Not just limited to digital payments and sanctioning loans, fintech has extended its ambit to stock trading and investment. Stock trading and investment have long been perceived as a domain of subject experts. It was meant for those individuals who understood the complexities of stocks, currencies, etc. By saying this, it is not a denial that the stock market is not complex, but with the advent of fintech and the use of computer programmes in stock market trading also known as algorithmic trading, investment has become easier.
What is algorithmic trading?
Algorithmic trading uses computer programming to follow a predefined set of instructions for buying and selling securities. The said instructions are based on timing, price, quantity, or any mathematical model. It can generate profits speedily with a frequency that cannot be matched by a human trader.
Such automated trading was introduced in India by SEBI who first allowed direct market access facility to institutional clients. The direct market access facility allows brokers to provide their infrastructure to clients and give them access to the exchange trading system without any intervention from their part. This facility reduced costs and helped investors to skip the time invested in routing the order to the broker and issuing necessary trade instructions.
Why use algorithm trading?
Since algorithms are written beforehand and executed automatically, the main advantage is speed. Besides that, algorithmic trading provides the following benefits:
Convenient buying and selling of securities without letting emotions or assumptions interfere to realise profits or cutting losses.
One does not need to be present physically for trading securities. It is a low maintenance process where we can set our algorithms up and let them trade around the schedule, 24 hours, day or night.
The algorithms can be backtested and refined more against the historical data to confirm if it is a viable trading strategy and find the best combination of parameters to buy or sell.
Algorithms can be finely adjusted in a trading strategy to implement stop losses and limits.
Reduce risks of manual errors while buying or selling stocks.
The investor has the freedom to choose or create an algorithm according to the strategy, thereby maximising exposure to opportunities in the underlying market.
Through algorithmic trading can be timed correctly to prevent significant price shocks.
How does algorithm trading work?
Say, we might face a golden cross and death cross scenario where we feed instructions to the programme to purchase 100 shares of a stock when the 50-day moving average moves above the 200-day moving average and sell the securities as soon as the 50-day moving average goes below the 200-day moving average.
Using this set of two instructions, a computer programme can be written that will automatically monitor the stock price, and based on the commands given the automated trading can place the buy or sell stocks when the defined conditions are met. The investor does not need to be present physically to monitor the live prices and graphs or sell and buy shares by itself. The algorithm does its work for the investor or trader efficiently.
Top three strategies to sell and buy stocks using algorithmic trading
Here are the strategies where algorithmic trading benefits the investor:
Algorithmic strategies can help to decode a trend or early reversal of it. The strategies in algorithmic trading are based on price, volume, support, resistance, moving averages, and other technical indicators. These are the simplest strategies to implement since these strategies do not require any predictions or price forecasts. Trades take place based on desirable trends that are straightforward to programme using algorithms without needing to go into predictive analysis.
In stock market trading position management is crucial. How well one can manage its position is what differentiates an ordinary investor from a good one. Algorithmic trading has made position sizing easier since it does not have emotions and will execute the trade as per the pre-defined instructions set on the system. For instance, one can pre-decide the value of each trade to be not more than Rs 2 lakh. If the price of a share is Rs 400 the algorithm will automatically purchase 500 shares, and if the price is Rs 1000 then the system will buy 200 shares. This results in purchasing each stock of the same value irrespective of any bias towards any stock.
We are aware of market uncertainties, hence we apply stop-loss to insulate from massive losses and manage the portfolios better. Algorithmic trading helps in modifying stop losses since markets are unpredictable. Putting stop-losses becomes a cumbersome task if the portfolio is large. Algorithms provide a convenient way to manage risk, where it can be fitted with strategies that change stop-losses on the movement of the stock in the portfolio. Any stop-losses be it trailing stop or 2% can be fitted with the algorithm.
For instance, we are putting a trailing stop loss at 3% on every position and stop-loss price changes on the positive movement of the stock. We feed this information into the algorithm that changes the price automatically. Suppose, initially if the price of a stock is Rs 100 then the stop-loss price is Rs 97, if the stock price increases to Rs 103 then stop loss becomes Rs 100, in this case, this continues until it reaches the point where stock price goes below 3% it automatically sells the stocks to help you safely exit from the trade.
Word of advice for the investors
Before plunging into algorithm trading there are few things that one needs to know:
- Knowledge of the programming language is required, since formulating these algorithms requires sound knowledge of languages such as C+, C++, Java, Python, etc. This calls for a strong programming foundation.
- Faulty algorithms have the potential to give unsurmountable losses for the trader. Recently, a company named Knight Capital launched a new algorithmic trading software which lost 10 pounds every minute due to a rogue algorithm, by the time the company wrapped its business it lost a massive 440 million pounds.
Lastly, it must be noted that not all algorithms work effectively in different market conditions.