algorithmic trading strategies.
Sentiment in a trading is determined by the behaviour of crowds. The goal of this trading strategy is to take large quantities of unstructured data from various sources such as news, reports, social posts, blogs etc and analyze to understand the market sentiment to make quick gains.
One of the most widely used trading strategies, usually considered as risk-free as it looks for market inefficiencies and price differentials between asset classes in order to make quick gain.
For example, if a company is trading at Rs. 100 on one exchange and Rs. 99.5 on other exchange.
The algorithm will use this difference of Rs.0.5 and buy from the exchange where its trading at a lower price and sell it in the exchange where its trading at higher price, making a small, quick, risk free gain.
Advantages of Algo Trading:
Quick and efficient: The biggest advantage of algo trading is that the trades are placed much faster pace(within microseconds), many times faster than humans. Since algorithms are written beforehand, the speed and accuracy of placing orders is much faster.
Multitasking: Algorithms can track multiple variables at the same time, and pick the best trade possible.This is impossible for a human being. Since multiple trades are analyzed at the same time, there are always more trading opportunities than ever.
Zero Emotional Bias: Humans are emotional, because of which we have our own biases towards certain people or events. While trading, human emotions can cause them to make irrational decisions which can destroy your capital.
Since algorithms are purely based on logical decision making, every trade placed by the algo traders is based on rational grounds, boosting the chance of success.
Low transaction cost: With algo trading, traders don’t have to spend as much time monitoring the markets, as trades can be executed without continuous supervision.
The dramatic time reduction for trading lowers transaction costs because of the saved opportunity cost of constantly monitoring the markets.
Nothing in this world is perfect, not even algorithms. While algo trading may be efficient and profitable, it does have its own disadvantages which are explained below:
Disadvantages of Algo Trading:
Requires Technical Knowledge: Since creating algorithms require use of programs and technical expertise, it can be done by only those people who have the required knowledge and expertise and hence it not everybody’s cup of tea which in turn does not provide level playing field to all participants in the stock market.
Not 100% accurate: Just because algos best are based purely on logic, does not mean that it’s flawless. Every algo trading software places its bets based on predefined set of instructions.
Since history does not always repeat itself, there is a chance that an algorithm may generate false signal and place bet based on it, causing loss to the trader.
One size “does not fit” all: Another limitation of algo trading is that it is not universal. One algorithm cannot be applied to all the market conditions , that is why it either requires some human supervision or one needs to have multiple algorithms suitable for different types of market conditions.
With computers getting smarter, they are contributing to every part of our daily life. Right from ordering food to making our investment decisions, everything is done with the help of computers. While algo trading is currently used largely by institutional investors, it is now slowly finding its way to retail investors.
Over the past few years, there has been significant progress the field of algo trading. With better and more complex algorithms, and the power of Artificial intelligence, algo trading will have a significant place even in our financial lives.