Algorithmic trading is the process of using computers programed to follow a defined set of instructions (an algorithm) for placing a trade in order to generate profits at a speed and frequency that is impossible for a human trader. The defined sets of rules are based on timing, price, quantity or any mathematical model. Apart from profit opportunities for the trader, algo-trading makes markets more liquid and makes trading more systematic by ruling out the impact of human emotions on trading activities.
In layman terms, AlgoTrading completely eliminates the need for manual intervention. Once the rules of the logic have been coded into the Algo, it will carry out end-to-end automation of trading i.e., tracking the market for opportunity, placing the order, monitoring stop loss and risk, squaring off when required.
Algos can be used for trading on any exchange segment - equities, F&O, foreign exchange, commodities as well as cryptocurrency. Indian exchanges like NSE, BSE, MCX, NCDEX, FX, or crypto exchanges like BITMEX, BITFINEX, etc.
Consider the below examples
Using this set of two simple instructions, it is easy to write a computer program that will automatically monitor the stock price (and the moving average indicators) and place the buy and sell orders when the defined conditions are met. The trader no longer needs to keep watch for live prices and graphs, or put in the orders manually. The algorithmic trading system automatically does it for him, by correctly identifying the trading opportunity and executing the trading order.
The regulation demands that the broker should take the approval on your behalf, you as a retail trader cannot go to the exchange and ask for approval. What is Backtesting?
In algorithmic trading, backtesting is the process of defining your idea and testing it against historical data. Doing so, you will immediately see if there was any merit in your idea, or not.
With good backtesting software and coding, backtesting is very easy as soon as you’ve understood the basics of the coding language and trading platform. Still, backtesting is not as simple as testing the idea, and then start trading.
Paper Trading : A paper trade is simulated trading which allows investors to buy and sell securities without risking real money.
Live – Offline : Assume your broker is not algo enabled. No worries. Once the strategy is ready to take a trade we will reach out to you or your broker using a wide gamut of communication methods (whatsapp, email, SMS, voice call). And then leave the rest to you and broker to take forward in whatever manner you are comfortable with.
Live – Auto oneclick : You are in control every step of the way and can choose to execute these trades only after you give a one-click confirmation. Live – Fully Auto : Your strategy will be executed automatically without seeking any confirmation from you.
Benefits of Algorithmic Trading
Algorithmic trading provides the following benefits:
The method is used in multiple forms of trading and investment activities. Following are some – Mid to long-term investors Buy-side firms such as pension funds, mutual funds, insurance companies, etc.
Risks Involved in the Trading System
Every strategy for implementing algorithmic trading requires an identified opportunity that is profitable in terms of improved earning or cost reduction. Following are the most used strategies of algorithmic trading;
The trend is the most commonly used trading strategy.
The trends used are moving averages, breakout, price level movement, etc. This is the most straightforward strategy to implement, as the strategy does not require any prediction of price.
Trades are executed based on a popular trend that is easy and straightforward to implement. For example, 30-day, 50-day, and 200-day moving average are the most popular trends used.
Some of the models such as delta-neutral, allow trading on a combination of options and underlying security. For novice readers, delta neutral is a portfolio strategy that comprises of positions offsetting the positive and negative delta. Delta is the ratio that compares the change in the price of the asset to its corresponding derivative.
The said strategy is based on the concept of high and low price of an asset which is temporary and the price reverts to the mean value over time. In this strategy, the main component is to identify and define the price range and thereby implementing the algorithm.
The strategy breaks a large order and releases a smaller chunk of order using historical volume profile for every stock. It seeks to execute the order close to the volume-weighted average price (VWAP).
The strategy breaks a large order and releases a smaller chunk of order using evenly divided time slots between a start and an end time. The strategy seeks to execute the order close to the average price between the start and end times.
In the strategy, the algorithm sends partial orders according to the defined participation ratio and volume traded in the market. .
Implementing the method of algorithmic trading requires a computer program. A computer program accompanied by backtesting completes the need from an execution standpoint. However, the challenge is to transform the strategies mentioned above into an integrated computerized process including access to the trading account for placing orders. .
Following are the technical requirements of algorithmic trading – computer programming – required to program the trading strategy using any language. One can use an existing trading platform as well.